Plaintext
Modular Electronics Learning (ModEL)
project
* SPICE ckt
v1 1 0 dc 12
v2 2 1 dc 15
r1 2 3 4700
r2 3 0 7100
.dc v1 12 12 1
.print dc v(2,3)
.print dc i(v2)
.end
V=IR
PN Junctions and Diodes
c 2019-2022 by Tony R. Kuphaldt – under the terms and conditions of the
Creative Commons Attribution 4.0 International Public License
Last update = 28 November 2022
This is a copyrighted work, but licensed under the Creative Commons Attribution 4.0 International
Public License. A copy of this license is found in the last Appendix of this document. Alternatively,
you may visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative
Commons: 171 Second Street, Suite 300, San Francisco, California, 94105, USA. The terms and
conditions of this license allow for free copying, distribution, and/or modification of all licensed
works by the general public.
ii
Contents
1 Introduction 3
2 Tutorial 5
3 Historical References 13
3.1 Crystal detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4 Programming References 17
4.1 Programming in C++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
4.2 Programming in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3 Modeling a diode using C++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5 Animations 37
5.1 Animation of a forward-biased PN diode junction . . . . . . . . . . . . . . . . . . . . 38
6 Questions 63
6.1 Conceptual reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
6.1.1 Reading outline and reflections . . . . . . . . . . . . . . . . . . . . . . . . . . 68
6.1.2 Foundational concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6.1.3 Motor-effect eliminator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
6.1.4 Temperature sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
6.1.5 Curve tracer circuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
6.1.6 Diode modeled as a source . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.1.7 Diode frequency limit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6.2 Quantitative reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.2.1 Miscellaneous physical constants . . . . . . . . . . . . . . . . . . . . . . . . . 78
6.2.2 Introduction to spreadsheets . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.2.3 Voltages and currents in simple diode circuits . . . . . . . . . . . . . . . . . . 82
6.2.4 LED resistor sizing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
6.3 Diagnostic reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6.3.1 Faults in a diode-resistor network . . . . . . . . . . . . . . . . . . . . . . . . . 85
6.3.2 Diode-testing circuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
A Problem-Solving Strategies 87
iii
CONTENTS 1
B Instructional philosophy 89
C Tools used 95
D Creative Commons License 99
E References 107
F Version history 109
Index 110
2 CONTENTS
Chapter 1
Introduction
The PN semiconductor junction is the basis for most solid-state electronic devices, with diodes being
the simplest and most direct application.
Important concepts related to diodes and PN semiconductor junctions include electric charge
carrier motion, atomic structure, electrons versus holes, semiconductor doping, depletion
regions, the Shockley diode equation, exponential functions, electrical sources versus loads,
and diode ratings.
Here are some good questions to ask of yourself while studying this subject:
• How might an experiment be designed and conducted to measure the forward voltage drop of
a PN junction? What hypothesis (i.e. prediction) might you pose for that experiment, and
what result(s) would either support or disprove that hypothesis?
• What are some practical applications of PN-junction electronic devices?
• How do vacuum-tube electronic devices function?
• How does the operation of a solid-state electronic device compare to that of a vacuum tube?
• How do electric charge carriers move through a semiconducting material?
• Why are solid-state diodes more energy-efficient than vacuum-tube diodes?
• Why does a depletion region form at the interface of P-type and N-type semiconductor
materials?
• Why is this “depletion region” called that? In what way is it depleted?
• What factors influence the size of a depletion region?
• What does bias mean with reference to a semiconductor diode?
• How do voltage and current relate to each other mathematically in a semiconductor diode?
• What are some common applications of PN junctions?
3
4 CHAPTER 1. INTRODUCTION
• Are diodes electrical sources or electrical loads?
• How may we electrically test a diode for proper operation?
• How do PN junctions tend to fail, compared to other common components such as resistors,
capacitors, and/or inductors?
• What are some of the electrical limitations typically associated with diodes (e.g. ratings)?
• How do VOMs and DMMs differ in their ability to test diodes?
• How is it possible for a DMM to measure electrical resistance in a circuit without forward-
biasing any PN junctions?
A helpful strategy for “actively” reading the Tutorial text is to apply the Shockley diode equation
to the computer-simulated results presented to you in the text. Don’t just read the results, but
instead use a calculator to see if you can get results similar to those output by the circuit simulation
software.
Chapter 2
Tutorial
Electronic components function by manipulating the energy states of electrons inside of it. The
original electronic devices utilized glass tubes evacuated of air (called vacuum tubes or electron
tubes) inside of which metal electrodes were placed. One electrode was heated to a dull glow by
an electrically-energized filament (similar to an incandescent lamp) while the other electrode was
constructed of unheated metal. Electrons within the heated electrode possessed more energy than
electrons within the unheated electrode by virtue of the filament’s heating, and this permitted
electrons to leave the heated metal surface and enter the vacuum space – a phenomenon called
thermionic emission – where they could travel to and be collected by the unheated metal electrode.
Travel in the other direction was prohibited by the lack of thermal energy at the unheated electrode,
where electrons there could not leave to enter the vacuum space. Thus, these early vacuum tubes
naturally functioned as one-way “valves” for small electrical currents.
The heated electrode of a vacuum tube is called the cathode and the unheated “collector”
electrode the anode. As with all uses of these terms, the cathode is intended to be the negative
pole of the device while the anode is intended to be the positive pole. This makes sense based on
the operational principle of a vacuum tube, where (negatively-charged) electrons may travel from
the hot cathode to the cold anode but not in the other direction. These particular vacuum tubes
became known as diodes in honor of having two electrodes. Later tube designs with three, four, and
five electrodes became known as triodes, tetrodes, and pentodes, respectively:
Current
(conventional notation)
No current
Diode tube
Anode
Current
(electron motion)
Cathode
Filament
5
6 CHAPTER 2. TUTORIAL
Vacuum-tubes ushered in the era of electronics with their ability to control the flow of electric
current in ways that were impossible with “passive” components such as resistors, capacitors,
inductors, transformers, etc. However, vacuum-tube devices had significant limitations, among
them being fragility (their glass envelopes were easily broken), high power demands (to maintain
the cathode in a state of dull-red glowing temperature), and short life (due to the thin filaments
breaking as well as air inevitably finding its way back into the tube’s interior space). The next great
breakthrough in electronic devices was the invention of so-called solid-state components where the
travel of electrons occurred though solid crystalline materials rather than through empty vacuums.
Specifically, a class of materials know as semiconductors permitted construction of solid-state diode
and transistor components.
A “semiconducting” material is any substance whose electrons are very nearly free to move
throughout. Substantial numbers of electrons residing within good conductors, by contrast, exist
at sufficiently high energy levels to be entirely “unbound” from their parent atoms, and as such
may freely drift throughout that solid’s volume in response to any applied electric field. Electrons
within the atoms of an insulating material exist at much lower energy levels, being tightly bound to
their constituent atoms and unable to drift about. The nearly-conductive nature of semiconducting
substances permits their higher-energy electrons to be manipulated to produce electrical conductivity
on demand, much like vacuum tubes but without the high power requirements of heating and without
the mechanical challenge of maintaining vacuum-tight seals. The most popular semiconducting
material in modern use is the element silicon, found in the same vertical “group” of the Periodic
Table of the Elements as the elements carbon, germanium, tin, and lead.
Semiconductor conductivity depends on a range of factors including temperature, exposure to
light, addition of impurities, and the presence of electric fields to name a few. We may construct
a diode from semiconducting materials by forming a “sandwich” of two differently-alloyed layers
(called P-type and N-type). N-type semiconductors contain specific alloying elements contributing
extra electrons to the crystalline lattice of the base material (e.g. phosphorus added to silicon),
and these electrons naturally inhabit higher energy states than the electrons of the base material,
allowing them to drift about like free electrons through metal. P-type semiconductor contain alloying
elements contributing electron vacancies to the crystalline lattice (e.g. boron added to silicon). These
vacancies, called holes, serve as waypoints for low-energy electrons to reside, and with enough of
these “holes” in the crystalline lattice it becomes possible for electrons to move about1 at far less
energy than would normally be required for them to leave their original atoms.
When P-type and N-type semiconductor materials contact each other, high-energy “free”
electrons from the N-type material fall into low-energy holes in the adjacent P-type material. This
creates a thin region at the PN junction devoid of both free electrons and holes, i.e. a region depleted
of charge carriers that might contribute to an electric current. The so-called depletion region is
rather thin because its formation creates an internal electric field repelling additional electrons that
might otherwise cross over and fill more holes. The width of this depletion region varies with the
application of an external voltage: if we apply voltage with a polarity aiding the depletion region’s
internal electric field, the region grows larger and less conductive; if the external voltage’s polarity
cancels the depletion region’s internal electric field, the region grows thinner and more conductive.
1 In fact, the holes themselves may be thought to move in the opposite direction of the electrons occupying them,
much like an air bubble moves through water opposite to the direction of the water molecules immediately adjacent
to the bubble.
7
We may summarize these key behaviors of semiconductor materials by way of illustration:
No current!
I I
−
−
−
+
+
+
Pure (intrinsic)
semiconductor N-type semiconductor P-type semiconductor
(free electrons) ("holes")
No current! No current!
I
−
−
+
+
Depletion region Depletion region Depletion region
N-type P-type N-type P-type N-type P-type
(Reverse bias) (No bias) (Forward bias)
As these illustrations show, a pure sample of semiconducting material such as silicon is essentially
non-conducting unless and until it is alloyed (“doped”) with impurities making either N-type or P-
type. Either type of doping enhances conductivity, with greater doping resulting in more conductivity
because more charge carriers are available to move within the material. The joining of N-type and
P-type materials results in a depletion region, the width of that region controllable by a DC voltage
applied across the junction. Connecting a DC voltage source with positive applied to the N-side and
negative to the P-side expands the depletion region and prevents current. Reversing the DC voltage
source’s polarity to make the N-side negative and the P-side positive collapses the depletion region
and permits current. Thus, a PN junction serves the same functional purpose as a vacuum-tube
diode but with much greater efficiency and ruggedness.
Semiconductor diodes are simple, two-terminal diodes with anode and cathode terminals. Its
symbol is an arrowhead meeting with a perpendicular line. The arrowhead points in the direction of
“conventional flow” current notation. A colored stripe toward one end of the physical device marks
the cathode terminal:
Diode symbol
Forward-biased Reverse-biased
Diode construction I
−
Anode Cathode + + (effectively
P N V − V open)
Diode package I
A PN junction connected with N-type negative and P-type positive (i.e. the polarity necessary
for conduction) is said to be forward-biased, while the opposite polarity makes the PN junction
reverse-biased.
8 CHAPTER 2. TUTORIAL
The energy required to collapse the depletion region of a PN junction is small, but results in
a relatively constant voltage drop when conducting. In other words, a forward-biased diode does
not conduct as well as a metal wire (which extracts very little energy loss from passing charge
carriers), but imposes an “energy penalty” on every passing charge carrier. This energy demand is
not proportional to current, and so diodes do not obey2 Ohm’s Law. Instead, the forward voltage
drop of a semiconductor diode is primarily a function of the type of semiconducting material it is
made of, and secondarily a function of temperature3 . Silicon diodes typically exhibit 0.5 to 0.7 Volts
of forward-bias drop, while germanium diodes typically drop 0.3 Volts or less.
The Shockley diode equation, named after William Shockley, predicts forward-bias current as a
function of applied voltage and temperature:
qV
I = IS e nKT − 1
Where,
I = Forward-bias current through the diode, Amperes
IS = Reverse-bias saturation current4 through the diode, Amperes
e = Euler’s constant (≈ 2.71828)
V = Voltage applied to the PN junction externally, Volts
q = Elementary charge of an electron (1.602 × 10−19 Coulombs)
n = Ideality factor (1 for a perfect junction)
k = Boltzmann’s constant (1.3806504 × 10−23 J / K)
T = Absolute temperature (Kelvin), 273.15 more than degrees Celsius
2 Ohm’s Law is not so much a physical law as it is a definition of electrical resistance (R = V ). Voltage and
I
current do not remain in fixed proportion for PN junctions as they do for resistors, and so a diode does not exhibit a
V
constant I ratio like a resistor does. This is what we really mean by saying that diodes “do not obey Ohm’s Law”.
3 This forward-bias voltage drop becomes smaller as temperature rises, because thermal energy assists charge
carriers crossing the depletion zone and therefore less electrical energy is needed. Interestingly, this relationship
between forward voltage drop and temperature for a semiconductor diode is precise enough to permit the use of
diodes as electronic temperature sensors!
4 A very small amount of current will still flow in the reverse-biased condition, due to so-called minority carriers
in the P and N halves of the diode. This tiny current, usually in the range of nano-Amperes, is referred to as the
reverse saturation current because its value does not increase appreciably with greater reverse-bias voltage but rather
“saturates” or “plateaus” at a constant value. This saturation current, while fairly independent of applied voltage,
varies greatly with changes in device temperature.
9
The following graph shows calculated current values for a typical diode in forward-bias mode,
for an applied voltage varying from 0 Volts to 800 milliVolts (0.8 Volts):
mA i(vamm)
300.0
250.0
200.0
150.0
100.0
50.0
0.0
0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0
v-sweep mV
As shown by the graph, the diode’s forward current does not become significant until the applied
voltage is well in excess of 0.5 Volt. A computer simulation for this particular diode5 yields forward-
bias current values of 567.7 × 10−15 Amperes at 0.1 Volt, 52.06 × 10−9 Amperes at 0.4 Volts, 0.1188
× 10−3 Amperes at 0.6 Volts, 5.675 mA at 0.7 Volts, and 271.1 mA at 0.8 Volts. For reasons of
simplicity, a constant forward voltage drop of 0.5 Volts to 0.7 Volts is often assumed for silicon
diodes at modest current values. This voltage drop means that diodes behave as electrical loads,
with charge carriers losing some energy in the form of heat and light as they pass through the diode
in its conductive state.
