Unlike conventional transistor fabrication, which takes place at elevated temperatures and requires high precision and ultraclean conditions, making fiber transistors is “totally compatible with the weaving process,” says Lee. She’s slated to present this new work at an international meeting on electronic devices next month in Washington, DC.

The two researchers make their new transistors by coating hair-thin strands of aluminum with an electrically insulating film. Doing that requires oven temperatures, but the step is completed before weaving takes place. Atop the insulating film, the researchers deposit a layer of pentacene, an organic chemical that behaves as a semiconductor.
In the lab, the researchers have demonstrated another important step in making fiber-based circuits: By positioning threads across the fiber transistors, the Berkeley team can deposit thin films of gold on the fibers except in the tiny areas where the overlying thread masks incoming gold vapor. This process breaks the fibers into discrete transistor regions, each of which can be contacted individually with thin, metallic wires during the weaving process.

“Using the fibers of the textile as shadow masks points to a possibly inexpensive way of making transistors on fabric,” comments Sigurd Wagner of Princeton University. On the other hand, pentacene transistors will require additional protective coatings to prevent degradation by moisture or exposure to the air, he notes.

Polytronics is an outgrowth of evolvable hardware (EHW). The basic concepts and some specific implementations of EHW were described in a number of previous NASA Tech Briefs articles. To recapitulate: The essence of EHW is to design, construct, and test a sequence of populations of circuits that function as incrementally better solutions of a given design problem through the selective, repetitive connection and/or disconnection of capacitors, transistors, amplifiers, inverters, and/or other circuit building blocks. The evolution is guided by a search-and-optimization algorithm (in particular, a genetic algorithm) that operates in the space of possible circuits to find a circuit that exhibits an acceptably close approximation of the desired functionality. The evolved circuits can be tested by computational simulation (in which case the evolution is said to be extrinsic), tested in real hardware (in which case the evolution is said to be intrinsic), or tested in random sequences of computational simulation and real hardware (in which case the evolution is said to be mixtrinsic).
The NASA Tech Briefs article most relevant to the emergence of polytronics is the preceding article, “EHW Approach to Temperature Compensation of Electronics.” Polytronics originated from recognition that the EHW approach makes it possible to go beyond mere compensation for deterioration of circuit functionality with temperature: The EHW approach is a means of designing a circuit to perform an acceptable approximation of almost any desired function at one or more temperatures. In addition to or instead of temperature, the functionality of a circuit could be made to depend on such variables as supply or bias potentials, states of digital control signals, signal frequencies, and/or the intensity of illumination.

Going beyond the temperature-dependent AND/OR gate, the following are a few additional examples of multifunctionality that could be implemented in polytronics:

* A digital circuit could pass data in either of two opposite directions and perform the same function or different functions in the two directions.

* The modes of operation of an entire computer or other complex circuit could be changed almost instantaneously by changing the temperature, supply voltage, or other parameter(s).

* A circuit could be made to perform one (or more) hidden function(s) in addition to a readily observable main function. For example, a hidden function could be an authentication signal that would appear only under specified conditions (for example, supply voltage above a specified level and temperature below a specified level).

* An increase in temperature beyond a specified level could trigger a desired reactive behavior. For example a “smart fuse” circuit could cause guidance circuitry to function differently at higher temperature.

The current research in polytronics involves two modes of evolution that, in EHW, would have been denoted as extrinsic and mixtrinsic, respectively. Each mode is characterized by a different combination of advantages and disadvantages.

* In one mode, evolution occurs entirely by computational simulation. For example, circuits can be computationally modeled as consisting only of negative-channel metal oxide semiconductor (NMOS) and positive-channel metal oxide semiconductor (PMOS) transistors that can be connected in arbitrary topologies. The advantage of this mode is that it enables free exploration of the search space, with few or no topological restrictions like those that occur in practice; the lack of restrictions can favor the emergence of new designs. The disadvantage of this approach is that there is no implementation of evolved designs in hardware.

EVERETT, Wash. - Fluke Corporation, the world’s leading supplier of test and measurement equipment, introduces the 28x series of universal waveform generators that produce multiple signals to test complex electronic circuits. The 28x series employs a direct digital synthesis generator with variable clock sampling technology to faithfully reproduce waveforms at any repetition rate.

