Circuit Approach Research Articles

Solving transport equations on quantum computers—potential and limitations of physics-informed quantum circuits

AbstractQuantum circuits with trainable parameters, paired with classical optimization routines can be used as machine learning models. The recently popularized physics-informed neural network (PINN) approach is a machine learning algorithm that solves differential equations by incorporating them into a loss function. Being a mesh-free method, it is a promising approach for computational fluid dynamics. The question arises whether the properties of quantum circuits can be leveraged for a quantum physics-informed machine learning model. In this study, we compare the classical PINN-ansatz and its quantum analog, which we name the physics-informed quantum circuit (PIQC). The PIQC simulations are performed on a noise-free quantum computing simulator. Studying various differential equations, we compare expressivity, accuracy and convergence properties. We find that one-dimensional problems, such as the linear transport of a Gaussian-pulse or Burgers’ equation, allow a successful approximation with the classical and the quantum ansatz. For these examples, the PIQC overall performs similarly to PINN and converges more consistently and for Burgers’ equations even faster. While this is promising, the chosen quantum circuit approach struggles to approximate discontinuous solutions which the classical PINN-ansatz can represent. Based on this comparison, we extrapolate that the required number of qubits for solving two-dimensional problems in aerodynamics may already be available in the next few years. However, the acceleration potential is currently unclear and challenges like noisy circuits and approximations of discontinuous solutions have to be overcome.

Inductive Frequency-Coded Sensor for Non-Destructive Structural Strain Monitoring of Composite Materials

Structural composite materials have gained significant appeal because of their ability to be customized for specific mechanical qualities for various applications, including avionics, wind turbines, transportation, and medical equipment. Therefore, there is a growing demand for effective and non-invasive structural health monitoring (SHM) devices to supervise the integrity of materials. This work introduces a novel sensor design, consisting of three spiral resonators optimized to operate at distinct frequencies and excited by a feeding strip line, capable of performing non-destructive structural strain monitoring via frequency coding. The initial discussion focuses on the analytical modeling of the sensor, which is based on a circuital approach. A numerical test case is developed to operate across the frequency range of 100 to 400 MHz, selected to achieve a balance between penetration depth and the sensitivity of the system. The encouraging findings from electromagnetic full-wave simulations have been confirmed by experimental measurements conducted on printed circuit board (PCB) prototypes embedded in a fiberglass-based composite sample. The sensor shows exceptional sensitivity and cost-effectiveness, and may be easily integrated into composite layers due to its minimal cabling requirements and extremely small profile. The particular frequency-coded configuration enables the suggested sensor to accurately detect and distinguish various structural deformations based on their severity and location.

Transfer Learning Enabled Modeling Paradigm for PVT-aware Circuit Performance Estimation

Designing robust performance models for modern complex digital circuits in the face of rapidly accelerating process variations is a critical yet demanding task. This paper introduces an efficient statistical performance modeling approach for VLSI digital circuits that incurs minimal computational expense. The fundamental concept involves capitalizing on knowledge gained from circuit modeling in one technology node to streamline the modeling process in another. This is achieved by merging previously established statistical models of process technology with a limited set of simulation data from a subsequent process technology through transfer learning. Comprehensive experiments conducted across diverse technology nodes demonstrate that the proposed framework is robust, precise, efficient in data usage, and computationally superior to other cutting-edge performance modeling techniques.

Study on the friction characteristics of a self-lubricating linear compressor using vapor injection{fr}Étude des caractéristiques de frottement d'un compresseur linéaire auto-lubrifié utilisant l'injection de vapeur.

The self-lubricating linear compressor with aerostatic bearings has good prospect for the scenario which has difficulties of oil returning. This study presents a novel oil-free linear compressor and establishes a frictional damping model by using equivalent circuit approach to evaluate the mechanical performance of the compressor. The changes in friction damping characteristics of VISLLC under different piston strokes and injection pressure are analyzed. The flow resistance coefficients within the porous medium and gas gap are obtained by experimental tests and modeling analysis. Simulation results indicate that the equivalent frictional damping coefficient can be reduced by 36.1 % comparing with that of the non-injection and the efficiency can improved the by 17.2 %. The frictional damping coefficient in the porous bearing thickness of 0.9 mm at 600 kPa injection pressure is 3.64 N∙s∙m−1.