Many different types of diodes exist, some designed to function as rectifiers (acting as one-way
valves for electric power), others designed to produce very constant amounts of voltage drop, and
yet others designed to emit light (i.e. light-emitting diodes, or LEDs). A photovoltaic cell or solar
cell is a special-purpose diode with its PN junction exposed to sunlight to produce electricity when
illuminated, acting as an electrical source rather than an electrical load. Diodes may also be used as
temperature-sensing devices, since temperature has a very strong effect on the junction’s saturation
current value (IS ).
5 This simulation used a saturation current value of approximately 1.10326 × 10−14 Amperes and a junction
temperature of approximately 28 degrees Celsius (approximately 301 Kelvin).
10 CHAPTER 2. TUTORIAL
PN junctions – whether found in a plain diode or in any other semiconductor device – are easy
to test using a multimeter. An analog Volt-Ohm-Milliammeter (VOM) can test a PN junction using
its resistance (Ohms) mode, the meter’s internal battery serving as the electrical source that either
forward- or reverse-biases the PN junction:
∞Ω 0Ω ∞Ω 0Ω
50 µAMPS 50 µAMPS
-10 A +1 V 250 MV +10 A -10 A +1 V 250 MV +10 A
500 MA 500 MA
TRANSIT 100 MA TRANSIT 100 MA
2.5 V 10 MA 2.5 V 10 MA
1V AMPS 1V AMPS
+DC +DC
-DC AC 10 V 1 MA ZERO OHMS -DC AC 10 V 1 MA ZERO OHMS
50 V Rx1 50 V Rx1
µAMPS µAMPS
250 V Rx100 250 V Rx100
1000 V 1000 V
COMMON 500 V Rx10,000 OUTPUT AC DC COMMON 500 V Rx10,000 OUTPUT AC DC
1000V 1000V
Meter forward-biases Meter reverse-biases
the PN junction the PN junction
current
no current
N P N P
When forward-biased, the meter will register a low resistance signifying conductivity; when
reverse-biased the meter will show infinite resistance (open). A failed-open PN junction will exhibit
extremely high resistance in both polarities, while a failed-shorted PN junction will register low
resistance in both directions. Interestingly, PN junctions tend to fail shorted more often than many
other types of components such as resistors.
11
Most digital multimeters (DMMs) provide a special diode test function in addition to
resistance/continuity testing, the diode test mode displaying the voltage dropped by the PN junction
when the meter passes a small amount of current through it.
0 0.5 1.0 0 0.5 1.0
MIN MAX RANGE HOLD MIN MAX RANGE HOLD
REL ∆ Hz REL ∆ Hz
PEAK MIN MAX PEAK MIN MAX
Ω Ω
mV mV
mA mA
V A V A
V µA V µA
OFF OFF
A mA µA COM VΩ A mA µA COM VΩ
400 mA 400 mA
fused fused
10 A fused 10 A fused
Meter forward-biases Meter reverse-biases
the PN junction the PN junction
current
no current
N P N P
Such a voltage-drop measurement is far better-suited to the testing of a PN junction than
an analog ohmmeter’s indication, since the voltage/current characteristics of a forward-biased PN
junction do not obey Ohm’s Law and therefore does not have “resistance” in the regular sense of
the word.
Furthermore, the resistance function (not the diode-test function) of such a DMM is designed to
apply a test voltage significantly less than 0.7 Volts so that it cannot forward-bias any PN junction
to the point of significant conduction. This is designed intentionally so that PN junctions will
not be “activated” by the meter when the user’s intent is to strictly measure Ohmic resistance
of other components – a particulary useful feature when PN-junction devices are found connected
in-circuit with resistors and other devices, and you only wish to measure the resistance of the non-
semiconductor devices.
12 CHAPTER 2. TUTORIAL
Diodes, like all electrical components, have ratings which must be respected for reliable operation.
The following list shows some of the more important ratings typical for diodes:
• Maximum average forward current – the amount of continuous forward current the diode
should be able to carry
• Maximum surge forward current – the amount of forward current the diode should be
able to carry for brief periods of time (typically milliseconds)
• Typical forward voltage – the amount of voltage drop expected under normal operating
conditions.
• DC blocking voltage – the amount of continuous reverse-bias voltage the diode should be
able to withstand without “breaking down” and passing reverse current
• Peak inverse voltage – also called “peak reverse voltage”, this is the amount of reverse-bias
voltage the diode should be able to momentarily withstand while still preventing current
The best source of information for any particular diode’s ratings is the manufacturer’s datasheet.
Chapter 3
Historical References
This chapter is where you will find references to historical texts and technologies related to the
module’s topic.
Readers may wonder why historical references might be included in any modern lesson on a
subject. Why dwell on old ideas and obsolete technologies? One answer to this question is that the
initial discoveries and early applications of scientific principles typically present those principles in
forms that are unusually easy to grasp. Anyone who first discovers a new principle must necessarily
do so from a perspective of ignorance (i.e. if you truly discover something yourself, it means you must
have come to that discovery with no prior knowledge of it and no hints from others knowledgeable in
it), and in so doing the discoverer lacks any hindsight or advantage that might have otherwise come
from a more advanced perspective. Thus, discoverers are forced to think and express themselves
in less-advanced terms, and this often makes their explanations more readily accessible to others
who, like the discoverer, comes to this idea with no prior knowledge. Furthermore, early discoverers
often faced the daunting challenge of explaining their new and complex ideas to a naturally skeptical
scientific community, and this pressure incentivized clear and compelling communication. As James
Clerk Maxwell eloquently stated in the Preface to his book A Treatise on Electricity and Magnetism
written in 1873,
It is of great advantage to the student of any subject to read the original memoirs on
that subject, for science is always most completely assimilated when it is in its nascent
state . . . [page xi]
Furthermore, grasping the historical context of technological discoveries is important for
understanding how science intersects with culture and civilization, which is ever important because
new discoveries and new applications of existing discoveries will always continue to impact our lives.
One will often find themselves impressed by the ingenuity of previous generations, and by the high
degree of refinement to which now-obsolete technologies were once raised. There is much to learn
and much inspiration to be drawn from the technological past, and to the inquisitive mind these
historical references are treasures waiting to be (re)-discovered.
13
14 CHAPTER 3. HISTORICAL REFERENCES
3.1 Crystal detectors
An important component within primitive AM (amplitude-modulation) radio receiver circuits is the
detector, which is basically a diode with a very high frequency capability. Vacuum-tube diodes
are one early technology suitable for this task, but others exist as well. The following US patent
(number 879,117) describes a solid-state diode constructed of naturally occurring crystal materials,
which of course enjoys the advantages of physical ruggedness and lower power requirements than a
heated-filament vacuum tube.
The inventor in this patent, George W. Pierce of the Massachusetts Wireless Equipment
Company, describes the purpose and application of his crystal-based detector in a set of paragraphs
found on page 1:
The invention relates to rectifiers and detectors for electric currents or electric oscillations
and more particularly to rectifiers and detectors such as may be successfully used as
receivers in wireless telegraphy or electric wave signaling systems.
In practicing my invention I employ as a rectifier or detector a substance known as
hessite which occurs in nature usually as telluride of silver, although the silver is
sometimes wholly or partially replaced by gold. I have discovered that this substance is
asymmetrically conductive when used in connection with small currents, and I have also
discovered that by reason of this property of asymmetrical conductivity and possibly
of other unknown properties this substance when properly placed between conductive
electrodes is highly sensitive as a receiver for electromagnetic waves.
The rectifying or detecting material may be utilized in many and various shapes and may
be connected in the circuit of the receiving or other apparatus, in various ways. [page
1]
3.1. CRYSTAL DETECTORS 15
Key to realizing the “asymmetrical conductivity” of these crystals is the means of electrical
contact made with their faces. The inventor describes and illustrates three different methods he
found to function well:
In the arrangement of Fig. 1, a piece a of hessite, is held in a clamp, the jaws b and c of
which form electrodes making contact with the rectifying or detecting material.
I have secured the best results by cutting a piece from a crystal on a plane substantially
at right angles to its axis and engaging, one of the electrodes with a point or corner of
the crystal so that a small area of contact is secured.
In the arrangement of Fig.2 a crystal or fragment of a crystal d is held in an ordinary
jewel mounting and a point of the crystal is engaged by a metallic spring e. The contact
between the spring e and the detecting material may be adjusted by a screw f to secure
the character of contact which will give the best results.
In the arrangement shown in Fig. 3 a piece g of hessite is sealed in the end of a glass
tube h. The piece g is in contact with a mass of conducting liquid within the tube h
and with a second mass of conducting liquid within a receptacle i, the masses of liquid
forming the electrodes which contact with the piece g. The liquid should be such that it
will not act destructively upon the piece g.
Any other suitable form and arrangement of the electrodes and of the rectifying or
detecting material may be employed which may be found desirable or best suited to the
conditions under which the particular apparatus in which the invention is embodied is
to be used. [page 1]
It should be apparent from Pierce’s descriptions that the theory of crystal diode behavior was
not understood at that time. One would simply obtain a piece of crystal and experiment with
different attachment methods until suitable rectification occurred. Radio technicians would later
come to refer to the crystal-based detectors as cat’s whisker detectors because they often employed
a spring-steel wire (the “whisker”) for one contact point on the crystal, the optimum placement of
that spring wire being a matter of trial and error.
16 CHAPTER 3. HISTORICAL REFERENCES
Chapter 4
Programming References
A powerful tool for mathematical modeling is text-based computer programming. This is where
you type coded commands in text form which the computer is able to interpret. Many different
text-based languages exist for this purpose, but we will focus here on just two of them, C++ and
Python.
17
18 CHAPTER 4. PROGRAMMING REFERENCES
4.1 Programming in C++
One of the more popular text-based computer programming languages is called C++. This is a
compiled language, which means you must create a plain-text file containing C++ code using a
program called a text editor, then execute a software application called a compiler to translate your
“source code” into instructions directly understandable to the computer. Here is an example of
“source code” for a very simple C++ program intended to perform some basic arithmetic operations
and print the results to the computer’s console:
#include <iostream>
using namespace std;
int main (void)
{
float x, y;
x = 200;
y = -560.5;
cout << "This simple program performs basic arithmetic on" << endl;
cout << "the two numbers " << x << " and " << y << " and then" << endl;
cout << "displays the results on the computer’s console." << endl;
cout << endl;
cout << "Sum = " << x + y << endl;
cout << "Difference = " << x - y << endl;
cout << "Product = " << x * y << endl;
cout << "Quotient of " << x / y << endl;
return 0;
}
Computer languages such as C++ are designed to make sense when read by human programmers.
The general order of execution is left-to-right, top-to-bottom just the same as reading any text
document written in English. Blank lines, indentation, and other “whitespace” is largely irrelevant
in C++ code, and is included only to make the code more pleasing1 to view.
1 Although not included in this example, comments preceded by double-forward slash characters (//) may be added
to source code as well to provide explanations of what the code is supposed to do, for the benefit of anyone reading
it. The compiler application will ignore all comments.
4.1. PROGRAMMING IN C++ 19
Let’s examine the C++ source code to explain what it means:
• #include <iostream> and using namespace std; are set-up instructions to the compiler
giving it some context in which to interpret your code. The code specific to your task is located
between the brace symbols ({ and }, often referred to as “curly-braces”).
• int main (void) labels the “Main” function for the computer: the instructions within this
function (lying between the { and } symbols) it will be commanded to execute. Every complete
C++ program contains a main function at minimum, and often additional functions as well,
but the main function is where execution always begins. The int declares this function will
return an integer number value when complete, which helps to explain the purpose of the
return 0; statement at the end of the main function: providing a numerical value of zero at
the program’s completion as promised by int. This returned value is rather incidental to our
purpose here, but it is fairly standard practice in C++ programming.
• Grouping symbols such as (parentheses) and {braces} abound in C, C++, and other languages
(e.g. Java). Parentheses typically group data to be processed by a function, called arguments
to that function. Braces surround lines of executable code belonging to a particular function.
• The float declaration reserves places in the computer’s memory for two floating-point
variables, in this case the variables’ names being x and y. In most text-based programming
languages, variables may be named by single letters or by combinations of letters (e.g. xyz
would be a single variable).
• The next two lines assign numerical values to the two variables. Note how each line terminates
with a semicolon character (;) and how this pattern holds true for most of the lines in this
program. In C++ semicolons are analogous to periods at the ends of English sentences. This
demarcation of each line’s end is necessary because C++ ignores whitespace on the page and
doesn’t “know” otherwise where one line ends and another begins.
• All the other instructions take the form of a cout command which prints characters to
the “standard output” stream of the computer, which in this case will be text displayed
on the console. The double-less-than symbols (<<) show data being sent toward the cout
command. Note how verbatim text is enclosed in quotation marks, while variables such as x
or mathematical expressions such as x - y are not enclosed in quotations because we want
the computer to display the numerical values represented, not the literal text.
• Standard arithmetic operations (add, subtract, multiply, divide) are represented as +, -, *,
and /, respectively.
• The endl found at the end of every cout statement marks the end of a line of text printed
to the computer’s console display. If not for these endl inclusions, the displayed text would
resemble a run-on sentence rather than a paragraph. Note the cout << endl; line, which
does nothing but create a blank line on the screen, for no reason other than esthetics.