The series includes the Model 281 single-channel, Model 282 two-channel, and Model 284 four-channel generators. All have extensive signal simulation capabilities, including arbitrary waveforms, function, trigger, tone and noise generators, and amplitude modulation source. Included is Waveform Manager Plus software, which creates, manipulates and manages arbitrary waveforms within a single Windows[R]-based program.
Fluke Corporation

Fluke Corporation is the world leader in compact, professional electronic test tools. Fluke customers are technicians, engineers, electricians and metrologists who install, troubleshoot, and manage industrial electrical and electronic equipment and calibration processes for quality control.

Undergraduate electronic circuits textbooks, such as Ref. 1, introduce the hysteresis phenomena to their readers while attempting to explain the behaviour of a simple op-amp comparator with positive feedback. Such a circuit is then characterized as bi-stable; i.e. it has two different driving point characteristics depending on whether the input voltage is increasing or decreasing. When plotted together on the same V^sub i^-V^sub o^ chart, a discontinuous loop appears and is termed the hysteresis loop. The sudden jumps in the loop are attributed to the bi-stable nature of the circuit and are not discussed any further.

From a nonlinear dynamics point of view, sudden jumps correspond to very fast energy transfer. Accordingly, an energy storage element (capacitor or inductor) of a significantly small value must exist to hold this transit energy transfer. Including a parasitic capacitor (inductor) is necessary but not sufficient to explain the hysteresis jumps, as explained in detail in the pioneering work of Kennedy and Chua2 which ironically never found its way to any textbook. In particular, the two necessary conditions for hysteresis to occur are:
1 Astatic d.c. nonlinear non-monotone driving-point characteristic.

2 Aparasitic energy storage element to accommodate the fast energy transfer. This fast transition is described by a stiff differential equation (one which contains two widely separated time constants).

The work presented here has two objectives:

(i) To show how the hysteresis behaviour can be explained in a clear manner with a circuit simulation example.

(ii) To show how nonlinear driving-point characteristics can be designed.

Explaining hysteresis

To explain hysteresis, one should address the two necessary conditions stated above. The first condition relates to the existence of d.c. nonlinear characteristics. In Fig. 1, the four basic nonlinear characteristics which can be obtained from any three segments are shown. The characteristics of Figs 1(a) and 1(b) are monotone which means they are equally controllable via the x-axis or the y-axis variable. A single value for x corresponds to a single value for y. However, Figs 1(c) and 1(d) are non-monotone because they are controllable only through the y-axis variable. Attempting to control these characteristics through the x-axis variable results in multiple values of y for the same value of x, which is not possible in electronic circuits. Accordingly, the apparent characteristics acquire ‘discontinuous jumps’ and follow the dashed lines in Fig. 1. Stimulating hysteresis is thus associated with controlling a nonlinear non-monotone driving-point characteristic via the wrong control variable.

In order to explain the ‘jump’ phenomena, which is a result of a fast energy transfer process, nonlinear dynamics principles3 imply that a transit (parasitic) energy storage element (capacitor or inductor) is necessary to accurately model this behaviour4. An inductor (capacitor) is considered for current (voltage)-controlled characteristics. To demonstrate this, the active tank oscillator, shown in the upperright corner of Fig. 2, is taken as an example. This classical sinusoidal oscillator employs a voltage-controlled negative resistor, which can be implemented using an op-amp, as shown in the lower-left corner of the same figure. However, this negative resistor has a limited linear range (due to the op-amp saturation voltage) and on the full range it is essentially nonlinear, as indicated by the PSpice d.c. simulation of Fig. 2. It is clear that this nonlinear resistor is non-monotone and should not be controlled by the y-axis variable; i.e. the input current. Attempting to use this nonlinear negative resistor in a current-controlled, rather than voltage-controlled, structure will stimulate hysteresis.

