Circuit Performance Research Articles

Numerical analysis and experimental research on the removal of CuO particles from monocrystalline silicon surfaces by picosecond laser

CuO particles on the surface of silicon wafers can seriously affect integrated circuits performance and service life. This paper carries out numerical calculations and experimental research on the removal of CuO particles from silicon substrates surfaces by picosecond laser. A thermal-stress coupled finite element model is established to simulate the changes in the temperature of silicon substrates and the thermal stress of CuO particles with laser action time and energy density, to predict the cleaning threshold of the particles and the damage threshold of the silicon substrates. The results show that the cleaning threshold for CuO particles with a particle size of 10 μm is 0.029 J/cm2 and the damage threshold for the silicon substrate is 0.512 J/cm2. As the laser energy density increases, the CuO particles removal rate on the silicon surface increases first and then decreases, and the silicon substrate roughness decreases first and then increases. When the laser energy density is 0.429J/cm2, the CuO particle removal rate reaches 93.42 %, the wafer surface is undamaged, and the roughness is as low as 1.33 nm. The ratio of Cu and Si elements on the cleaned silicon substrate surface is close to that on the silicon substrate surface before the sample was made.

Modeling, Prediction, and Results Correction of PDSH Circuits for Nanosecond Pulse Peak Detection

The peak detect and sample hold (PDSH) circuit is an important component of the light detection and ranging (LiDAR) system, because the PDSH circuit can correct the walk error of the time discriminator, and distinguish different objects at the same location. However, due to the requirement for high-precision measurement of nanosecond-scale pulse signals, the design of the PDSH circuit presents significant challenges. This paper accomplishes the modeling of the PDSH circuit, including the modeling of the PDSH measurement speed and the voltage step, quantifies various factors that affect the PDSH circuit measurement results, and makes predictions based on the model. Through the derivation and simplification of the rise process in the PDSH circuit, this study establishes a mathematical model to predict the performance of the PDSH circuit. Furthermore, this study also investigates the effect of circuit delay time on the measurement speed of the PDSH circuit. Meanwhile, this study analyzes the voltage step process, and an equivalent circuit model is derived through theoretical analysis. By utilizing a fitting method, the equivalent capacitance value of the diode is obtained. The simulation and experiment results show that the errors between the measurement speed model of the PDSH circuit and the actual circuit are no more than 1.98 ns and 2.03 ns, respectively. Thus, the measurement speed model can accurately predict whether the PDSH circuit meets the requirements. Moreover, the maximum absolute error of the equivalent circuit model is 19.87 mV, which can significantly reduce the error caused by the voltage step.

On the Use of Geometric Deep Learning for the Iterative Classification and Down-Selection of Analog Electric Circuits

Abstract Many complex engineering systems can be represented in a topological form, such as graphs. This paper utilizes a machine learning technique called Geometric Deep Learning (GDL) to aid designers with challenging, graph-centric design problems. The strategy presented here is to take the graph data and apply GDL to seek the best realizable performing solution effectively and efficiently with lower computational costs. This case study used here is the synthesis of analog electrical circuits that attempt to match a specific frequency response within a particular frequency range. Previous studies utilized an enumeration technique to generate 43,249 unique undirected graphs presenting valid potential circuits. Unfortunately, determining the sizing and performance of many circuits can be too expensive. To reduce computational costs with a quantified trade-off in accuracy, the fraction of the circuit graphs and their performance are used as input data to a classification-focused GDL model. Then, the GDL model can be used to predict the remainder cheaply, thus, aiding decision-makers in the search for the best graph solutions. The results discussed in this paper show that additional graph-based features are useful, favorable total set classification accuracy of 80% in using only 10% of the graphs, and iteratively built GDL models can further subdivide the graphs into targeted groups with medians significantly closer to the best and containing 88.2 of the top 100 best-performing graphs on average using 25% of the graphs.

Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation

Stabilizer simulation can efficiently simulate an important class of quantum circuits consisting exclusively of Clifford gates. However, all existing extensions of this simulation to arbitrary quantum circuits including non-Clifford gates suffer from an exponential runtime.To address this challenge, we present a novel approach for efficient stabilizer simulation on arbitrary quantum circuits, at the cost of lost precision. Our key idea is to compress an exponential sum representation of the quantum state into a single abstract summand covering (at least) all occurring summands. This allows us to introduce an abstract stabilizer simulator that efficiently manipulates abstract summands by over−approximating the effect of circuit operations including Clifford gates, non-Clifford gates, and (internal) measurements.We implemented our abstract simulator in a tool called Abstraqt and experimentally demonstrate that Abstraqt can establish circuit properties intractable for existing techniques.

Efficient RF-to-DC Converters for Biomedical Implantable Devices

The power management section associated with the biomedical circuit is very crucial and should be optimally designed for optimal utilization of power. This work discusses the different power shaping or conversion circuits that had been taken for their performance analysis. The two-performance metrics power conversion efficiency and susceptibility against the wireless power transfer have been taken to investigate the operational performance of the biomedical circuits against the input signal strength and operating frequencies. Simulated results confirm the CNFET-based circuit performance is very good at a small value of input voltage 0.6V and a broad range of operating frequency (953 MHz). Therefore, a CNFET-based circuit can be used suitably in implantable devices with optimum power utilization and a remote powering mechanism over the RF link.

A single-component, light-assisted uncaging switch for endoproteolytic release.

Proteases function as pivotal molecular switches, initiating numerous biological events. Notably, potyviral protease, derived from plant viruses, has emerged as a trusted proteolytic switch in synthetic biological circuits. To harness their capabilities, we have developed a single-component photocleavable switch, termed LAUNCHER (Light-Assisted UNcaging switCH for Endoproteolytic Release), by employing a circularly permutated tobacco etch virus protease and a blue-light-gated substrate, which are connected by fine-tuned intermodular linkers. As a single-component system, LAUNCHER exhibits a superior signal-to-noise ratio compared with multi-component systems, enabling precise and user-controllable release of payloads. This characteristic renders LAUNCHER highly suitable for diverse cellular applications, including transgene expression, tailored subcellular translocation and optochemogenetics. Additionally, the plug-and-play integration of LAUNCHER into existing synthetic circuits facilitates the enhancement of circuit performance. The demonstrated efficacy of LAUNCHER in improving existing circuitry underscores its significant potential for expanding its utilization in various applications.

Modulation by Neuropeptides with Overlapping Targets Results in Functional Overlap in Oscillatory Circuit Activation.

Neuromodulation lends flexibility to neural circuit operation but the general notion that different neuromodulators sculpt neural circuit activity into distinct and characteristic patterns is complicated by interindividual variability. In addition, some neuromodulators converge onto the same signaling pathways, with similar effects on neurons and synapses. We compared the effects of three neuropeptides on the rhythmic pyloric circuit in the stomatogastric ganglion of male crabs, Cancer borealis Proctolin (PROC), crustacean cardioactive peptide (CCAP), and red pigment concentrating hormone (RPCH) activate the same modulatory inward current, I MI, and have convergent actions on synapses. However, while PROC targets all four neuron types in the core pyloric circuit, CCAP and RPCH target the same subset of only two neurons. After removal of spontaneous neuromodulator release, none of the neuropeptides restored the control cycle frequency, but all restored the relative timing between neuron types. Consequently, differences between neuropeptide effects were mainly found in the spiking activity of different neuron types. We performed statistical comparisons using the Euclidean distance in the multidimensional space of normalized output attributes to obtain a single measure of difference between modulatory states. Across preparations, the circuit output in PROC was distinguishable from CCAP and RPCH, but CCAP and RPCH were not distinguishable from each other. However, we argue that even between PROC and the other two neuropeptides, population data overlapped enough to prevent reliable identification of individual output patterns as characteristic for a specific neuropeptide. We confirmed this notion by showing that blind classifications by machine learning algorithms were only moderately successful.Significance Statement It is commonly assumed that distinct behaviors or circuit activities can be elicited by different neuromodulators. Yet it is unknown to what extent these characteristic actions remain distinct across individuals. We use a well-studied circuit model of neuromodulation to examine the effects of three neuropeptides, each known to produce a distinct activity pattern in controlled studies. We find that, when compared across individuals, the three peptides elicit activity patterns that are either statistically indistinguishable or show too much overlap to be labeled characteristic. We ascribe this to interindividual variability and overlapping subcellular actions of the modulators. Because both factors are common in all neural circuits, these findings have broad significance for understanding chemical neuromodulatory actions while considering interindividual variability.