20 CHAPTER 4. PROGRAMMING REFERENCES
After saving this source code text to a file with its own name (e.g. myprogram.cpp), you would
then compile the source code into an executable file which the computer may then run. If you are
using a console-based compiler such as GCC (very popular within variants of the Unix operating
system2 , such as Linux and Apple’s OS X), you would type the following command and press the
Enter key:
g++ -o myprogram.exe myprogram.cpp
This command instructs the GCC compiler to take your source code (myprogram.cpp) and create
with it an executable file named myprogram.exe. Simply typing ./myprogram.exe at the command-
line will then execute your program:
./myprogram.exe
If you are using a graphic-based C++ development system such as Microsoft Visual Studio3 , you
may simply create a new console application “project” using this software, then paste or type your
code into the example template appearing in the editor window, and finally run your application to
test its output.
As this program runs, it displays the following text to the console:
This simple program performs basic arithmetic on
the two numbers 200 and -560.5 and then
displays the results on the computer’s console.
Sum = -360.5
Difference = 760.5
Product = -112100
Quotient of -0.356824
As crude as this example program is, it serves the purpose of showing how easy it is to write and
execute simple programs in a computer using the C++ language. As you encounter C++ example
programs (shown as source code) in any of these modules, feel free to directly copy-and-paste the
source code text into a text editor’s screen, then follow the rest of the instructions given here (i.e.
save to a file, compile, and finally run your program). You will find that it is generally easier to
2 A very functional option for users of Microsoft Windows is called Cygwin, which provides a Unix-like console
environment complete with all the customary utility applications such as GCC!
3 Using Microsoft Visual Studio community version 2017 at the time of this writing to test this example, here are
the steps I needed to follow in order to successfully compile and run a simple program such as this: (1) Start up
Visual Studio and select the option to create a New Project; (2) Select the Windows Console Application template,
as this will perform necessary set-up steps to generate a console-based program which will save you time and effort
as well as avoid simple errors of omission; (3) When the editing screen appears, type or paste the C++ code within
the main() function provided in the template, deleting the “Hello World” cout line that came with the template; (4)
Type or paste any preprocessor directives (e.g. #include statements, namespace statements) necessary for your code
that did not come with the template; (5) Lastly, under the Debug drop-down menu choose either Start Debugging
(F5 hot-key) or Start Without Debugging (Ctrl-F5 hotkeys) to compile (“Build”) and run your new program. Upon
execution a console window will appear showing the output of your program.
4.1. PROGRAMMING IN C++ 21
learn computer programming by closely examining others’ example programs and modifying them
than it is to write your own programs starting from a blank screen.
22 CHAPTER 4. PROGRAMMING REFERENCES
4.2 Programming in Python
Another text-based computer programming language called Python allows you to type instructions
at a terminal prompt and receive immediate results without having to compile that code. This
is because Python is an interpreted language: a software application called an interpreter reads
your source code, translates it into computer-understandable instructions, and then executes those
instructions in one step.
The following shows what happens on my personal computer when I start up the Python
interpreter on my personal computer, by typing python34 and pressing the Enter key:
Python 3.7.2 (default, Feb 19 2019, 18:15:18)
[GCC 4.1.2] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
The >>> symbols represent the prompt within the Python interpreter “shell”, signifying readiness
to accept Python commands entered by the user.
Shown here is an example of the same arithmetic operations performed on the same quantities,
using a Python interpreter. All lines shown preceded by the >>> prompt are entries typed by the
human programmer, and all lines shown without the >>> prompt are responses from the Python
interpreter software:
>>> x = 200
>>> y = -560.5
>>> x + y
-360.5
>>> x - y
760.5
>>> x * y
-112100.0
>>> x / y
-0.35682426404995538
>>> quit()
4 Using version 3 of Python, which is the latest at the time of this writing.
4.2. PROGRAMMING IN PYTHON 23
More advanced mathematical functions are accessible in Python by first entering the line
from math import * which “imports” these functions from Python’s math library (with functions
identical to those available for the C programming language, and included on any computer with
Python installed). Some examples show some of these functions in use, demonstrating how the
Python interpreter may be used as a scientific calculator:
>>> from math import *
>>> sin(30.0)
-0.98803162409286183
>>> sin(radians(30.0))
0.49999999999999994
>>> pow(2.0, 5.0)
32.0
>>> log10(10000.0)
4.0
>>> e
2.7182818284590451
>>> pi
3.1415926535897931
>>> log(pow(e,6.0))
6.0
>>> asin(0.7071068)
0.78539819000368838
>>> degrees(asin(0.7071068))
45.000001524425265
>>> quit()
Note how trigonometric functions assume angles expressed in radians rather than degrees, and
how Python provides convenient functions for translating between the two. Logarithms assume a
base of e unless otherwise stated (e.g. the log10 function for common logarithms).
The interpreted (versus compiled) nature of Python, as well as its relatively simple syntax, makes
it a good choice as a person’s first programming language. For complex applications, interpreted
languages such as Python execute slower than compiled languages such as C++, but for the very
simple examples used in these learning modules speed is not a concern.
24 CHAPTER 4. PROGRAMMING REFERENCES
Another Python math library is cmath, giving Python the ability to perform arithmetic on
complex numbers. This is very useful for AC circuit analysis using phasors 5 as shown in the following
example. Here we see Python’s interpreter used as a scientific calculator to show series and parallel
impedances of a resistor, capacitor, and inductor in a 60 Hz AC circuit:
>>> from math import *
>>> from cmath import *
>>> r = complex(400,0)
>>> f = 60.0
>>> xc = 1/(2 * pi * f * 4.7e-6)
>>> zc = complex(0,-xc)
>>> xl = 2 * pi * f * 1.0
>>> zl = complex(0,xl)
>>> r + zc + zl
(400-187.38811239154882j)
>>> 1/(1/r + 1/zc + 1/zl)
(355.837695813625+125.35793777619385j)
>>> polar(r + zc + zl)
(441.717448903332, -0.4381072059213295)
>>> abs(r + zc + zl)
441.717448903332
>>> phase(r + zc + zl)
-0.4381072059213295
>>> degrees(phase(r + zc + zl))
-25.10169387356105
When entering a value in rectangular form, we use the complex() function where the arguments
are the real and imaginary quantities, respectively. If we had opted to enter the impedance values
in polar form, we would have used the rect() function where the first argument is the magnitude
and the second argument is the angle in radians. For example, we could have set the capacitor’s
impedance (zc) as XC 6 −90o with the command zc = rect(xc,radians(-90)) rather than with
the command zc = complex(0,-xc) and it would have worked the same.
Note how Python defaults to rectangular form for complex quantities. Here we defined a 400
Ohm resistance as a complex value in rectangular form (400 +j0 Ω), then computed capacitive and
inductive reactances at 60 Hz and defined each of those as complex (phasor) values (0 − jXc Ω and
0 + jXl Ω, respectively). After that we computed total impedance in series, then total impedance in
parallel. Polar-form representation was then shown for the series impedance (441.717 Ω 6 −25.102o ).
Note the use of different functions to show the polar-form series impedance value: polar() takes
the complex quantity and returns its polar magnitude and phase angle in radians; abs() returns
just the polar magnitude; phase() returns just the polar angle, once again in radians. To find the
polar phase angle in degrees, we nest the degrees() and phase() functions together.
The utility of Python’s interpreter environment as a scientific calculator should be clear from
these examples. Not only does it offer a powerful array of mathematical functions, but also unlimited
5 A “phasor” is a voltage, current, or impedance represented as a complex number, either in rectangular or polar
form.
4.2. PROGRAMMING IN PYTHON 25
assignment of variables as well as a convenient text record6 of all calculations performed which may
be easily copied and pasted into a text document for archival.
It is also possible to save a set of Python commands to a text file using a text editor application,
and then instruct the Python interpreter to execute it at once rather than having to type it line-by-
line in the interpreter’s shell. For example, consider the following Python program, saved under the
filename myprogram.py:
x = 200
y = -560.5
print("Sum")
print(x + y)
print("Difference")
print(x - y)
print("Product")
print(x * y)
print("Quotient")
print(x / y)
As with C++, the interpreter will read this source code from left-to-right, top-to-bottom, just the
same as you or I would read a document written in English. Interestingly, whitespace is significant
in the Python language (unlike C++), but this simple example program makes no use of that.
To execute this Python program, I would need to type python myprogram.py and then press the
Enter key at my computer console’s prompt, at which point it would display the following result:
Sum
-360.5
Difference
760.5
Product
-112100.0
Quotient
-0.35682426405
As you can see, syntax within the Python programming language is simpler than C++, which
is one reason why it is often a preferred language for beginning programmers.
6 Like many command-line computing environments, Python’s interpreter supports “up-arrow” recall of previous
entries. This allows quick recall of previously typed commands for editing and re-evaluation.
26 CHAPTER 4. PROGRAMMING REFERENCES
If you are interested in learning more about computer programming in any language, you will
find a wide variety of books and free tutorials available on those subjects. Otherwise, feel free to
learn by the examples presented in these modules.
4.3. MODELING A DIODE USING C++ 27
4.3 Modeling a diode using C++
Suppose we wished to graphically plot the voltage/current characteristic function for a PN
semiconductor diode, based on the Shockley diode equation:
qV
I = IS e nKT − 1
To plot this function manually we would “plug in” a wide range of values for V , calculate
I for each one of those voltage values, and then plot those number pairs on a two-dimensional
graph. Obtaining a high-resolution graph would require many such calculations, a tedious task at
best to perform manually. This is precisely the sort of thing computers are good at: performing
mathematical calculations very quickly.
The following C++ code evaluates the Shockley diode equation at 0.7 Volts:
#include <iostream>
#include <math.h>
using namespace std;
int main(void)
{
float v, i, is, n, k, T, q;
is = 20e-9; // Reverse saturation current, 20 nA
n = 1.3; // Ideality factor, typically between 1 and 2
k = 1.38e-23; // Boltzmann’s constant, 1.380 x 10^(-23) Joules per Kelvin
T = 293.15; // Absolute temperature, 293.15 Kelvin = 20 degrees C
q = 1.602e-19; // Elementary charge of electron, 1.602 x 10^(-19) Coulombs
v = 0.7;
i = is * (exp(q * v / (n * k * T)) - 1);
cout << "Current (A)" << endl;
cout << i << endl;
return 0;
}
The result, when compiled and executed is this:
Current (A)
36.4326
28 CHAPTER 4. PROGRAMMING REFERENCES
Let’s analyze how this program works, discussing the following programming principles as we do:
• Preprocessor directives, namespaces
• The main function: return values, arguments
• Delimiter characters (e.g. { } ;)
• Variable types (float), names, and declarations
• Variable assignment/initialization (=)
• Comments (//)
• Basic arithmetic (+, -, *, /)
• Arithmetic functions (exp)
• Printing text output (cout, <<, endl)
• Loops (for)
• Comparison (<)
• Order of execution
• Compiler commands
• Redirecting console text to files (>, |, tee)
• Nested loops
The first three lines (#include and using namespace) merely instruct the compiler software how
to interpret many of the lines that follow. In this program the compiler is told to use the “standard”
namespace, and to include the iostream and math header files which define certain instructions used
later in the program such as cout and exp.
Every C++ program has a main function where execution begins. All of our code appears
between the curly-brace ({ }) symbols belonging to the main function, those braces instructing the
compiler where main’s content begins and ends.
The line beginning with float declares seven floating-point variables our program will use in its
computation. This is where we define the names of our variables, and how the compiler will know
how much of the computer’s memory to reserve to store them all. Note how C++ permits the use
of single-letter variable names as well as multi-letter names (e.g. is).
This line of code ends with a semicolon delimiter (;) telling the compiler where the line ends.
You will notice most of the lines of code end with semicolons, exceptions being main (because its
curly-brace symbols serve the same purpose) and the #include directives which are technically
set-up instructions for the compiler and not executed at run-time.
4.3. MODELING A DIODE USING C++ 29
The next five lines of code initialize several of our floating-point variables with values equal
to physical constants necessary for the Shockley diode equation, using power-of-ten notation (e.g.
1.38e-23 is equivalent to 1.38 × 10−23 ). In order to make this code more sensible to human readers,
each initialization is immediately followed by a comment. In C and C++ any text following a
double-slash (//) is completely ignored by the compiler, giving the programmer a way to include
helpful notes for future reference. Comments are an excellent practice for any programmer in any
language, as they improve the readability of the code for the benefit of anyone viewing it. This
includes the person who originally wrote the code, who might appreciate having notes when they
revisit that code years later!
Following those five initializing lines, we have one more to initialize our voltage variable (v) at
0.7 (Volts).
30 CHAPTER 4. PROGRAMMING REFERENCES
It is worth noting that we could have omitted several variables in this program and all of the
initialization lines simply by placing those exact same numerical values within the math statement
as shown in the following example:
#include <iostream>
#include <math.h>
using namespace std;
int main(void)
{
float i;
i = 20e-9 * (exp(1.602e-19 * 0.7 / (1.3 * 1.38e-23 * 293.15)) - 1);
cout << "Current (A)" << endl;
cout << i << endl;
return 0;
}
This condensed version, you might agree, is not quite as easy to understand as the original.
Once again, we see the merits of extra coding for the sake of human-readability. There are
times when terse code is better, for example when writing software for microcontrollers which
have very limited memory and processing speed. However, for the majority of modern computer
programming applications, the benefit we reap by writing easy-to-understand code usually outweighs
any performance costs.
Moving along in our exploration of the code, we come to the line where diode current gets
calculated. This is, obviously, an arithmetic function involving multiplication (*), division (/),
subtraction (-), and an exponential function (ex , coded as exp() where the exponent value x
fits within the parentheses). In the C and C++ languages, a single “equals” symbol (=) means
assignment, with the computed value on the right-hand side stored in the variable on the left-hand
side. In other words, we should read the = symbol as “set equal to”.