Enhanced forest fire evacuation planning using real-time sensor and GPS algorithm

Forest fires are the source of countless fatalities and extreme economic repercussions. The safe evacuation of residents of an area affected by forest fires is the highest priority of local authorities, and finding the most optimal course of action has been a primary research focus for years. Previous studies over several decades have attempted to find an optimal solution using the applications of bug navigation systems, road network reconfiguration, graph traversals, swarm optimization, etc. The author, with the motivation to prevent human casualties at the time of such calamity, presents a novel study which solves the problem in nearly linear time computation, surpassing the performance standards of previous research, and accommodates the unpredictability of the spread of forest fires. This includes a proposal of an algorithm which builds upon the application of Spielman and Teng’s Electrical Circuit Approach to solve for maximum flow in a network and implements this with real-time sensor and Global Positioning System input.

A map neuron with piezoelectric membrane, energy regulation and coherence resonance

The cell membrane has a layered structure, which separates the intracellular and extracellular ions for developing gradient electromagnetic field, and its flexible property enables the capacitance dependence on the shape deformation due to external stimuli. Therefore, piezoelectric membrane can be suitable to describe the biophysical characteristic of cell membrane and equivalent circuit approach becomes important. In this paper, two capacitors are connected via a piezoelectric ceramic and two additive memristive channels are combined to mimic the neural activity response with exact energy description. Furthermore, linear transformation is applied to obtain an equivalent piezoelectric map neuron and energy function is provided to explore the adaptive energy regulation on mode selection in neural activities. Coherence resonance is detected and analyzed. The map neuron can also be considered as an auditory neuron for perceiving acoustic signals and its membrane property is considered from physical aspect.

Polarization insensitive and wideband terahertz absorber using high-impedance resistive material of RuO2

This paper introduces a novel, cost-effective solution designed to achieve large absorption bandwidth within the THz spectrum employing a miniaturized, single-layer metamaterial structure. The designed structure features a single circular ring composed of an ohmic resistive sheet with notably higher sheet resistance than traditional metallic resonators. This distinctive design is implemented on a lossy dielectric polyimide substrate with a backing of metallic gold. Our developed absorbing structure demonstrates the capability to achieve a substantial absorption bandwidth ranging from 3.78 to 4.25 THz, maintaining a consistent absorption rate of over 90%. Moreover, we conducted an analysis to assess its absorption performance under various sheet resistance values within the top layer. Additionally, we characterized its angular stability and polarization insensitivity through oblique incident and polarization angle analysis. Finally, an RLC circuital and interference theory approach is adopted to justify its simulated results. The proposed absorber shows potential for a broad spectrum of applications, encompassing communication, imaging, and diverse integrated circuits operating within the THz band.

Basal forebrain-lateral habenula inputs and control of impulsive behavior.

Deficits in impulse control are observed in several neurocognitive disorders, including attention deficit hyperactivity (ADHD), substance use disorders (SUDs), and those following traumatic brain injury (TBI). Understanding brain circuits and mechanisms contributing to impulsive behavior may aid in identifying therapeutic interventions. We previously reported that intact lateral habenula (LHb) function is necessary to limit impulsivity defined by impaired response inhibition in rats. Here, we examine the involvement of a synaptic input to the LHb on response inhibition using cellular, circuit, and behavioral approaches. Retrograde fluorogold tracing identified basal forebrain (BF) inputs to LHb, primarily arising from ventral pallidum and nucleus accumbens shell (VP/NAcs). Glutamic acid decarboxylase and cannabinoid CB1 receptor (CB1R) mRNAs colocalized with fluorogold, suggesting a cannabinoid modulated GABAergic pathway. Optogenetic activation of these axons strongly inhibited LHb neuron action potentials and GABA release was tonically suppressed by an endogenous cannabinoid in vitro. Behavioral experiments showed that response inhibition during signaled reward omission was impaired when VP/NAcs inputs to LHb were optogenetically stimulated, whereas inhibition of this pathway did not alter LHb control of impulsivity. Systemic injection with the psychotropic phytocannabinoid, Δ9-tetrahydrocannabinol (Δ9-THC), also increased impulsivity in male, and not female rats, and this was blocked by LHb CB1R antagonism. However, as optogenetic VP/NAcs pathway inhibition did not alter impulse control, we conclude that the pro-impulsive effects of Δ9-THC likely do not occur via inhibition of this afferent. These results identify an inhibitory LHb afferent that is controlled by CB1Rs that can regulate impulsive behavior.