DC operating points of Mott neuristor circuits

In 1960 Hewitt Crane conceptualized neuristors as electronic logic networks that could mimic action potential generation by biological neurons. In 2012 Mott memristors were presented as nano-scale electronic devices for physically constructing neuristor networks. Both the original Mott memristor model and the simplified model presented in 2020 are stiff nonlinear first-order ordinary differential equations (ODEs) that describe the voltage controlled threshold switching and current controlled negative differential resistance, attributed to a Mott insulator-to-metal phase transition. By design, a Mott neuristor contains two identical Mott memristors plus linear resistors and capacitors (no inductors), which enables alternating threshold switching by the memristors to generate periodic (AC) output voltage spikes in response to a DC current or voltage input. This paper presents a steady-state analysis of dynamic neuristor models, including four-, five-, and six-state variables (each of which is a system of first-order ODEs involving the states) based on the original phenomenological model of the Mott memristor. Specifically, it reveals the unique stable operating points that occur for applied currents or voltages below the amounts needed to induce resistive switching. These DC operating points represent the physically meaningful “OFF” states for the circuit when the neuristor does not output voltage spikes. Jacques Hadamard's mathematical criteria for a well-posed physical model (existence, uniqueness, continuity, stability) motivated the search for these DC operating points (OFF states), which are needed for efficiently initializing neuristor models before conducting dynamic neuristor simulations. The key result of our analysis is the neuristor steady-state eq. (29) which is useful for understanding neuristor OFF states as well as the role of negative-differential resistance (NDR) in the operation of the Mott memristor model and neuristor circuits. In addition to the steady-state analysis, three numerical examples of dynamic neuristor circuit operation are also given and MATLAB code for the dynamic four-state model is available for interested readers.

Review of innovations in low-power flip-flops based on the development of innovative logic gates

Integrated circuits have advanced quickly alongside the semiconductor industry's tremendous growth. The primary design considerations for each circuit in a VLSI data path are minimization of area and power consumption. As a very important logic unit in the integrated circuit, reducing the flip-flop's power consumption is of great significance for improving the performance of the whole circuit. There are many ways to reduce the power consumption of the flip-flop. This paper reviews several new low-power flip-flop designs using methods to improve the logic structure of flip-flops and their logic gates, including a reversible flip-flop design with reversible gates, a flip-flop design with memristors, and a sense amplifier-based flip-flop. The analysis shows that all three options for improving the logic gate can reduce the power consumption of the flip-flops and also have a positive effect on reducing the size of the device.

GA evolved CGP configuration data for digital circuit design on embryonic architecture

Embryonic architecture that carries self-evolving design with fault tolerant feature is proposed for deep space missions. Fault tolerance is achieved in the embryonic architecture due to its homogeneous structure. The cloning of configuration data or genome data to all the embryonic cells makes each cell capable of selecting required cell function using selective gene. The primary digital circuits of avionics are implemented on the fabric, where the configuration data in Cartesian Genetic Programming (CGP) format is evolved through customized GA. The CGP format is preferred over LUT format for the circuit configuration data due to its fixed data size in case of modular design. Further the CGP format enables fault detection at embryonic cell level as well as logic gate level. The various combinational and sequential circuits like adder, comparator, multiplier, register and counter are designed and implemented on embryonic fabric using Verilog. The circuit performance is evaluated using simulation. The proposed PHsClone genetic algorithm (GA) design with parallel-pipeline approach is to achieve faster convergence. Four concurrent PHsClone GA executions (four parallel threads) achieve convergence for the 10 times faster for a 1-bit adder, and 3 times faster for a 2-bit comparator.