The cout lines instruct the computer to print text to the console of the computer so that people
can see the results. Anything directed to cout within quotation marks will be printed in its literal
form. Any variable directed to cout (e.g. cout << i) will have its numerical value printed to the
console. endl instructs the computer to “end the line” of text on the screen – without these the
two cout instructions would print as a run-on sentence rather than as two separate lines. The fact
that the two cout instructions appear as two different lines of code does not necessarily mean their
outputs will display as two different lines of text on the console. This must be explicitly instructed
by using the endl characters.
Finally, the main function concludes with a return statement instructing the computer to
4.3. MODELING A DIODE USING C++ 31
generate a numerical value at the function’s successful completion. This is not strictly necessary,
but it is a good programming practice. Note how the integer variable type precedes the main label
near the top of the program, and how the numerical value (zero) is an integer number.
Now that we have explored how this simple program functions, it’s time to make some dramatic
improvements. First and foremost, we should remedy the fact that all it does is calculate diode
current for a single voltage value (0.7 Volts). If our goal is to plot the characteristic function of a
diode, we will need a many current calculations for many different voltage values. It would be tedious
to repeatedly edit the source code and recompile just to receive one current value per execution of
the program. What would be much better would be a program that does this repetition internally.
C and C++ offer a very effective way to do this, called a for loop, shown in the following program
example:
#include <iostream>
#include <math.h>
using namespace std;
int main (void)
{
float v, i, is, n, k, T, q;
is = 20e-9; // Reverse saturation current, 20 nA
n = 1.3; // Ideality factor, typically between 1 and 2
k = 1.38e-23; // Boltzmann’s constant, 1.380 x 10^(-23) Joules per Kelvin
T = 293.15; // Absolute temperature, 293.15 Kelvin = 20 degrees C
q = 1.602e-19; // Elementary charge of electron, 1.602 x 10^(-19) Coulombs
for (v = 0.0 ; v < 0.7 ; v = v + 0.05)
{
i = is * (exp (q * v / (n * k * T)) - 1);
cout << v << " , " << i << endl;
}
return 0;
}
The for statement has a similar structure to the main function, in that it has parentheses
containing information it requires for operation, followed by a collection of code lines encapsulated
between curly-brace symbols. The indentation used in this example is not required by the
programming language, but is included to make the program easier for humans to read: seeing
each new set of braced ({ }) lines indented makes it clear to see which function or statement they
belong to.
32 CHAPTER 4. PROGRAMMING REFERENCES
Three statements contained within the for statement’s parentheses and separated by semicolons
instruct the for loop how many times to execute. The variable v will begin at a value of zero, the
loop will continue so long as v is less than 0.7 (Volts), and with each iteration v will be incremented
by 0.05 (Volts). All lines of code contained between the for statement’s braces will be executed in
normal order (left-to-right, top-to-bottom) with each iteration.
As we see in this example, with each pass through the loop the computer calculates diode current,
and then immediately prints both the voltage and current values to the console, each number pair
separated by a comma character. When run, the program generates the following output:
0 , 0
0.05 , 7.17258e-08
0.1 , 4.00681e-07
0.15 , 1.90936e-06
0.2 , 8.82863e-06
0.25 , 4.05624e-05
0.3 , 0.000186102
0.35 , 0.000853592
0.4 , 0.00391489
0.45 , 0.0179549
0.5 , 0.0823465
0.55 , 0.377665
0.6 , 1.73208
0.65 , 7.94383
These coordinate pairs are now ready to be plotted on a graph, the result being a curve for the
diode’s characteristic voltage/current function. Unfortunately, the C++ language does not include
a standard graphics library, and so instructing the computer to plot these values to a screen requires
much more advanced programming than is worth the effort to present here7 .
However, there is a simple solution useful on any computer with standard business spreadsheet
software installed (e.g. Microsoft Excel). We can run our code, and redirect its output from the
console to a text file to make it accessible to other software applications. All modern spreadsheets
are capable of reading plain-text data in comma-delimited format (i.e. numerical values separated
by comma characters), and also capable of generating scatter plots based on columns of numbers8 .
7 Many graphics libraries for C++ are system-dependent, which means they may not work on all computers, on
any operating system software. My goal in presenting programming examples is to show code that will execute on
any computer system.
8 This technique of using a spreadsheet application as a visual front-end for text-based data is very useful, and
once having mastered it you will find many practical applications on your own. As you can see, writing C++ code to
generate columns of numbers is fairly simple, which means in combination with a spreadsheet you have a ready-made
graphical interface for any code you might wish to write.
4.3. MODELING A DIODE USING C++ 33
The following instructions will show you how to accomplish this redirection. Suppose we compiled
our source code (located in a file named diode.cpp) with the following command:
g++ -o diode.exe diode.cpp
Instead of running the executable file by typing ./diode.exe we instead append that command
with a redirection character and the name of a new file we wish the text to go into:
./diode.exe > graph.csv
Our simulated voltage and current data will now be saved in a file named graph.csv. We choose
the filename suffix .csv because it stands for comma-separated values which any modern spreadsheet
software should understand. After opening this file using the spreadsheet application, we will see
the voltage and current values appearing in separate columns of the workbook. Simply highlight
those columns and then command the spreadsheet to insert a graph (i.e. chart) of the scatter-plot
style.
If you are using a computer system lacking a command-line interface, and therefore cannot
redirect your C++ program’s output, you still have the option of selecting and copying the text
using the computer’s mouse (left-click and drag over the text, then press <Ctrl>-C to copy) and
then pasting that text (press <Ctrl>-V) into an open spreadsheet window. The following screenshot
shows the graphic plot generated from this text data, using Microsoft Excel version 2010:
34 CHAPTER 4. PROGRAMMING REFERENCES
Another option we have with for loops is nesting them inside of each other. This is useful in
our diode-modeling program for plotting current as a function of two variables, for instance voltage
(V ) and the ideality factor (n). Examine the following C++ code example:
#include <iostream>
#include <math.h>
using namespace std;
int main (void)
{
float v, i, is, n, k, T, q;
is = 20e-9; // Reverse saturation current, 20 nA
n = 1.3; // Ideality factor, typically between 1 and 2
k = 1.38e-23; // Boltzmann’s constant, 1.380 x 10^(-23) Joules per Kelvin
T = 293.15; // Absolute temperature, 293.15 Kelvin = 20 degrees C
q = 1.602e-19; // Elementary charge of electron, 1.602 x 10^(-19) Coulombs
for (v = 0.0 ; v < 0.7 ; v = v + 0.05)
{
cout << v << " , " ;
for (n = 1.2 ; n < 1.5 ; n = n + 0.1)
{
i = is * (exp (q * v / (n * k * T)) - 1);
cout << i << " , " ;
}
cout << endl;
}
return 0;
}
This program is written with two for loops: an outer loop increasing v by 0.05 Volt increments,
and an inner loop incrementing n from 1.2 to 1.4 in increments of 0.1. Perhaps the most confusing
aspect of this code are the cout statements. For each new iteration of the outer loop it prints the
voltage value without an end-line character, then as the inner loop cycles it calculated and prints
current values for each n factor (at the same voltage), each of those current values preceded by a
comma character. An endl character only gets printed at the very end of the outer loop, just before
voltage gets incremented once more. The result of all this is a set of printed text lines, each line
starting with the voltage value, followed by comma-separated current values (each representing a
different ideality factor).
4.3. MODELING A DIODE USING C++ 35
Here is what the output of this program looks like when printed to the console:
0 , 0 , 0 , 0
0.05 , 8.41389e-08 , 7.17258e-08 , 6.22705e-08
0.1 , 5.22246e-07 , 4.00681e-07 , 3.18422e-07
0.15 , 2.80345e-06 , 1.90936e-06 , 1.37211e-06
0.2 , 1.46815e-05 , 8.82862e-06 , 5.70646e-06
0.25 , 7.65301e-05 , 4.05623e-05 , 2.3536e-05
0.3 , 0.000398573 , 0.000186102 , 9.6878e-05
0.35 , 0.00207543 , 0.000853591 , 0.000398573
0.4 , 0.0108068 , 0.00391489 , 0.0016396
0.45 , 0.0562703 , 0.0179549 , 0.0067446
0.5 , 0.292997 , 0.0823464 , 0.0277442
0.55 , 1.52562 , 0.377664 , 0.114126
0.6 , 7.94382 , 1.73208 , 0.469462
0.65 , 41.3631 , 7.94382 , 1.93115
As with the simpler two-column output, this text data is ready to be entered into a spreadsheet
application and graphically plotted as a “family” of curves representing diode current for three
different diodes (with ideality factors of 1.2, 1.3, and 1.4).
A screenshot showing Microsoft Excel displaying this data as a “scatter plot” appears next:
Columns A through D are highlighted to select the data to be plotted. By default, Excel regards
data in the first column as the independent variable (i.e. data for the graph’s horizontal axis) and
data in all subsequent columns as dependent variables for different functions. Each function is then
named Series1, Series2, etc. and plotted in different colors on the same space. The result is our
desired “family” of curves for diodes having three different ideality factors. Note how Excel has
automatically re-scaled the vertical axis to accommodate the “tallest” of the three functions.
36 CHAPTER 4. PROGRAMMING REFERENCES
Chapter 5
Animations
Some concepts are much easier to grasp when seen in action. A simple yet effective form of animation
suitable to an electronic document such as this is a “flip-book” animation where a set of pages in the
document show successive frames of a simple animation. Such “flip-book” animations are designed
to be viewed by paging forward (and/or back) with the document-reading software application,
watching it frame-by-frame. Unlike video which may be difficult to pause at certain moments,
“flip-book” animations lend themselves very well to individual frame viewing.
37
38 CHAPTER 5. ANIMATIONS
5.1 Animation of a forward-biased PN diode junction
The following animation illustrates the behavior of mobile1 charge carriers inside a semiconductor
diode junction. A DC voltage source provides forward-biasing voltage to the PN junction, and
this voltage source’s value is progressively raised until the diode begins to conduct. Energy levels
within the diode’s semiconductor halves are shown relative to one another by means of height in the
illustration.
1 In this animation, immobile electrons in the valence band are not shown – only the holes in that band.
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 39
P N
Conduction band
Conduction band
Ef Ef
Valence band
Valence band
0V
40 CHAPTER 5. ANIMATIONS
P N
Conduction band
Conduction band
Ef Ef
Valence band
Valence band
0.1 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 41
P N
Conduction band
Conduction band
Ef Ef
Valence band
Valence band
0.1 V
42 CHAPTER 5. ANIMATIONS
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.2 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 43
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.2 V
44 CHAPTER 5. ANIMATIONS
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.3 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 45
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.3 V
46 CHAPTER 5. ANIMATIONS
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.4 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 47
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.4 V
48 CHAPTER 5. ANIMATIONS
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.5 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 49
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.5 V
50 CHAPTER 5. ANIMATIONS
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.6 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 51
P N
Conduction band
Conduction band
Ef
Ef
Valence band
Valence band
0.6 V
52 CHAPTER 5. ANIMATIONS
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 53
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
54 CHAPTER 5. ANIMATIONS
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 55
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
56 CHAPTER 5. ANIMATIONS
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 57
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
58 CHAPTER 5. ANIMATIONS
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 59
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
60 CHAPTER 5. ANIMATIONS
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
5.1. ANIMATION OF A FORWARD-BIASED PN DIODE JUNCTION 61
P N
Conduction band Conduction band
Ef
Ef
Valence band Valence band
0.7 V
62 CHAPTER 5. ANIMATIONS
Chapter 6
Questions
This learning module, along with all others in the ModEL collection, is designed to be used in an
inverted instructional environment where students independently read1 the tutorials and attempt
to answer questions on their own prior to the instructor’s interaction with them. In place of
lecture2 , the instructor engages with students in Socratic-style dialogue, probing and challenging
their understanding of the subject matter through inquiry.
Answers are not provided for questions within this chapter, and this is by design. Solved problems
may be found in the Tutorial and Derivation chapters, instead. The goal here is independence, and
this requires students to be challenged in ways where others cannot think for them. Remember
that you always have the tools of experimentation and computer simulation (e.g. SPICE) to explore
concepts!
The following lists contain ideas for Socratic-style questions and challenges. Upon inspection,
one will notice a strong theme of metacognition within these statements: they are designed to foster
a regular habit of examining one’s own thoughts as a means toward clearer thinking. As such these
sample questions are useful both for instructor-led discussions as well as for self-study.
1 Technical reading is an essential academic skill for any technical practitioner to possess for the simple reason
that the most comprehensive, accurate, and useful information to be found for developing technical competence is in
textual form. Technical careers in general are characterized by the need for continuous learning to remain current
with standards and technology, and therefore any technical practitioner who cannot read well is handicapped in
their professional development. An excellent resource for educators on improving students’ reading prowess through
intentional effort and strategy is the book textitReading For Understanding – How Reading Apprenticeship Improves
Disciplinary Learning in Secondary and College Classrooms by Ruth Schoenbach, Cynthia Greenleaf, and Lynn
Murphy.
2 Lecture is popular as a teaching method because it is easy to implement: any reasonably articulate subject matter
expert can talk to students, even with little preparation. However, it is also quite problematic. A good lecture always
makes complicated concepts seem easier than they are, which is bad for students because it instills a false sense of
confidence in their own understanding; reading and re-articulation requires more cognitive effort and serves to verify
comprehension. A culture of teaching-by-lecture fosters a debilitating dependence upon direct personal instruction,
whereas the challenges of modern life demand independent and critical thought made possible only by gathering
information and perspectives from afar. Information presented in a lecture is ephemeral, easily lost to failures of
memory and dictation; text is forever, and may be referenced at any time.
63
64 CHAPTER 6. QUESTIONS
General challenges following tutorial reading
• Summarize as much of the text as you can in one paragraph of your own words. A helpful
strategy is to explain ideas as you would for an intelligent child: as simple as you can without
compromising too much accuracy.