Laboratory activities play a very important role in understanding theoretical concepts as well as encouraging students to confront practical challenges. However, the implementation of a laboratory of dynamical systems and process control encounters several challenges, such as space limitations, financial support, difficulties of building a real system, etc. In this context, an electronic analogue can be extremely helpful in developing experimental activities destined to teach dynamical systems and process control, since the dynamical behaviour of a specific system can be easily reproduced through an analogous electronic system.1
Using robust, compact, versatile and inexpensive electronic circuits, it is possible to perform a qualitative study of the nonlinear equations of dynamical behaviour to obtain insights into the nature of their solutions.2 Since the dynamical behaviour of real systems can be expressed by differential equations, this electronic analogy can be easily used to implement educational platforms that reproduce mechanical, electrical, chemical, thermal, hydraulic, economic or biological systems. In this analogy, the original system variables and its derivatives are represented by electric signals, and the system behaviour can be directly observed and recorded on oscilloscopes and/or acquisition boards, avoiding the use of expensive and complex sensor devices.

Although an electronic prototype does not completely reproduce the real system, it can incorporate several aspects of practical implementations such as unpredictable noises, uncertainties, measurement problems and failures that are very difficult to reproduce by means of computational simulation. Another advantage of the electronic analogy is the possibility of on-line adjustments on system parameters.3 However, since electric signals are generally subject to severe limitations, to assure the correct operation and the integrity of the electronic devices, correct reproduction of a dynamical system from a direct electronic implementation can become relatively difficult.

This paper presents a methodology to design analogous electronic circuits that reproduce the dynamical behaviour of physical systems. The implementation of these electronic circuits can be used in practical experiments for the study of dynamical systems and other related subjects. It is always desirable to obtain an electronic version of any system which is as simple as possible to reduce difficulties with its implementation. If necessary, the original model must be modified to restrict the amplitudes and frequencies of electrical signals aiming to respect the limitations imposed by electronic devices and to assure the correct reproduction of a dynamical system. Case studies are presented, in which electronic circuits are designed and experimentally implemented to reproduce the dynamical behaviour of three natural chaotic systems: the forced Duffing system, the Lorenz system and the Rössler system.

Principles of electronic analogy

The first step towards understanding, analysis, design and control of an intricate real system is to obtain its mathematical model,1,4 which usually is expressed as a set of ordinary differential equations and can be considered as the mathematical analogue of a real system.5 The development of an adequate mathematical model requires a deep knowledge of the dynamical system under study in order to describe uncertainties and hypotheses related to its practical operation.3,5

Considering that real implementations of electric and electronic systems are easily realised, electronic circuits can be used to emulate the dynamical behaviour of other physical systems, where the original system variables are represented by electric signals. This concept is known as analogue simulation, and it has practically been forgotten in consequence of the development of fast digital computers and efficient software packages, such as MATLAB/Simulink or VISSIM. Nevertheless, since a physical realisation of several real systems can be very difficult and expensive, this technique remains as an interesting solution to the practical teaching of dynamical systems and process control, allowing an efficient experimental analysis.

How do you design nano-sized circuits and guarantee “nearly perfect yields” in the process?
According to HP coding theory will be the key to building a “defect tolerant interface” for its cross-bar architecture in future processors.

Coding theory is most strongly associated with solving math, cryptography and telecom problems.

“We have invented a completely new way of designing an electronic interconnect for nano-scale circuits using coding theory,” said Stan Williams, HP Senior Fellow and director, Quantum Science Research at HP Labs. “By using a cross-bar architecture and adding 50 percent more wires as an ‘insurance policy,’ we believe it will be possible to fabricate nano-electronic circuits with nearly perfect yields even though the probability of broken components will be high.”

Abstract We show how the hysteresis behaviour in electronic circuits can be explained in a robust manner using PSpice transient simulations. Furthermore, we describe a simple circuit for three-segment nonlinear characteristic shaping and show how this circuit can be used to produce hysteresis loops. The realisation of relaxation oscillators is then given as a typical application.

Keywords amplifiers; hysteresis; nonlinear circuits; nonlinear dynamics
Undergraduate electronic circuits textbooks, such as Ref. 1, introduce the hysteresis phenomena to their readers while attempting to explain the behaviour of a simple op-amp comparator with positive feedback. Such a circuit is then characterized as bi-stable; i.e. it has two different driving point characteristics depending on whether the input voltage is increasing or decreasing. When plotted together on the same V^sub i^-V^sub o^ chart, a discontinuous loop appears and is termed the hysteresis loop. The sudden jumps in the loop are attributed to the bi-stable nature of the circuit and are not discussed any further.