A simplified three-diode model for photovoltaic module: cell modeling and performance analysis

Purpose Estimation of solar cell parameters, mathematical modeling and the actual performance analysis of photovoltaic (PV) cells at various ecological conditions are very important in the design and analysis of maximum power point trackers and power converters. This study aims to propose the analysis and modeling of a simplified three-diode model based on the manufacturer’s performance data. Design/methodology/approach A novel technique is presented to evaluate the PV cell constraints and simplify the existing equation using analytical and iterative methods. To examine the current equation, this study focuses on three crucial operational points: open circuit, short circuit and maximum operating points. The number of parameters needed to estimate these built-in models is decreased from nine to five by an effective iteration method, considerably reducing computational requirements. Findings The proposed model, in contrast to the previous complex nine-parameter three-diode model, simplifies the modeling and analysis process by requiring only five parameters. To ensure the reliability and accuracy of this proposed model, its results were carefully compared with datasheet values under standard test conditions (STC). This model was implemented using MATLAB/Simulink and validated using a polycrystalline solar cell under STC conditions. Originality/value The proposed three-diode model clearly outperforms the earlier existing two-diode model in terms of accuracy and performance, especially in lower irradiance settings, according to the results and comparison analysis.

Investigating and Modeling the Factors That Affect Genetic Circuit Performance.

Over the past 2 decades, synthetic biology has yielded ever more complex genetic circuits that are able to perform sophisticated functions in response to specific signals. Yet, genetic circuits are not immediately transferable to an outside-the-lab setting where their performance is highly compromised. We propose introducing a broader test step to the design-build-test-learn workflow to include factors that might contribute to unexpected genetic circuit performance. As a proof of concept, we have designed and evaluated a genetic circuit in various temperatures, inducer concentrations, nonsterilized soil exposure, and bacterial growth stages. We determined that the circuit's performance is dramatically altered when these factors differ from the optimal lab conditions. We observed significant changes in the time for signal detection as well as signal intensity when the genetic circuit was tested under nonoptimal lab conditions. As a learning effort, we then proceeded to generate model predictions in untested conditions, which is currently lacking in synthetic biology application design. Furthermore, broader test and learn steps uncovered a negative correlation between the time it takes for a gate to turn ON and the bacterial growth phases. As the synthetic biology discipline transitions from proof-of-concept genetic programs to appropriate and safe application implementations, more emphasis on test and learn steps (i.e., characterizing parts and circuits for a broad range of conditions) will provide missing insights on genetic circuit behavior outside the lab.

Improving performance of pump-controlled hydraulic circuits for single-rod actuators: conceptual study

Pump-controlled hydraulic circuits are more efficient than conventional valve-controlled ones. Pump-controlled hydraulic circuits for double rod cylinders are well developed and, presently, implemented in many applications including aviation. Nevertheless, current pump-controlled hydraulic circuits for single-rod cylinders encounter performance issues during specific operating conditions. Pressure and actuator velocity oscillations are encountered when operating in this critical zone. Different concepts, techniques and designs are proposed by researchers to overcome such vibration issues. In this research, three different concepts to overcome the reported oscillation problem in these circuits are presented; namely: (1) shifting of critical zone into lower loading ranges, (2) applying selective leakage, and (3) applying selective throttling. Simulation studies indicated that the new concepts alleviated the oscillation issue of the common pump-controlled circuits, and improved their performances. The second and third concepts, in particular, were capable of eliminating the whole critical zone. The first concept reduced the area of the critical zone in the load-velocity plane and lessened undesirable effect of oscillations. Simulation studies further proved the enhanced performance of circuits that applies these concepts as compared to previously-designed circuits.