• Simplify a particular section of the text, for example a paragraph or even a single sentence, so
as to capture the same fundamental idea in fewer words.
• Where did the text make the most sense to you? What was it about the text’s presentation
that made it clear?
• Identify where it might be easy for someone to misunderstand the text, and explain why you
think it could be confusing.
• Identify any new concept(s) presented in the text, and explain in your own words.
• Identify any familiar concept(s) such as physical laws or principles applied or referenced in the
text.
• Devise a proof of concept experiment demonstrating an important principle, physical law, or
technical innovation represented in the text.
• Devise an experiment to disprove a plausible misconception.
• Did the text reveal any misconceptions you might have harbored? If so, describe the
misconception(s) and the reason(s) why you now know them to be incorrect.
• Describe any useful problem-solving strategies applied in the text.
• Devise a question of your own to challenge a reader’s comprehension of the text.
65
General follow-up challenges for assigned problems
• Identify where any fundamental laws or principles apply to the solution of this problem,
especially before applying any mathematical techniques.
• Devise a thought experiment to explore the characteristics of the problem scenario, applying
known laws and principles to mentally model its behavior.
• Describe in detail your own strategy for solving this problem. How did you identify and
organized the given information? Did you sketch any diagrams to help frame the problem?
• Is there more than one way to solve this problem? Which method seems best to you?
• Show the work you did in solving this problem, even if the solution is incomplete or incorrect.
• What would you say was the most challenging part of this problem, and why was it so?
• Was any important information missing from the problem which you had to research or recall?
• Was there any extraneous information presented within this problem? If so, what was it and
why did it not matter?
• Examine someone else’s solution to identify where they applied fundamental laws or principles.
• Simplify the problem from its given form and show how to solve this simpler version of it.
Examples include eliminating certain variables or conditions, altering values to simpler (usually
whole) numbers, applying a limiting case (i.e. altering a variable to some extreme or ultimate
value).
• For quantitative problems, identify the real-world meaning of all intermediate calculations:
their units of measurement, where they fit into the scenario at hand. Annotate any diagrams
or illustrations with these calculated values.
• For quantitative problems, try approaching it qualitatively instead, thinking in terms of
“increase” and “decrease” rather than definite values.
• For qualitative problems, try approaching it quantitatively instead, proposing simple numerical
values for the variables.
• Were there any assumptions you made while solving this problem? Would your solution change
if one of those assumptions were altered?
• Identify where it would be easy for someone to go astray in attempting to solve this problem.
• Formulate your own problem based on what you learned solving this one.
General follow-up challenges for experiments or projects
• In what way(s) was this experiment or project easy to complete?
• Identify some of the challenges you faced in completing this experiment or project.
66 CHAPTER 6. QUESTIONS
• Show how thorough documentation assisted in the completion of this experiment or project.
• Which fundamental laws or principles are key to this system’s function?
• Identify any way(s) in which one might obtain false or otherwise misleading measurements
from test equipment in this system.
• What will happen if (component X) fails (open/shorted/etc.)?
• What would have to occur to make this system unsafe?
6.1. CONCEPTUAL REASONING 67
6.1 Conceptual reasoning
These questions are designed to stimulate your analytic and synthetic thinking3 . In a Socratic
discussion with your instructor, the goal is for these questions to prompt an extended dialogue
where assumptions are revealed, conclusions are tested, and understanding is sharpened. Your
instructor may also pose additional questions based on those assigned, in order to further probe and
refine your conceptual understanding.
Questions that follow are presented to challenge and probe your understanding of various concepts
presented in the tutorial. These questions are intended to serve as a guide for the Socratic dialogue
between yourself and the instructor. Your instructor’s task is to ensure you have a sound grasp of
these concepts, and the questions contained in this document are merely a means to this end. Your
instructor may, at his or her discretion, alter or substitute questions for the benefit of tailoring the
discussion to each student’s needs. The only absolute requirement is that each student is challenged
and assessed at a level equal to or greater than that represented by the documented questions.
It is far more important that you convey your reasoning than it is to simply convey a correct
answer. For this reason, you should refrain from researching other information sources to answer
questions. What matters here is that you are doing the thinking. If the answer is incorrect, your
instructor will work with you to correct it through proper reasoning. A correct answer without an
adequate explanation of how you derived that answer is unacceptable, as it does not aid the learning
or assessment process.
You will note a conspicuous lack of answers given for these conceptual questions. Unlike standard
textbooks where answers to every other question are given somewhere toward the back of the book,
here in these learning modules students must rely on other means to check their work. The best way
by far is to debate the answers with fellow students and also with the instructor during the Socratic
dialogue sessions intended to be used with these learning modules. Reasoning through challenging
questions with other people is an excellent tool for developing strong reasoning skills.
Another means of checking your conceptual answers, where applicable, is to use circuit simulation
software to explore the effects of changes made to circuits. For example, if one of these conceptual
questions challenges you to predict the effects of altering some component parameter in a circuit,
you may check the validity of your work by simulating that same parameter change within software
and seeing if the results agree.
3 Analytical thinking involves the “disassembly” of an idea into its constituent parts, analogous to dissection.
Synthetic thinking involves the “assembly” of a new idea comprised of multiple concepts, analogous to construction.
Both activities are high-level cognitive skills, extremely important for effective problem-solving, necessitating frequent
challenge and regular practice to fully develop.
68 CHAPTER 6. QUESTIONS
6.1.1 Reading outline and reflections
“Reading maketh a full man; conference a ready man; and writing an exact man” – Francis Bacon
Francis Bacon’s advice is a blueprint for effective education: reading provides the learner with
knowledge, writing focuses the learner’s thoughts, and critical dialogue equips the learner to
confidently communicate and apply their learning. Independent acquisition and application of
knowledge is a powerful skill, well worth the effort to cultivate. To this end, students should
read these educational resources closely, write their own outline and reflections on the reading, and
discuss in detail their findings with classmates and instructor(s). You should be able to do all of the
following after reading any instructional text:
√
Briefly OUTLINE THE TEXT, as though you were writing a detailed Table of Contents. Feel
free to rearrange the order if it makes more sense that way. Prepare to articulate these points in
detail and to answer questions from your classmates and instructor. Outlining is a good self-test of
thorough reading because you cannot outline what you have not read or do not comprehend.
√
Demonstrate ACTIVE READING STRATEGIES, including verbalizing your impressions as
you read, simplifying long passages to convey the same ideas using fewer words, annotating text
and illustrations with your own interpretations, working through mathematical examples shown in
the text, cross-referencing passages with relevant illustrations and/or other passages, identifying
problem-solving strategies applied by the author, etc. Technical reading is a special case of problem-
solving, and so these strategies work precisely because they help solve any problem: paying attention
to your own thoughts (metacognition), eliminating unnecessary complexities, identifying what makes
sense, paying close attention to details, drawing connections between separated facts, and noting
the successful strategies of others.
√
Identify IMPORTANT THEMES, especially GENERAL LAWS and PRINCIPLES, expounded
in the text and express them in the simplest of terms as though you were teaching an intelligent
child. This emphasizes connections between related topics and develops your ability to communicate
complex ideas to anyone.
√
Form YOUR OWN QUESTIONS based on the reading, and then pose them to your instructor
and classmates for their consideration. Anticipate both correct and incorrect answers, the incorrect
answer(s) assuming one or more plausible misconceptions. This helps you view the subject from
different perspectives to grasp it more fully.
√
Devise EXPERIMENTS to test claims presented in the reading, or to disprove misconceptions.
Predict possible outcomes of these experiments, and evaluate their meanings: what result(s) would
confirm, and what would constitute disproof? Running mental simulations and evaluating results is
essential to scientific and diagnostic reasoning.
√
Specifically identify any points you found CONFUSING. The reason for doing this is to help
diagnose misconceptions and overcome barriers to learning.
6.1. CONCEPTUAL REASONING 69
6.1.2 Foundational concepts
Correct analysis and diagnosis of electric circuits begins with a proper understanding of some basic
concepts. The following is a list of some important concepts referenced in this module’s full tutorial.
Define each of them in your own words, and be prepared to illustrate each of these concepts with a
description of a practical example and/or a live demonstration.
Energy
Thermionic emission
Cathode versus Anode
Vacuum tube
Doping
N-type semiconductor
P-type semiconductor
Depletion region
Diode
Forward-biasing
Reverse-biasing
Shockley diode equation
70 CHAPTER 6. QUESTIONS
Ohm’s Law
Electrical source
Electrical load
Light-emitting diode
Photovoltaic cell
Breakdown
6.1.3 Motor-effect eliminator
Suppose we have an application where a DC generator provides power to charge a secondary-cell
battery:
Gen
The only problem with this setup is, the generator tries to act as a motor when the engine
turning it is shut off, drawing power from the battery and discharging it. How could we use a diode
to prevent this from happening?
Challenges
• Is there any other circuit arrangement with the diode that might work as well?
• Identify any relevant diode ratings we should be aware of when selecting a diode for this
application.
6.1. CONCEPTUAL REASONING 71
6.1.4 Temperature sensor
For any given amount of forward current, a diode’s voltage drop is a function of junction temperature.
Sketch a circuit exploiting this principle, and describe how you could use it to sense ambient
temperature.
Challenges
• Do you anticipate any sources of error with your design?
72 CHAPTER 6. QUESTIONS
6.1.5 Curve tracer circuit
The following schematic diagram is of a simple curve tracer circuit, used to plot the current/voltage
characteristics of different electronic components on an oscilloscope screen:
Simple curve tracer circuit
BNC connector to
’scope vertical input
Rshunt (device current)
Chassis Indicator
ground
lamp
Voltage To device BNC connector to
adjust under test ’scope horiz. input
(device voltage)
Rlimit
The way it works is by applying an AC voltage across the terminals of the device under test,
outputting two different voltage signals to the oscilloscope. One signal, driving the horizontal
axis of the oscilloscope, represents the voltage across the two terminals of the device. The other
signal, driving the vertical axis of the oscilloscope, is the voltage dropped across the shunt resistor,
representing current through the device. With the oscilloscope set for “X-Y” mode, the electron
beam traces the device’s characteristic curve.
For example, a simple resistor would generate this oscilloscope display:
Positive current
Positive applied
voltage
6.1. CONCEPTUAL REASONING 73
A resistor of greater value (more Ohms of resistance) would generate a characteristic plot with
a shallower slope, representing less current for the same amount of applied voltage:
Higher-valued resistor
Curve tracer circuits find their real value in testing semiconductor components, whose
voltage/current behaviors are nonlinear. Take for instance this characteristic curve for an ordinary
rectifying diode:
Rectifying diode curve
The trace is flat everywhere left of center where the applied voltage is negative, indicating no
diode current when it is reverse-biased. To the right of center, though, the trace bends sharply
upward, indicating exponential diode current with increasing applied voltage (forward-biased) just
as Shockley’s equation predicts.
74 CHAPTER 6. QUESTIONS
On the following grids, plot the characteristic curve for a diode that is failed shorted, and also
for one that is failed open:
Diode failed shorted Diode failed open
Challenges
• Does the amplitude (i.e. voltage) of the AC source matter to the operation of this circuit?
• Does the frequency of the AC source matter to the operation of this circuit?
6.1. CONCEPTUAL REASONING 75
6.1.6 Diode modeled as a source
When plotted on a curve tracer, the characteristic curve for a normal PN junction rectifying diode
looks something like this:
Rectifying diode curve
Label each axis (horizontal and vertical) of the curve tracer graph, then determine whether the
diode behaves more like a voltage source or more like a current source (i.e. does it try to maintain
constant voltage or does it try to maintain constant current?) when it is conducting current.
Models are very useful because they simplify circuit approximations. For example, we can analyze
this diode circuit quite easily if we substitute an electrical source in place of the diode:
Original circuit D1
V1 Rload
Should we model the diode as . . . ?
A voltage source? A current source?
Vmodel . . . or as . . . Imodel
V1 Rload V1 Rload
76 CHAPTER 6. QUESTIONS
Challenges
• In what way(s) is a diode not a true electrical source?
• How might this information be useful when applying Thévenin’s or Norton’s theorem to a
circuit?
6.1.7 Diode frequency limit
What diode performance parameter(s) establish the limit for maximum frequency of AC which it
may rectify? If you were to examine a diode datasheet, what parameter (or parameters) would be
the most important in answering this question?
6.2. QUANTITATIVE REASONING 77
6.2 Quantitative reasoning
These questions are designed to stimulate your computational thinking. In a Socratic discussion with
your instructor, the goal is for these questions to reveal your mathematical approach(es) to problem-
solving so that good technique and sound reasoning may be reinforced. Your instructor may also pose
additional questions based on those assigned, in order to observe your problem-solving firsthand.
Mental arithmetic and estimations are strongly encouraged for all calculations, because without
these abilities you will be unable to readily detect errors caused by calculator misuse (e.g. keystroke
errors).
You will note a conspicuous lack of answers given for these quantitative questions. Unlike
standard textbooks where answers to every other question are given somewhere toward the back
of the book, here in these learning modules students must rely on other means to check their work.
My advice is to use circuit simulation software such as SPICE to check the correctness of quantitative
answers. Refer to those learning modules within this collection focusing on SPICE to see worked
examples which you may use directly as practice problems for your own study, and/or as templates
you may modify to run your own analyses and generate your own practice problems.
Completely worked example problems found in the Tutorial may also serve as “test cases4 ” for
gaining proficiency in the use of circuit simulation software, and then once that proficiency is gained
you will never need to rely5 on an answer key!
4 In other words, set up the circuit simulation software to analyze the same circuit examples found in the Tutorial.
If the simulated results match the answers shown in the Tutorial, it confirms the simulation has properly run. If
the simulated results disagree with the Tutorial’s answers, something has been set up incorrectly in the simulation
software. Using every Tutorial as practice in this way will quickly develop proficiency in the use of circuit simulation
software.