A Power Optimization Approach for Large-scale RM-TB Dual Logic Circuits Based on an Adaptive Multi-Task Intelligent Algorithm

Logic synthesis is a crucial step in integrated circuit design, and power optimization is an indispensable part of this process. However, power optimization for large-scale Mixed Polarity Reed-Muller (MPRM) logic circuits is an NP-hard problem. In this article, we divide Boolean circuits into small-scale circuits based on the idea of divide and conquer using the proposed Dynamic Adaptive Grouping Strategy (DAGS) and the proposed circuit decomposition model (CDM). Each small-scale Boolean circuit is transformed into an MPRM logic circuit by a polarity transformation algorithm. Based on the gate-level integration, we integrate small-scale circuits into an MPRM and Boolean Dual Logic (RBDL) circuit. Furthermore, the power optimization problem of RBDL circuits is a multi-task, multi-extremal, high-dimensional combinatorial optimization problem, for which we propose an Adaptive Multi-task Intelligent Algorithm (AMIA), which includes global task optimization, population reproduction, valuable knowledge transfer (VKT), and local exploration to search for the lowest power for RBDL circuits. Moreover, based on the proposed Fast Power Decomposition Algorithm (FPDA), we proposed a Power Optimization Approach (POA) for an RBDL circuit with the lowest power using the AMIA. Experimental results based on Microelectronics Center of North Carolina (MCNC) Benchmark test circuits demonstrate the effectiveness and superiority of the POA compared to state-of-the-art POAes.

Design and analysis of Minkowski fractal shaped metasurface absorber with broadband and polarization-insensitive characteristics using a tunable graphene layer for terahertz applications

The proposed research article’s main goal is to demonstrate a terahertz (THz) broadband absorber for high-speed wireless communication applications. The proposed structure is a compact one and possesses three layers. The ground layer acts as a metal reflector, lossy silicon acts as a dielectric material and finally a graphene layer in the shape of a minkowski fractal acts as a radiating patch for the proposed design. We have chosen a thickness of 5 μm for the lossy silicon which has a dielectric constant of 11.90. The bottom layer of the proposed design contains a good conductive material like gold with a conductivity of 4.561 e+007 s m−1 with a thickness of 0.2 μm. The thickness of a monolayer graphene is one nanometer, and the overall unit cell size of the proposed structure is 12 × 12 μm2. Because of its symmetrical nature, the proposed absorber offers a broad response to both TM and TE modes irrespective of any polarization angle. The proposed absorber can operate in the terahertz frequency range and has achieved two broad frequency bands from 3.34–3.98 THz and 4.6–5.30 THz, with an absorption percentage greater than 90. We can observe peak absorption frequencies at 3.60 THz and 5.04 THz, which exhibit an absorption percentage close to unity. Additionally, we validated the proposed broadband absorber using an equivalent circuit approach and verified it using the ADS tool.

MgAl-LDH nanoflowers as a novel sensing material for high-performance humidity sensing.

This work details a novel application of MgAl-LDH nanoflowers, applied in the fabrication of humidity sensors using quartz crystal microbalance (QCM). An oscillating circuit approach has been utilized to thoroughly investigate the humidity detection characteristics of QCM sensors that are fabricated using MgAl-LDH nanoflowers. The examination encompassed various parameters such as the sensors' response, humidity hysteresis, repeatability, and stability. Experimental results clearly indicate that these MgAl-LDH nanoflower-based QCM sensors exhibit a distinct logarithmic frequency response to varying moisture levels. Notably, the sensitivity of the sensors is intricately tied to the amount of MgAl-LDH nanoflowers utilized during the deposition process. Moreover, these sensors maintain remarkable stability across a wide humidity range spanning from 11% to 97% RH. Additionally, the MgAl-LDH nanoflower-based QCM sensors possess minimal humidity hysteresis and display swift dynamic response and recovery periods, further highlighting their potential for humidity detection applications.