Scattering-induced circuit modelling and performance analysis of coupled hybrid Interconnections: Sub-threshold performance evaluation

This paper presents the scattering induced circuit modelling and performance analysis in terms of crosstalk and frequency stability in the newly proposed hybrid interconnects operating in the sub-threshold domain. The electrical performances of hybrid copper carbon-nanotube (HCNT), hybrid copper graphene nanoribbon (HGNR) and hybrid Copper carbon (H Carbon) interconnects are examined and compared with that of copper (Cu), single walled carbon nanotube bundles (SWCNTs) and lithium doped multilayer graphene nanoribbon (MLGNR) interconnects in terms of dynamic and functional crosstalk results by employing the transmission line (TL) analytical model for sub-threshold applications. The impact of the grain-size on the resistivity of Cu and the various scatterings induced mean free path (MFP) on the overall resistance has been analysed in the modelling of HGNR interconnects. The comprehensive analysis of the crosstalk induced delay (dynamic crosstalk), the positive peaks and the time-duration (functional crosstalk) ensures the efficacy of hybrid interconnects, especially H Carbon interconnects in the designing of on-chip interconnects. It has also been observed from the frequency response that the maximum 3-dB bandwidth is obtained in the case of H Carbon hybrid interconnects (approx. 6.7586 × 1010 Hz) at 300 K temperature values. Further, the bandwidth values tend to decrease with the rise in temperature values.

A single-phase full-bridge soft-switching inverter circuit with an auxiliary resonant circuit

A new topological structure is proposed in this article for the traditional single-phase full-bridge inverter circuit by adding an auxiliary synchronizing resonant circuit. Without extra switching transistors, the complexity of the control circuit is simplified while enabling zero voltage switching (ZVS) functionality. The significance of this proposed topology is that the switching transistors of all bridge arms are sharing one common synchronizing unit which is constructed with an absorbing inductor and capacitor. In this way, the added-on components can be substantially reduced for the main switching transistor circuit. By utilizing a big-volume capacitor as the constant voltage source, the sourceless energy feedback unit can minimize the switching losses. In the meantime, the proportional-resonant feedback circuit can modify the sinusoidal pulse width modulation (SPWM) duty ratio to stabilize the output current. In the PSIM power electronic simulation software environment, the operation of the soft-switching inverter circuit is analyzed to demonstrate our proposed topology can reduce the on-off switching losses as expected for the switching transistors of the soft-switching inverter circuit.

Improved Duty Compensation Control-Based Bidirectional Resonant DC−DC Converter With Reduced Input-Current Ripple for Battery Energy Storage Systems

This paper proposes an improved duty control-based resonant bidirectional dc–dc converter (BDC) to remarkably minimize input-current ripple for battery energy storage systems. The proposed converter offers a resonant-boost operation using a pulse-width-modulation (PWM) full-bridge circuit with a push-pull transformer under the forward-mode. Whereas, in the backward-mode, a resonant-buck operation is implemented with a PWM neutral-point-clamped (NPC)-type circuit. Unlike conventional current-fed BDCs, the most appealing characteristic of the proposed converter is the NPC-type structure with a push-pull transformer, which can significantly mitigate the input-current ripple without using extra input-inductors. Moreover, the proposed BDC minimizes the conduction-loss of the low-voltage side bottom switches by alleviating unbalanced DC offset-currents via proposed duty-compensation control under mismatched magnetizing inductances of the transformer's primary-windings. The designed circuit operation is analyzed in detail and its practicability has been fully confirmed with the proportional-integral and spider-monkey-optimization control techniques-based experimental verifications using a prototype 1-kW test-bed.

Design of Fully Differential Amplification Circuit and Analysis of Related Parameters Based on Feedback Mechanism

In this paper, a new feedback-based mismatch reduction method is proposed for CMOS process-based differential circuit design. The method combines an active feedback circuit and a differential amplifier circuit to reduce the error caused by device mismatch by utilizing the feedback signal, which is calculated to achieve higher circuit performance and accuracy. Meanwhile, based on the actual circuit simulation in Candence, it is concluded that under the conditions of input voltage of 5V, operating current of 100mA, and the same transistor parameters, the circuit with the introduction of the feedback mechanism is able to achieve a maximum gain of about 10dB and a lower common mode rejection ratio at the same frequency compared with the circuit without feedback.