5 This approach is perfectly in keeping with the instructional philosophy of these learning modules: teaching students
to be self-sufficient thinkers. Answer keys can be useful, but it is even more useful to your long-term success to have
a set of tools on hand for checking your own work, because once you have left school and are on your own, there will
no longer be “answer keys” available for the problems you will have to solve.
78 CHAPTER 6. QUESTIONS
6.2.1 Miscellaneous physical constants
Note: constants shown in bold type are exact, not approximations. Values inside of parentheses show
one standard deviation (σ) of uncertainty in the final digits: for example, Avogadro’s number given
as 6.02214179(30) × 1023 means the center value (6.02214179×1023 ) plus or minus 0.00000030×1023 .
Avogadro’s number (NA ) = 6.02214179(30) × 1023 per mole (mol−1 )
Boltzmann’s constant (k) = 1.3806504(24) × 10−23 Joules per Kelvin (J/K)
Electronic charge (e) = 1.602176487(40) × 10−19 Coulomb (C)
Faraday constant (F ) = 9.64853399(24) × 104 Coulombs per mole (C/mol)
Magnetic permeability of free space (µ0 ) = 1.25663706212(19) × 10−6 Henrys per meter (H/m)
Electric permittivity of free space (ǫ0 ) = 8.8541878128(13) × 10−12 Farads per meter (F/m)
Characteristic impedance of free space (Z0 ) = 376.730313668(57) Ohms (Ω)
Gravitational constant (G) = 6.67428(67) × 10−11 cubic meters per kilogram-seconds squared
(m3 /kg-s2 )
Molar gas constant (R) = 8.314472(15) Joules per mole-Kelvin (J/mol-K) = 0.08205746(14) liters-
atmospheres per mole-Kelvin
Planck constant (h) = 6.62606896(33) × 10−34 joule-seconds (J-s)
Stefan-Boltzmann constant (σ) = 5.670400(40) × 10−8 Watts per square meter-Kelvin4 (W/m2 ·K4 )
Speed of light in a vacuum (c) = 299792458 meters per second (m/s) = 186282.4 miles per
second (mi/s)
Note: All constants taken from NIST data “Fundamental Physical Constants – Extensive Listing”,
from http://physics.nist.gov/constants, National Institute of Standards and Technology
(NIST), 2006; with the exception of the permeability of free space which was taken from NIST’s
2018 CODATA recommended values database.
6.2. QUANTITATIVE REASONING 79
6.2.2 Introduction to spreadsheets
A powerful computational tool you are encouraged to use in your work is a spreadsheet. Available
on most personal computers (e.g. Microsoft Excel), spreadsheet software performs numerical
calculations based on number values and formulae entered into cells of a grid. This grid is
typically arranged as lettered columns and numbered rows, with each cell of the grid identified
by its column/row coordinates (e.g. cell B3, cell A8). Each cell may contain a string of text, a
number value, or a mathematical formula. The spreadsheet automatically updates the results of all
mathematical formulae whenever the entered number values are changed. This means it is possible
to set up a spreadsheet to perform a series of calculations on entered data, and those calculations
will be re-done by the computer any time the data points are edited in any way.
For example, the following spreadsheet calculates average speed based on entered values of
distance traveled and time elapsed:
A B C D
1 Distance traveled 46.9 Kilometers
2 Time elapsed 1.18 Hours
3 Average speed = B1 / B2 km/h
4
5
Text labels contained in cells A1 through A3 and cells C1 through C3 exist solely for readability
and are not involved in any calculations. Cell B1 contains a sample distance value while cell B2
contains a sample time value. The formula for computing speed is contained in cell B3. Note how
this formula begins with an “equals” symbol (=), references the values for distance and speed by
lettered column and numbered row coordinates (B1 and B2), and uses a forward slash symbol for
division (/). The coordinates B1 and B2 function as variables 6 would in an algebraic formula.
When this spreadsheet is executed, the numerical value 39.74576 will appear in cell B3 rather
than the formula = B1 / B2, because 39.74576 is the computed speed value given 46.9 kilometers
traveled over a period of 1.18 hours. If a different numerical value for distance is entered into cell
B1 or a different value for time is entered into cell B2, cell B3’s value will automatically update. All
you need to do is set up the given values and any formulae into the spreadsheet, and the computer
will do all the calculations for you.
Cell B3 may be referenced by other formulae in the spreadsheet if desired, since it is a variable
just like the given values contained in B1 and B2. This means it is possible to set up an entire chain
of calculations, one dependent on the result of another, in order to arrive at a final value. The
arrangement of the given data and formulae need not follow any pattern on the grid, which means
you may place them anywhere.
6 Spreadsheets may also provide means to attach text labels to cells for use as variable names (Microsoft Excel
simply calls these labels “names”), but for simple spreadsheets such as those shown here it’s usually easier just to use
the standard coordinate naming for each cell.
80 CHAPTER 6. QUESTIONS
Common7 arithmetic operations available for your use in a spreadsheet include the following:
• Addition (+)
• Subtraction (-)
• Multiplication (*)
• Division (/)
• Powers (^)
• Square roots (sqrt())
• Logarithms (ln() , log10())
Parentheses may be used to ensure8 proper order of operations within a complex formula.
Consider this example of a spreadsheet implementing the quadratic formula, used to solve for roots
of a polynomial expression in the form of ax2 + bx + c:
√
−b ± b2 − 4ac
x=
2a
A B
1 x_1 = (-B4 + sqrt((B4^2) - (4*B3*B5))) / (2*B3)
2 x_2 = (-B4 - sqrt((B4^2) - (4*B3*B5))) / (2*B3)
3 a = 9
4 b = 5
5 c = -2
This example is configured to compute roots9 of the polynomial 9x2 + 5x − 2 because the values
of 9, 5, and −2 have been inserted into cells B3, B4, and B5, respectively. Once this spreadsheet has
been built, though, it may be used to calculate the roots of any second-degree polynomial expression
simply by entering the new a, b, and c coefficients into cells B3 through B5. The numerical values
appearing in cells B1 and B2 will be automatically updated by the computer immediately following
any changes made to the coefficients.
7 Modern spreadsheet software offers a bewildering array of mathematical functions you may use in your
computations. I recommend you consult the documentation for your particular spreadsheet for information on
operations other than those listed here.
8 Spreadsheet programs, like text-based programming languages, are designed to follow standard order of operations
by default. However, my personal preference is to use parentheses even where strictly unnecessary just to make it
clear to any other person viewing the formula what the intended order of operations is.
9 Reviewing some algebra here, a root is a value for x that yields an overall value of zero for the polynomial. For
this polynomial (9x2 + 5x − 2) the two roots happen to be x = 0.269381 and x = −0.82494, with these values displayed
in cells B1 and B2, respectively upon execution of the spreadsheet.
6.2. QUANTITATIVE REASONING 81
Alternatively, one could break up the long quadratic formula into smaller pieces like this:
p
y = b2 − 4ac z = 2a
−b ± y
x=
z
A B C
1 x_1 = (-B4 + C1) / C2 = sqrt((B4^2) - (4*B3*B5))
2 x_2 = (-B4 - C1) / C2 = 2*B3
3 a = 9
4 b = 5
5 c = -2
Note how the square-root term (y) is calculated in cell C1, and the denominator term (z) in cell
C2. This makes the two final formulae (in cells B1 and B2) simpler to interpret. The positioning of
all these cells on the grid is completely arbitrary10 – all that matters is that they properly reference
each other in the formulae.
Spreadsheets are particularly useful for situations where the same set of calculations representing
a circuit or other system must be repeated for different initial conditions. The power of a spreadsheet
is that it automates what would otherwise be a tedious set of calculations. One specific application
of this is to simulate the effects of various components within a circuit failing with abnormal values
(e.g. a shorted resistor simulated by making its value nearly zero; an open resistor simulated by
making its value extremely large). Another application is analyzing the behavior of a circuit design
given new components that are out of specification, and/or aging components experiencing drift
over time.
10 My personal preference is to locate all the “given” data in the upper-left cells of the spreadsheet grid (each data
point flanked by a sensible name in the cell to the left and units of measurement in the cell to the right as illustrated
in the first distance/time spreadsheet example), sometimes coloring them in order to clearly distinguish which cells
contain entered data versus which cells contain computed results from formulae. I like to place all formulae in cells
below the given data, and try to arrange them in logical order so that anyone examining my spreadsheet will be able
to figure out how I constructed a solution. This is a general principle I believe all computer programmers should
follow: document and arrange your code to make it easy for other people to learn from it.
82 CHAPTER 6. QUESTIONS
6.2.3 Voltages and currents in simple diode circuits
Complete the following table of values for this diode circuit, assuming the forward voltage drop
values shown:
470 Ω R1 D1 Total
V 12 V
R1
I
D1 12 V
R 470 Ω
P
Vf = 0.65 V
920 Ω R1 D1 Total
V 16 V
R1
I
D1 16 V
R 920 Ω
P
Vf = 0.72 V
Challenges
• How will voltages and currents be affected by the diode failing open?
• How will voltages and currents be affected by the diode failing shorted?
• How will voltages and currents be affected by the resistor failing open?
• How will voltages and currents be affected by the resistor failing shorted?
• How will voltages and currents be affected by the source polarity being reversed?
6.2. QUANTITATIVE REASONING 83
6.2.4 LED resistor sizing
Calculate the proper resistor value to limit LED voltage and current to 1.65 Volts and 22
milliAmperes, respectively, given the following source voltage ratings:
R
LED + V
− S
• VS = 15 Volts ; R =
• VS = 24 Volts ; R =
• VS = 48 Volts ; R =
Challenges
• A very common mistake made by beginning students is to calculate resistor values of 681.8 Ω,
1090.9 Ω, and 2181.8 Ω, respectively. Identify the error implicit in these results.
• Calculate the amount of power dissipated by the resistor for each of these source voltages.
84 CHAPTER 6. QUESTIONS
6.3 Diagnostic reasoning
These questions are designed to stimulate your deductive and inductive thinking, where you must
apply general principles to specific scenarios (deductive) and also derive conclusions about the failed
circuit from specific details (inductive). In a Socratic discussion with your instructor, the goal is for
these questions to reinforce your recall and use of general circuit principles and also challenge your
ability to integrate multiple symptoms into a sensible explanation of what’s wrong in a circuit. Your
instructor may also pose additional questions based on those assigned, in order to further challenge
and sharpen your diagnostic abilities.
As always, your goal is to fully explain your analysis of each problem. Simply obtaining a
correct answer is not good enough – you must also demonstrate sound reasoning in order to
successfully complete the assignment. Your instructor’s responsibility is to probe and challenge
your understanding of the relevant principles and analytical processes in order to ensure you have a
strong foundation upon which to build further understanding.
You will note a conspicuous lack of answers given for these diagnostic questions. Unlike standard
textbooks where answers to every other question are given somewhere toward the back of the book,
here in these learning modules students must rely on other means to check their work. The best way
by far is to debate the answers with fellow students and also with the instructor during the Socratic
dialogue sessions intended to be used with these learning modules. Reasoning through challenging
questions with other people is an excellent tool for developing strong reasoning skills.
Another means of checking your diagnostic answers, where applicable, is to use circuit simulation
software to explore the effects of faults placed in circuits. For example, if one of these diagnostic
questions requires that you predict the effect of an open or a short in a circuit, you may check the
validity of your work by simulating that same fault (substituting a very high resistance in place of
that component for an open, and substituting a very low resistance for a short) within software and
seeing if the results agree.
6.3. DIAGNOSTIC REASONING 85
6.3.1 Faults in a diode-resistor network
Predict how all component voltages and currents in this circuit will be affected as a result of the
following faults. Consider each fault independently (i.e. one at a time, no coincidental faults):
D1
R1
V1
R2
• Diode D1 fails open:
• Diode D1 fails shorted:
• Resistor R1 fails open:
• Resistor R1 fails shorted:
• Resistor R2 fails open:
• Resistor R2 fails shorted:
Challenges
• What will happen if the voltage source polarity becomes reversed?
86 CHAPTER 6. QUESTIONS
6.3.2 Diode-testing circuit
Explain how the following diode-testing circuit is supposed to function for the following scenarios:
LED1
R1 LED2 To AC line
power source
Anode Cathode
Diode to be tested
• Good diode
• Shorted diode
• Open diode
• Backwards diode
Challenges
• Explain how to properly size the resistor in this circuit.
Appendix A
Problem-Solving Strategies
The ability to solve complex problems is arguably one of the most valuable skills one can possess,
and this skill is particularly important in any science-based discipline.
• Study principles, not procedures. Don’t be satisfied with merely knowing how to compute
solutions – learn why those solutions work.
• Identify what it is you need to solve, identify all relevant data, identify all units of measurement,
identify any general principles or formulae linking the given information to the solution, and
then identify any “missing pieces” to a solution. Annotate all diagrams with this data.
• Sketch a diagram to help visualize the problem. When building a real system, always devise
a plan for that system and analyze its function before constructing it.
• Follow the units of measurement and meaning of every calculation. If you are ever performing
mathematical calculations as part of a problem-solving procedure, and you find yourself unable
to apply each and every intermediate result to some aspect of the problem, it means you
don’t understand what you are doing. Properly done, every mathematical result should have
practical meaning for the problem, and not just be an abstract number. You should be able to
identify the proper units of measurement for each and every calculated result, and show where
that result fits into the problem.
• Perform “thought experiments” to explore the effects of different conditions for theoretical
problems. When troubleshooting real systems, perform diagnostic tests rather than visually
inspecting for faults, the best diagnostic test being the one giving you the most information
about the nature and/or location of the fault with the fewest steps.
• Simplify the problem until the solution becomes obvious, and then use that obvious case as a
model to follow in solving the more complex version of the problem.