Review of Integrated Gate Driver Circuits in Active Matrix Thin-Film Transistor Display Panels.

Many advanced technologies have been employed in high-performance active matrix displays, including liquid crystal displays, organic light-emitting diode displays, and micro-light-emitting diode displays. On the other side, there exists a strong demand for cost reduction, and it is one of the low-cost schemes for integrating the driver circuit in a panel based on thin-film transistor technologies. This paper reviews the overall concept, operation principles, and various circuit approaches in shift registers for scanning pulse generation. In addition, it deals with the implementation of additional functionalities in gate drivers to support pixel compensation, multi-line driving, in-cell capacitive touch screen, pixel sensing, and adaptive scanning region control.

Enhance controllability of a memristive neuron under magnetic field and circuit approach

Enhance controllability of a memristive neuron under magnetic field and circuit approach

INDIDO: A novel low-power approach for domino logic circuits

Power dissipation in Nanoelectronic circuits at advanced technology nodes is dominated by leakage power dissipation. This is due to an increase in short channel effects in the scaled transistors.The VLSI industry is seeking alternative options to enhance the performance of portable electronic systems by ensuring higher speed and reduced power dissipation. In the ultra-deep submicron (DSM) regime, a new device called the fin-shaped field effect transistor (FinFET) was developed to replace CMOS technology. FinFET, a multi-gate device, significantly reduces power dissipation compared to planer MOS (Metal Oxide Semiconductor ) transistor, but it doesn’t entirely resolve the issue. To further reduce power dissipation in the ultra DSM regime, low power approaches are required. Domino logic, a widely-used dynamic logic, is commonly utilized in high-speed VLSI architectures. In this research work, a novel INput Dependent Inverter DOmino (INDIDO) logic approach for low-power domino logic circuits using FinFET devices is proposed. A comparative analysis between the proposed INDIDO method and the existing approaches is performed for domino logic circuits for various performance metrics at the 16 nm technology node. In this research, various circuits like domino buffer, domino OR, domino AND, domino XOR and domino half adder are designed using the proposed INDIDO approach.The proposed INDIDO FinFET buffer circuit offers significant improvement in energy efficiency and FOM (Figure of Merit) by 53.18% and 82% respectively as compared to conventional FinFET footed domino buffer circuit. Beside this, proposed circuits like INDIDO OR, INDIDO AND, INDIDO XOR and INDIDO Half adder circuit follow the same trend as INDIDO buffer circuit and show better performance parametres in comparison to the existing low power domino approaches as well. In addition to this, the proposed INDIDO buffer circuits are also analyzed for PVT(process voltage and temperature) variability.This whole analysis makes us to conclude that proposed INDIDO approach reduces power dissipation and delay penalty, have high noise tolerance capacity, more immunity against PVT variations and high energy efficiency in comparison to the already existing techniques.

Comparing Numerical and Analytical Methods for Heat Loss Determination of District Heating Systems

Energy efficiency assessment considers the heat losses in district heating systems. For instance, life cycle assessments of such engineering structures require knowledge of the heat losses during their use phase. Therefore, it is essential to have the most accurate knowledge of the heat losses of a district heating system. In this study, three different methods for the determination of specific heat losses for buried preinsulated steel pipes are compared. The first method involves an analytical calculation in accordance with EN 13941, while the second utilizes an equivalent circuit approach. The third method employs finite element analysis. The objective was to evaluate the accuracy of the methods, the achievable range of results, and the effort required to solve the respective calculation algorithms. Therefore, typical 2-dimensional cross sections including different pipe diameters were selected. In situ measurements were not part of this study. Consequently, the analysis centres on the deviation between the methods. All three methods determine the heat loss in both the supply and return pipes. While the analytical calculation method cannot determine temperatures in the soil, the equivalent circuit method can handle more complex tasks and gives detailed results at predefined points in the model. With the finite element method, a high degree of detail can be achieved, but the requirements for solving the algorithms increase. An emerging trend in district heating involves reducing operational temperatures in both new and existing networks. This will change the relation between heat losses and heat delivered to the customers. Subsequently, an increasing interest in the actual heat losses and the precision of calculation is expected within this development. Therefore, it remains essential to evaluate the performance of different models

Transient analysis of the electrochemical noise arising from the stainless steel local anodic events by the equivalent circuit approach