STUDY OF THE PASSAGE OF MAGNETIC FLUXES
 THROUGH ROLLING ROLLERS AS PART OF MAGNETIC CIRCUITS

Among the wide variety of different converting devices, there are also devices for the direct conversion of mechanical
 energy into thermal energy. They are of various types, including the induction type. One way to improve
 the conversion efficiency in such devices is to eliminate air gaps in switched magnetic circuits to increase the intensity
 of magnetic fluxes. The degree of weakening of the magnetic flux during its passage through the rolling rollers
 as part of the magnetic circuit has not yet been evaluated. Therefore, in this paper, an attempt is made to quantify
 the degree of weakening of the magnetic flux in different modes of operation of an unbranched magnetic circuit
 containing a rolling roller element. The obtained dependencies will make it possible to judge the level of increase
 in the efficiency of induction devices for the direct conversion of mechanical energy into thermal energy with the indicated
 option of excluding air gaps in the magnetic circuits of the device.

Ambulatory 7-day mechanical circulatory support in sheep model of pulmonary hypertension and right heart failure

Right heart failure is the major cause of death in pulmonary hypertension. Lung transplantation is the only long-term treatment option for patients who fail medical therapy. Due to the scarcity of donor lungs, there is a critical need to develop durable mechanical support for the failing right heart. A major design goal for durable support is to reduce the size and complexity of devices to facilitate ambulation. Toward this end, we sought to deploy wearable mechanical support technology in a sheep disease model of chronic right heart failure. In 6 sheep with chronic right heart failure, a mechanical support system consisting of an extracorporeal blood pump coupled with a gas exchange unit was attached in a right atrium-to-left atrium configuration for up to 7days. Circuit performance, hematologic parameters, and animal hemodynamics were analyzed. Six subjects underwent the chronic disease model for 56 to 71days. Three of the subjects survived to the 7-day end-point for circulatory support. The circuit provided 2.8 (0.5) liter/min of flow compared to the native pulmonary blood flow of 3.5 (1.1) liter/min. The animals maintained physiologically balanced blood gas profile with a sweep flow of 1.2 (1.0) liter/min. Two animals freely ambulated while wearing the circuit. Our novel mechanical support system provided physiologic support for a large animal model of pulmonary hypertension with right heart failure. The small footprint of the circuit and the low sweep requirement demonstrate the feasibility of this technology to enable mobile ambulatory applications.

The Impact of Restricting Air Intake in Self-Aspirated Flotation Cells at Los Pelambres Concentrator

This article describes the impact of restricting the air intake in industrial 250 m3 WEMCO flotation cells at Los Pelambres concentrator. The influence of air restriction on the hydrodynamic and metallurgical performance of this type of machine was evaluated. The experiments were conducted in single flotation cells and entire rougher banks. In all cases, the gas holdup was measured to estimate the effectiveness of the obstruction system to decrease the air concentration. In single cells, axial profiles for solid percentage and particle size were evaluated. In addition, mass balances were conducted to assess the copper recoveries and concentrate features. In individual cells, air restriction led to a decrease in the gas holdup. However, this slight change was enough to obtain a more stable froth zone and a better solid suspension. The latter was observed as: (i) a higher P80 below the pulp–froth interface, (ii) a less diluted pulp at this level, (iii) a slightly higher Cu recovery, and (iv) a coarser concentrate product. A mineralogical analysis of the concentrate sample also showed the presence of coarser liberated Cu-sulfide particles. The results in single cells suggested an improvement in the recovery of coarse particles via more intense solid suspension. The air intake was also restricted in three rougher banks to assess the impact of air obstruction on the overall performance of the respective circuit. Eleven out of fourteen cells were operated with air restriction, which led to a significant improvement in recovery of 0.9%–1.6% (absolute), at a 95% confidence level. Size-by-size mass balances were also conducted for the rougher circuits, which proved that the recovery improvements were justified by the simultaneous increase in the recovery of coarse and fine particles. Thus, a restriction in the air intake showed that a decrease in the gas holdup (and in the bubble surface area flux) was compensated by better solid suspension and a higher collision efficiency in the draft tube. The former promoted the recovery of coarse particles in the quiescent zone, whereas the latter improved the interaction between bubbles and fine particles. Further developments are being made to implement a regulatory control strategy for the air intake in self-aspirated flotation cells and to use this approach for optimizing industrial flotation banks.