• Check for exceptions to see if your solution is incorrect or incomplete. A good solution will
work for all known conditions and criteria. A good example of this is the process of testing
scientific hypotheses: the task of a scientist is not to find support for a new idea, but rather
to challenge that new idea to see if it holds up under a battery of tests. The philosophical
87
88 APPENDIX A. PROBLEM-SOLVING STRATEGIES
principle of reductio ad absurdum (i.e. disproving a general idea by finding a specific case
where it fails) is useful here.
• Work “backward” from a hypothetical solution to a new set of given conditions.
• Add quantities to problems that are qualitative in nature, because sometimes a little math
helps illuminate the scenario.
• Sketch graphs illustrating how variables relate to each other. These may be quantitative (i.e.
with realistic number values) or qualitative (i.e. simply showing increases and decreases).
• Treat quantitative problems as qualitative in order to discern the relative magnitudes and/or
directions of change of the relevant variables. For example, try determining what happens if a
certain variable were to increase or decrease before attempting to precisely calculate quantities:
how will each of the dependent variables respond, by increasing, decreasing, or remaining the
same as before?
• Consider limiting cases. This works especially well for qualitative problems where you need to
determine which direction a variable will change. Take the given condition and magnify that
condition to an extreme degree as a way of simplifying the direction of the system’s response.
• Check your work. This means regularly testing your conclusions to see if they make sense.
This does not mean repeating the same steps originally used to obtain the conclusion(s), but
rather to use some other means to check validity. Simply repeating procedures often leads to
repeating the same errors if any were made, which is why alternative paths are better.
Appendix B
Instructional philosophy
“The unexamined circuit is not worth energizing” – Socrates (if he had taught electricity)
These learning modules, although useful for self-study, were designed to be used in a formal
learning environment where a subject-matter expert challenges students to digest the content and
exercise their critical thinking abilities in the answering of questions and in the construction and
testing of working circuits.
The following principles inform the instructional and assessment philosophies embodied in these
learning modules:
• The first goal of education is to enhance clear and independent thought, in order that
every student reach their fullest potential in a highly complex and inter-dependent world.
Robust reasoning is always more important than particulars of any subject matter, because
its application is universal.
• Literacy is fundamental to independent learning and thought because text continues to be the
most efficient way to communicate complex ideas over space and time. Those who cannot read
with ease are limited in their ability to acquire knowledge and perspective.
• Articulate communication is fundamental to work that is complex and interdisciplinary.
• Faulty assumptions and poor reasoning are best corrected through challenge, not presentation.
The rhetorical technique of reductio ad absurdum (disproving an assertion by exposing an
absurdity) works well to discipline student’s minds, not only to correct the problem at hand
but also to learn how to detect and correct future errors.
• Important principles should be repeatedly explored and widely applied throughout a course
of study, not only to reinforce their importance and help ensure their mastery, but also to
showcase the interconnectedness and utility of knowledge.
89
90 APPENDIX B. INSTRUCTIONAL PHILOSOPHY
These learning modules were expressly designed to be used in an “inverted” teaching
environment1 where students first read the introductory and tutorial chapters on their own, then
individually attempt to answer the questions and construct working circuits according to the
experiment and project guidelines. The instructor never lectures, but instead meets regularly
with each individual student to review their progress, answer questions, identify misconceptions,
and challenge the student to new depths of understanding through further questioning. Regular
meetings between instructor and student should resemble a Socratic2 dialogue, where questions
serve as scalpels to dissect topics and expose assumptions. The student passes each module only
after consistently demonstrating their ability to logically analyze and correctly apply all major
concepts in each question or project/experiment. The instructor must be vigilant in probing each
student’s understanding to ensure they are truly reasoning and not just memorizing. This is why
“Challenge” points appear throughout, as prompts for students to think deeper about topics and as
starting points for instructor queries. Sometimes these challenge points require additional knowledge
that hasn’t been covered in the series to answer in full. This is okay, as the major purpose of the
Challenges is to stimulate analysis and synthesis on the part of each student.
The instructor must possess enough mastery of the subject matter and awareness of students’
reasoning to generate their own follow-up questions to practically any student response. Even
completely correct answers given by the student should be challenged by the instructor for the
purpose of having students practice articulating their thoughts and defending their reasoning.
Conceptual errors committed by the student should be exposed and corrected not by direct
instruction, but rather by reducing the errors to an absurdity3 through well-chosen questions and
thought experiments posed by the instructor. Becoming proficient at this style of instruction requires
time and dedication, but the positive effects on critical thinking for both student and instructor are
spectacular.
An inspection of these learning modules reveals certain unique characteristics. One of these is
a bias toward thorough explanations in the tutorial chapters. Without a live instructor to explain
concepts and applications to students, the text itself must fulfill this role. This philosophy results in
lengthier explanations than what you might typically find in a textbook, each step of the reasoning
process fully explained, including footnotes addressing common questions and concerns students
raise while learning these concepts. Each tutorial seeks to not only explain each major concept
in sufficient detail, but also to explain the logic of each concept and how each may be developed
1 In a traditional teaching environment, students first encounter new information via lecture from an expert, and
then independently apply that information via homework. In an “inverted” course of study, students first encounter
new information via homework, and then independently apply that information under the scrutiny of an expert. The
expert’s role in lecture is to simply explain, but the expert’s role in an inverted session is to challenge, critique, and
if necessary explain where gaps in understanding still exist.
2 Socrates is a figure in ancient Greek philosophy famous for his unflinching style of questioning. Although he
authored no texts, he appears as a character in Plato’s many writings. The essence of Socratic philosophy is to
leave no question unexamined and no point of view unchallenged. While purists may argue a topic such as electric
circuits is too narrow for a true Socratic-style dialogue, I would argue that the essential thought processes involved
with scientific reasoning on any topic are not far removed from the Socratic ideal, and that students of electricity and
electronics would do very well to challenge assumptions, pose thought experiments, identify fallacies, and otherwise
employ the arsenal of critical thinking skills modeled by Socrates.
3 This rhetorical technique is known by the Latin phrase reductio ad absurdum. The concept is to expose errors by
counter-example, since only one solid counter-example is necessary to disprove a universal claim. As an example of
this, consider the common misconception among beginning students of electricity that voltage cannot exist without
current. One way to apply reductio ad absurdum to this statement is to ask how much current passes through a
fully-charged battery connected to nothing (i.e. a clear example of voltage existing without current).
91
from “first principles”. Again, this reflects the goal of developing clear and independent thought in
students’ minds, by showing how clear and logical thought was used to forge each concept. Students
benefit from witnessing a model of clear thinking in action, and these tutorials strive to be just that.
Another characteristic of these learning modules is a lack of step-by-step instructions in the
Project and Experiment chapters. Unlike many modern workbooks and laboratory guides where
step-by-step instructions are prescribed for each experiment, these modules take the approach that
students must learn to closely read the tutorials and apply their own reasoning to identify the
appropriate experimental steps. Sometimes these steps are plainly declared in the text, just not as
a set of enumerated points. At other times certain steps are implied, an example being assumed
competence in test equipment use where the student should not need to be told again how to use
their multimeter because that was thoroughly explained in previous lessons. In some circumstances
no steps are given at all, leaving the entire procedure up to the student.
This lack of prescription is not a flaw, but rather a feature. Close reading and clear thinking are
foundational principles of this learning series, and in keeping with this philosophy all activities are
designed to require those behaviors. Some students may find the lack of prescription frustrating,
because it demands more from them than what their previous educational experiences required. This
frustration should be interpreted as an unfamiliarity with autonomous thinking, a problem which
must be corrected if the student is ever to become a self-directed learner and effective problem-solver.
Ultimately, the need for students to read closely and think clearly is more important both in the
near-term and far-term than any specific facet of the subject matter at hand. If a student takes
longer than expected to complete a module because they are forced to outline, digest, and reason
on their own, so be it. The future gains enjoyed by developing this mental discipline will be well
worth the additional effort and delay.
Another feature of these learning modules is that they do not treat topics in isolation. Rather,
important concepts are introduced early in the series, and appear repeatedly as stepping-stones
toward other concepts in subsequent modules. This helps to avoid the “compartmentalization”
of knowledge, demonstrating the inter-connectedness of concepts and simultaneously reinforcing
them. Each module is fairly complete in itself, reserving the beginning of its tutorial to a review of
foundational concepts.
This methodology of assigning text-based modules to students for digestion and then using
Socratic dialogue to assess progress and hone students’ thinking was developed over a period of
several years by the author with his Electronics and Instrumentation students at the two-year college
level. While decidedly unconventional and sometimes even unsettling for students accustomed to
a more passive lecture environment, this instructional philosophy has proven its ability to convey
conceptual mastery, foster careful analysis, and enhance employability so much better than lecture
that the author refuses to ever teach by lecture again.
Problems which often go undiagnosed in a lecture environment are laid bare in this “inverted”
format where students must articulate and logically defend their reasoning. This, too, may be
unsettling for students accustomed to lecture sessions where the instructor cannot tell for sure who
comprehends and who does not, and this vulnerability necessitates sensitivity on the part of the
“inverted” session instructor in order that students never feel discouraged by having their errors
exposed. Everyone makes mistakes from time to time, and learning is a lifelong process! Part of
the instructor’s job is to build a culture of learning among the students where errors are not seen as
shameful, but rather as opportunities for progress.
92 APPENDIX B. INSTRUCTIONAL PHILOSOPHY
To this end, instructors managing courses based on these modules should adhere to the following
principles:
• Student questions are always welcome and demand thorough, honest answers. The only type
of question an instructor should refuse to answer is one the student should be able to easily
answer on their own. Remember, the fundamental goal of education is for each student to learn
to think clearly and independently. This requires hard work on the part of the student, which
no instructor should ever circumvent. Anything done to bypass the student’s responsibility to
do that hard work ultimately limits that student’s potential and thereby does real harm.
• It is not only permissible, but encouraged, to answer a student’s question by asking questions
in return, these follow-up questions designed to guide the student to reach a correct answer
through their own reasoning.
• All student answers demand to be challenged by the instructor and/or by other students.
This includes both correct and incorrect answers – the goal is to practice the articulation and
defense of one’s own reasoning.
• No reading assignment is deemed complete unless and until the student demonstrates their
ability to accurately summarize the major points in their own terms. Recitation of the original
text is unacceptable. This is why every module contains an “Outline and reflections” question
as well as a “Foundational concepts” question in the Conceptual reasoning section, to prompt
reflective reading.
• No assigned question is deemed answered unless and until the student demonstrates their
ability to consistently and correctly apply the concepts to variations of that question. This is
why module questions typically contain multiple “Challenges” suggesting different applications
of the concept(s) as well as variations on the same theme(s). Instructors are encouraged to
devise as many of their own “Challenges” as they are able, in order to have a multitude of
ways ready to probe students’ understanding.
• No assigned experiment or project is deemed complete unless and until the student
demonstrates the task in action. If this cannot be done “live” before the instructor, video-
recordings showing the demonstration are acceptable. All relevant safety precautions must be
followed, all test equipment must be used correctly, and the student must be able to properly
explain all results. The student must also successfully answer all Challenges presented by the
instructor for that experiment or project.
93
Students learning from these modules would do well to abide by the following principles:
• No text should be considered fully and adequately read unless and until you can express every
idea in your own words, using your own examples.
• You should always articulate your thoughts as you read the text, noting points of agreement,
confusion, and epiphanies. Feel free to print the text on paper and then write your notes in
the margins. Alternatively, keep a journal for your own reflections as you read. This is truly
a helpful tool when digesting complicated concepts.
• Never take the easy path of highlighting or underlining important text. Instead, summarize
and/or comment on the text using your own words. This actively engages your mind, allowing
you to more clearly perceive points of confusion or misunderstanding on your own.
• A very helpful strategy when learning new concepts is to place yourself in the role of a teacher,
if only as a mental exercise. Either explain what you have recently learned to someone else,
or at least imagine yourself explaining what you have learned to someone else. The simple act
of having to articulate new knowledge and skill forces you to take on a different perspective,
and will help reveal weaknesses in your understanding.
• Perform each and every mathematical calculation and thought experiment shown in the text
on your own, referring back to the text to see that your results agree. This may seem trivial
and unnecessary, but it is critically important to ensuring you actually understand what is
presented, especially when the concepts at hand are complicated and easy to misunderstand.
Apply this same strategy to become proficient in the use of circuit simulation software, checking
to see if your simulated results agree with the results shown in the text.
• Above all, recognize that learning is hard work, and that a certain level of frustration is
unavoidable. There are times when you will struggle to grasp some of these concepts, and that
struggle is a natural thing. Take heart that it will yield with persistent and varied4 effort, and
never give up!
Students interested in using these modules for self-study will also find them beneficial, although
the onus of responsibility for thoroughly reading and answering questions will of course lie with
that individual alone. If a qualified instructor is not available to challenge students, a workable
alternative is for students to form study groups where they challenge5 one another.
To high standards of education,
Tony R. Kuphaldt
4 As the old saying goes, “Insanity is trying the same thing over and over again, expecting different results.” If
you find yourself stumped by something in the text, you should attempt a different approach. Alter the thought
experiment, change the mathematical parameters, do whatever you can to see the problem in a slightly different light,
and then the solution will often present itself more readily.
5 Avoid the temptation to simply share answers with study partners, as this is really counter-productive to learning.
Always bear in mind that the answer to any question is far less important in the long run than the method(s) used to
obtain that answer. The goal of education is to empower one’s life through the improvement of clear and independent
thought, literacy, expression, and various practical skills.
94 APPENDIX B. INSTRUCTIONAL PHILOSOPHY
Appendix C
Tools used
I am indebted to the developers of many open-source software applications in the creation of these
learning modules. The following is a list of these applications with some commentary on each.