From a nonlinear dynamics point of view, sudden jumps correspond to very fast energy transfer. Accordingly, an energy storage element (capacitor or inductor) of a significantly small value must exist to hold this transit energy transfer. Including a parasitic capacitor (inductor) is necessary but not sufficient to explain the hysteresis jumps, as explained in detail in the pioneering work of Kennedy and Chua2 which ironically never found its way to any textbook. In particular, the two necessary conditions for hysteresis to occur are:
the x-axis or the y-axis variable. A single value for x corresponds to a single value for y. However, Figs 1(c) and 1(d) are non-monotone because they are controllable only through the y-axis variable. Attempting to control these characteristics through the x-axis variable results in multiple values of y for the same value of x, which is not possible in electronic circuits. Accordingly, the apparent characteristics acquire ‘discontinuous jumps’ and follow the dashed lines in Fig. 1. Stimulating hysteresis is thus associated with controlling a nonlinear non-monotone driving-point characteristic via the wrong control variable.

In order to explain the ‘jump’ phenomena, which is a result of a fast energy transfer process, nonlinear dynamics principles3 imply that a transit (parasitic) energy storage element (capacitor or inductor) is necessary to accurately model this behaviour4. An inductor (capacitor) is considered for current (voltage)-controlled characteristics. To demonstrate this, the active tank oscillator, shown in the upperright corner of Fig. 2, is taken as an example. This classical sinusoidal oscillator employs a voltage-controlled negative resistor, which can be implemented using an op-amp, as shown in the lower-left corner of the same figure. However, this negative resistor has a limited linear range (due to the op-amp saturation voltage) and on the full range it is essentially nonlinear, as indicated by the PSpice d.c. simulation of Fig. 2. It is clear that this nonlinear resistor is non-monotone and should not be controlled by the y-axis variable; i.e. the input current. Attempting to use this nonlinear negative resistor in a current-controlled, rather than voltage-controlled, structure will stimulate hysteresis.

Abstract The behaviour of dynamical systems can be reproduced from analogous electronic circuits, which allows the study of many interesting phenomena associated with them using inexpensive and versatile electronic components easily found on the market. This paper proposes a methodology to develop didactic platforms for the study of dynamical systems based on analogous electronic circuits. Presented here are the design and implementation of three electronic circuits that mimic natural chaotic systems: the forced Duffing system, the Lorenz system and the Rössler system.
Laboratory activities play a very important role in understanding theoretical concepts as well as encouraging students to confront practical challenges. However, the implementation of a laboratory of dynamical systems and process control encounters several challenges, such as space limitations, financial support, difficulties of building a real system, etc. In this context, an electronic analogue can be extremely helpful in developing experimental activities destined to teach dynamical systems and process control, since the dynamical behaviour of a specific system can be easily reproduced through an analogous electronic system.1
Using robust, compact, versatile and inexpensive electronic circuits, it is possible to perform a qualitative study of the nonlinear equations of dynamical behaviour to obtain insights into the nature of their solutions.2 Since the dynamical behaviour of real systems can be expressed by differential equations, this electronic analogy can be easily used to implement educational platforms that reproduce mechanical, electrical, chemical, thermal, hydraulic, economic or biological systems. In this analogy, the original system variables and its derivatives are represented by electric signals, and the system behaviour can be directly observed and recorded on oscilloscopes and/or acquisition boards, avoiding the use of expensive and complex sensor devices.

Although an electronic prototype does not completely reproduce the real system, it can incorporate several aspects of practical implementations such as unpredictable noises, uncertainties, measurement problems and failures that are very difficult to reproduce by means of computational simulation. Another advantage of the electronic analogy is the possibility of on-line adjustments on system parameters.3 However, since electric signals are generally subject to severe limitations, to assure the correct operation and the integrity of the electronic devices, correct reproduction of a dynamical system from a direct electronic implementation can become relatively difficult.

This paper presents a methodology to design analogous electronic circuits that reproduce the dynamical behaviour of physical systems. The implementation of these electronic circuits can be used in practical experiments for the study of dynamical systems and other related subjects. It is always desirable to obtain an electronic version of any system which is as simple as possible to reduce difficulties with its implementation. If necessary, the original model must be modified to restrict the amplitudes and frequencies of electrical signals aiming to respect the limitations imposed by electronic devices and to assure the correct reproduction of a dynamical system. Case studies are presented, in which electronic circuits are designed and experimentally implemented to reproduce the dynamical behaviour of three natural chaotic systems: the forced Duffing system, the Lorenz system and the Rössler system.

Principles of electronic analogy

The first step towards understanding, analysis, design and control of an intricate real system is to obtain its mathematical model,1,4 which usually is expressed as a set of ordinary differential equations and can be considered as the mathematical analogue of a real system.5 The development of an adequate mathematical model requires a deep knowledge of the dynamical system under study in order to describe uncertainties and hypotheses related to its practical operation.3,5

Considering that real implementations of electric and electronic systems are easily realised, electronic circuits can be used to emulate the dynamical behaviour of other physical systems, where the original system variables are represented by electric signals. This concept is known as analogue simulation, and it has practically been forgotten in consequence of the development of fast digital computers and efficient software packages, such as MATLAB/Simulink or VISSIM. Nevertheless, since a physical realisation of several real systems can be very difficult and expensive, this technique remains as an interesting solution to the practical teaching of dynamical systems and process control, allowing an efficient experimental analysis.

The main electronic component used in this approach is the operational amplifier, a multistage amplifier with differential inputs, the generic circuit for which is presented in Fig. 1. Depending on the impedances used in its structure, it can perform several mathematical operations involving voltage signals such as multiplication by constant, subtraction, derivatives, weighted sum and weighted integration. Nonlinear functions can be obtained by splitting the function curve into line segments generated by circuits with polarized diodes.3,6 Since a mathematical model is generally defined as a set of differential equations, the most important cell in analogous electronic implementations is the inverter-weighted integrator, where V^sub i+^ is grounded, Z^sub i^ is multi-input resistances and Z^sub f^ is a capacitance C. Considering three inputs, the transfer function of the weighted integrator is expressed by:

How do you design nano-sized circuits and guarantee “nearly perfect yields” in the process?
According to HP coding theory will be the key to building a “defect tolerant interface” for its cross-bar architecture in future processors.

Coding theory is most strongly associated with solving math, cryptography and telecom problems.

“We have invented a completely new way of designing an electronic interconnect for nano-scale circuits using coding theory,” said Stan Williams, HP Senior Fellow and director, Quantum Science Research at HP Labs. “By using a cross-bar architecture and adding 50 percent more wires as an ‘insurance policy,’ we believe it will be possible to fabricate nano-electronic circuits with nearly perfect yields even though the probability of broken components will be high.”
It’s the nano-equivalent of a telephone operator that keeps patching your call through no matter how many cables break.

It’s hard to pinpoint exactly what small tech is because it has so many wide-ranging applications. “I would call it more of a revolution than an evolution,” says Snyder. Nanotechnology, for example, deals with matter at an atomic and molecular level–that is, with matter often described as being less than the width of a human hair in size. It’s appearing in everything from stainproof coating for fabrics to scratch-resistant coating for eyeglasses to miniscule computer chip circuits from HP Labs.

Research funding for small tech is enormous. Ardesta is devoted to investing in and helping launch various small tech ventures with an ultimate goal of bringing actual products to market. Many businesses in this fledgling technological area are small entrepreneurial start-ups and spin-offs from research institutions. Life sciences and materials manufacturing are two industries that will really feel the early effects of the growing small tech market.
Eventually, though, small tech will touch just about everything. Synder calls it pervasive and transparent. Some applications are out already and operating in your business right under your nose. Microtech is built into inkjet cartridges and portable projectors. At SmallTimes.com, a clearinghouse for information on small technology, the section devoted to applications is an eye-opener: A recent visit to the site brought up articles on nanotech use in products such as tennis rackets and LCD monitors, among others.

There are a million microscopic reasons to get excited, but it’s important to keep them all in perspective. Synder sees an accelerating growth curve over the next five years as small tech makes its way into real-life markets. But you shouldn’t expect companies to shout “nano” or “MEMS” in their product advertising. The way you’ll know small tech has touched your business is when Snyder’s mantra comes into play: “Smaller, faster, better, cheaper.”