You will notice a theme common to many of these applications: a bias toward code. Although
I am by no means an expert programmer in any computer language, I understand and appreciate
the flexibility offered by code-based applications where the user (you) enters commands into a plain
ASCII text file, which the software then reads and processes to create the final output. Code-based
computer applications are by their very nature extensible, while WYSIWYG (What You See Is What
You Get) applications are generally limited to whatever user interface the developer makes for you.
The GNU/Linux computer operating system
There is so much to be said about Linus Torvalds’ Linux and Richard Stallman’s GNU
project. First, to credit just these two individuals is to fail to do justice to the mob of
passionate volunteers who contributed to make this amazing software a reality. I first
learned of Linux back in 1996, and have been using this operating system on my personal
computers almost exclusively since then. It is free, it is completely configurable, and it
permits the continued use of highly efficient Unix applications and scripting languages
(e.g. shell scripts, Makefiles, sed, awk) developed over many decades. Linux not only
provided me with a powerful computing platform, but its open design served to inspire
my life’s work of creating open-source educational resources.
Bram Moolenaar’s Vim text editor
Writing code for any code-based computer application requires a text editor, which may
be thought of as a word processor strictly limited to outputting plain-ASCII text files.
Many good text editors exist, and one’s choice of text editor seems to be a deeply personal
matter within the programming world. I prefer Vim because it operates very similarly to
vi which is ubiquitous on Unix/Linux operating systems, and because it may be entirely
operated via keyboard (i.e. no mouse required) which makes it fast to use.
95
96 APPENDIX C. TOOLS USED
Donald Knuth’s TEX typesetting system
Developed in the late 1970’s and early 1980’s by computer scientist extraordinaire Donald
Knuth to typeset his multi-volume magnum opus The Art of Computer Programming,
this software allows the production of formatted text for screen-viewing or paper printing,
all by writing plain-text code to describe how the formatted text is supposed to appear.
TEX is not just a markup language for documents, but it is also a Turing-complete
programming language in and of itself, allowing useful algorithms to be created to control
the production of documents. Simply put, TEX is a programmer’s approach to word
processing. Since TEX is controlled by code written in a plain-text file, this means
anyone may read that plain-text file to see exactly how the document was created. This
openness afforded by the code-based nature of TEX makes it relatively easy to learn how
other people have created their own TEX documents. By contrast, examining a beautiful
document created in a conventional WYSIWYG word processor such as Microsoft Word
suggests nothing to the reader about how that document was created, or what the user
might do to create something similar. As Mr. Knuth himself once quipped, conventional
word processing applications should be called WYSIAYG (What You See Is All You
Get).
Leslie Lamport’s LATEX extensions to TEX
Like all true programming languages, TEX is inherently extensible. So, years after the
release of TEX to the public, Leslie Lamport decided to create a massive extension
allowing easier compilation of book-length documents. The result was LATEX, which
is the markup language used to create all ModEL module documents. You could say
that TEX is to LATEX as C is to C++. This means it is permissible to use any and all TEX
commands within LATEX source code, and it all still works. Some of the features offered
by LATEX that would be challenging to implement in TEX include automatic index and
table-of-content creation.
Tim Edwards’ Xcircuit drafting program
This wonderful program is what I use to create all the schematic diagrams and
illustrations (but not photographic images or mathematical plots) throughout the ModEL
project. It natively outputs PostScript format which is a true vector graphic format (this
is why the images do not pixellate when you zoom in for a closer view), and it is so simple
to use that I have never had to read the manual! Object libraries are easy to create for
Xcircuit, being plain-text files using PostScript programming conventions. Over the
years I have collected a large set of object libraries useful for drawing electrical and
electronic schematics, pictorial diagrams, and other technical illustrations.
97
Gimp graphic image manipulation program
Essentially an open-source clone of Adobe’s PhotoShop, I use Gimp to resize, crop, and
convert file formats for all of the photographic images appearing in the ModEL modules.
Although Gimp does offer its own scripting language (called Script-Fu), I have never
had occasion to use it. Thus, my utilization of Gimp to merely crop, resize, and convert
graphic images is akin to using a sword to slice bread.
SPICE circuit simulation program
SPICE is to circuit analysis as TEX is to document creation: it is a form of markup
language designed to describe a certain object to be processed in plain-ASCII text.
When the plain-text “source file” is compiled by the software, it outputs the final result.
More modern circuit analysis tools certainly exist, but I prefer SPICE for the following
reasons: it is free, it is fast, it is reliable, and it is a fantastic tool for teaching students of
electricity and electronics how to write simple code. I happen to use rather old versions of
SPICE, version 2g6 being my “go to” application when I only require text-based output.
NGSPICE (version 26), which is based on Berkeley SPICE version 3f5, is used when I
require graphical output for such things as time-domain waveforms and Bode plots. In
all SPICE example netlists I strive to use coding conventions compatible with all SPICE
versions.
Andrew D. Hwang’s ePiX mathematical visualization programming library
This amazing project is a C++ library you may link to any C/C++ code for the purpose
of generating PostScript graphic images of mathematical functions. As a completely
free and open-source project, it does all the plotting I would otherwise use a Computer
Algebra System (CAS) such as Mathematica or Maple to do. It should be said that
ePiX is not a Computer Algebra System like Mathematica or Maple, but merely a
mathematical visualization tool. In other words, it won’t determine integrals for you
(you’ll have to implement that in your own C/C++ code!), but it can graph the results, and
it does so beautifully. What I really admire about ePiX is that it is a C++ programming
library, which means it builds on the existing power and toolset available with that
programming language. Mr. Hwang could have probably developed his own stand-alone
application for mathematical plotting, but by creating a C++ library to do the same thing
he accomplished something much greater.
98 APPENDIX C. TOOLS USED
gnuplot mathematical visualization software
Another open-source tool for mathematical visualization is gnuplot. Interestingly, this
tool is not part of Richard Stallman’s GNU project, its name being a coincidence. For
this reason the authors prefer “gnu” not be capitalized at all to avoid confusion. This is
a much “lighter-weight” alternative to a spreadsheet for plotting tabular data, and the
fact that it easily outputs directly to an X11 console or a file in a number of different
graphical formats (including PostScript) is very helpful. I typically set my gnuplot
output format to default (X11 on my Linux PC) for quick viewing while I’m developing
a visualization, then switch to PostScript file export once the visual is ready to include in
the document(s) I’m writing. As with my use of Gimp to do rudimentary image editing,
my use of gnuplot only scratches the surface of its capabilities, but the important points
are that it’s free and that it works well.
Python programming language
Both Python and C++ find extensive use in these modules as instructional aids and
exercises, but I’m listing Python here as a tool for myself because I use it almost daily
as a calculator. If you open a Python interpreter console and type from math import
* you can type mathematical expressions and have it return results just as you would
on a hand calculator. Complex-number (i.e. phasor ) arithmetic is similarly supported
if you include the complex-math library (from cmath import *). Examples of this are
shown in the Programming References chapter (if included) in each module. Of course,
being a fully-featured programming language, Python also supports conditionals, loops,
and other structures useful for calculation of quantities. Also, running in a console
environment where all entries and returned values show as text in a chronologically-
ordered list makes it easy to copy-and-paste those calculations to document exactly how
they were performed.
Appendix D
Creative Commons License
Creative Commons Attribution 4.0 International Public License
By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms
and conditions of this Creative Commons Attribution 4.0 International Public License (“Public
License”). To the extent this Public License may be interpreted as a contract, You are granted the
Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor
grants You such rights in consideration of benefits the Licensor receives from making the Licensed
Material available under these terms and conditions.
Section 1 – Definitions.
a. Adapted Material means material subject to Copyright and Similar Rights that is derived
from or based upon the Licensed Material and in which the Licensed Material is translated, altered,
arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright
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Appendix E
References
“1N4001 thru 1N4007 General Purpose Plastic Rectifier”, datasheet document number 88503,
Vishay, 23 February 2011.
Pierce, George W., US Patent 879,117, “Rectifier and Detector”, application 5 April 1907, patent
granted 11 February 1908.
Stroustrup, Bjarne, The C++ Programming Language, fourth edition, Addison-Wesley, Upper
Saddle River, NJ, 2013.
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108 APPENDIX E. REFERENCES
Appendix F
Version history
This is a list showing all significant additions, corrections, and other edits made to this learning
module. Each entry is referenced by calendar date in reverse chronological order (newest version
first), which appears on the front cover of every learning module for easy reference. Any contributors
to this open-source document are listed here as well.
28 November 2022 – placed questions at the top of the itemized list in the Introduction chapter
prompting students to devise experiments related to the tutorial content.
27 October 2022 – added some questions to the Introduction chapter and fixed some minor
typographical errors (one of them identified by Galen Bennett). Also made some minor additions
to the Tutorial including edits to image 1888.
1 November 2021 – fixed cosmetic errors in image 4760.
9 May 2021 – commented out or deleted empty chapters.
20 April 2021 – minor additions to the “Faults in a diode-resistor network” Diagnostic Reasoning
question.
16 April 2021 – minor additions to the Introduction chapter.
22 March 2021 – added more digits to Boltzmann’s constant, and clarified that Kelvin is 273.15
more than Celsius.
18 March 2021 – corrected one instance of “volts” that should have been capitalized “Volts”.
11 February 2021 – corrected several instances where “Ohms” was uncapitalized.
14 December 2020 – added commentary on multimeter testing of PN junctions to the Tutorial.
29 October 2020 – added some Challenge questions.
30 August 2020 – significantly edited the Introduction chapter to make it more suitable as a
109
110 APPENDIX F. VERSION HISTORY
pre-study guide and to provide cues useful to instructors leading “inverted” teaching sessions. Also
made some minor additions to the Tutorial chapter.
11 February 2020 – minor edits to the Tutorial.
24 January 2020 – added mention of “breakdown” to the Tutorial.
23 January 2020 – added Foundational Concepts to the list in the Conceptual Reasoning section.
5 January 2020 – added bullet-list of relevant programming principles to the Programming
References section.
2 January 2020 – removed from from C++ code execution output, to clearly distinguish it from
the source code listing which is still framed.
31 December 2019 – continued writing C++ code section modeling a PN junction.
30 December 2019 – began adding C++ code calculating current through a PN junction as a
function of voltage.
18 December 2019 – minor edits to diagnostic questions, replacing “no multiple faults” with “no
coincidental faults”.
20 October 2019 – added patent number to the Historical Reference section on George Pierce’s
invention using crystals as rectifiers.
18 October 2019 – document first created.
Index
Adding quantities to a qualitative problem, 88 Hwang, Andrew D., 97
AM radio, 14
Amplitude modulation, 14 Identify given data, 87
Annotating diagrams, 87 Identify relevant principles, 87
Anode, 5 Instructions for projects and experiments, 91
Intermediate results, 87
Bias, forward, 7 Interpreter, Python, 22
Bias, reverse, 7 Inverted instruction, 90
Breakdown, 12
Java, 19
C++, 18
Cathode, 5 Knuth, Donald, 96
Checking for exceptions, 88
Checking your work, 88 Lamport, Leslie, 96
Code, computer, 95 LED, 9
Compiler, C++, 18 Light-emitting diode, 9
Computer programming, 17 Limiting cases, 88
Load, 9
Datasheet, 12
Depletion region, 6, 8 Maxwell, James Clerk, 13
Detector, AM radio, 14 Metacognition, 68
Dimensional analysis, 87 Microsoft Excel, 32, 33, 35
Diode, 5 Moolenaar, Bram, 95
Diode equation, 8, 27 Murphy, Lynn, 63
Diode, light-emitting, 9
Doping, 7 N-type semiconductor, 6, 8
Edwards, Tim, 96 Ohm’s Law, 8
Electron tube, 5 Open-source, 95
Excel, Microsoft, 32, 33, 35
P-type semiconductor, 6, 8
Forward bias, 7 Pentode, 5
Periodic table of the elements, 6
Germanium, 8 Photovoltaic cell, 9
Graph values to solve a problem, 88 Problem-solving: annotate diagrams, 87
Greenleaf, Cynthia, 63 Problem-solving: check for exceptions, 88
Problem-solving: checking work, 88
How to teach with these modules, 90 Problem-solving: dimensional analysis, 87
111
112 INDEX
Problem-solving: graph values, 88 Triode, 5
Problem-solving: identify given data, 87 Tube, electron, 5
Problem-solving: identify relevant principles, 87 Tube, vacuum, 5
Problem-solving: interpret intermediate results,
87 Units of measurement, 87
Problem-solving: limiting cases, 88
Problem-solving: qualitative to quantitative, 88 Vacuum tube, 5
Problem-solving: quantitative to qualitative, 88 Visualizing a system, 87
Problem-solving: reductio ad absurdum, 88
Whitespace, C++, 18, 19
Problem-solving: simplify the system, 87
Whitespace, Python, 25
Problem-solving: thought experiment, 87
Work in reverse to solve a problem, 88
Problem-solving: track units of measurement, 87
WYSIWYG, 95, 96
Problem-solving: visually represent the system,
87
Problem-solving: work in reverse, 88
Programming, computer, 17
Python, 22
Qualitatively approaching a quantitative
problem, 88
Reading Apprenticeship, 63
Reductio ad absurdum, 88–90
Reverse bias, 7
Schoenbach, Ruth, 63
Scientific method, 68
Semiconductor, 6
Shockley diode equation, 8, 27
Shockley, William, 8, 27
Silicon, 6, 8
Simplifying a system, 87
Socrates, 89
Socratic dialogue, 90
Solar cell, 9
Solid state, 6
Source, 9
Source code, 18
SPICE, 63
Spreadsheet, 32, 33, 35
Stallman, Richard, 95
Temperature sensor, 9
Tetrode, 5
Thought experiment, 87
Torvalds, Linus, 95