PurposeThis study aims to investigate the individual electrochemical transients arising from local anodic events on stainless steel, to uncover the potential mechanisms producing different types of transients and to derive appropriate parameters indicative of the corrosion severity of such transient events.Design/methodology/approachAn equivalent circuit model was used for the transient analysis, which was performed using a local current allocation rule based on the relative instant cathodic resistance of the coupled electrodes, as well as the kinetic parameters derived from the electrochemical polarization measurement.FindingsThe shape and size of the electrochemical current transients arising from SS 316 L were influenced by the film stability, local anodic dissolution kinetics and the symmetry of the cathodic kinetics between the coupled electrodes, where the ultralong transient might correspond to the propagation of film damage with a slow anodic dissolution rate. The dynamic cathodic resistance during the final stage of transient current growth can serve as a characteristic parameter that reflects the loss of passive film protection.Originality/valueEstimation of the local anodic current trace opens a new way for individual electrochemical transient analysis associated with the charges involved, local current densities and changes in film resistance throughout localized corrosion processes.

Effect of Li2O composition and temperature on the ionic conductivity of lithium-borate-silicate glasses containing gold nanoparticles using electrochemical impedance spectroscopy

This research systematically investigates the conductivity properties of a lithium-borate-silicate glass containing varying amounts of Li2O (30 to 50 mol %) in the presence and absence of a fixed concentration of gold nanoparticles (0.05 M). Three techniques were used to characterize the glass material: Electrochemical Impedance Spectroscopy, X-ray diffraction, and Differential Scanning Calorimetry. Impedance spectra were recorded at temperatures of 100 °C, 140 °C, and 200 °C, and the results were analyzed qualitatively and quantitatively using models based on the equivalent circuit approach. It was observed that below a critical concentration of Li2O, namely 35 mol %, the conductivity behavior exhibits a single relaxation process. However, above the critical concentration, the materials present two relaxation processes associated with changes in morphology. Impedance measurements also evaluate the DC and AC conductivity properties of the glasses. Interestingly, regardless of the morphology, conduction in the glasses appears to be thermally activated, with the conduction mechanism being controlled by polaron hopping in a correlated barrier. There is no evidence suggesting that the gold nanoparticles play a significant role in determining the conduction properties of the glasses, at least within the concentration range studied here.

Modeling the effect of magnetoelectric nanoparticles on neuronal electrical activity: An analog circuit approach.

This paper introduces a physical neuron model that incorporates magnetoelectric nanoparticles (MENPs) as an essential electrical circuit component to wirelessly control local neural activity. Availability of such a model is important as MENPs, due to their magnetoelectric effect, can wirelessly and noninvasively modulate neural activity, which, in turn, has implications for both finding cures for neurological diseases and creating a wireless noninvasive high-resolution brain-machine interface. When placed on a neuronal membrane, MENPs act as magnetic-field-controlled finite-size electric dipoles that generate local electric fields across the membrane in response to magnetic fields, thus allowing to controllably activate local ion channels and locally initiate an action potential. Herein, the neuronal electrical characteristic description is based on ion channel activation and inhibition mechanisms. A MENP-based memristive Hodgkin-Huxley circuit model is extracted by combining the Hodgkin-Huxley model and an equivalent circuit model for a single MENP. In this model, each MENP becomes an integral part of the neuron, thus enabling wireless local control of the neuron's electric circuit itself. Furthermore, the model is expanded to include multiple MENPs to describe collective effects in neural systems.

Exploring Terahertz COMPLEMENTARY METAL OXIDE SEMICONDUCTOR Integrated Circuits: Advancements and Obstacles

The text provides a description of the characteristics of several NMOS and CMOS circuit approaches, as well as an explanation of the limitations associated with each technology. Next, the CMOS domino circuit, a novel form of circuit, is explained. This entails interconnecting dynamic CMOS gates in a manner that enables the activation of all gates in the circuit simultaneously using a single clock edge. Consequently, there is no need for intricate clocking methods, allowing the dynamic gate to operate at its maximum speed. This circuit features a basic mode voltage-controlled oscillator operating at 135 GHz in 80-nm COMPLEMENTARY METAL OXIDE SEMICONDUCTOR, a 405 GHz push-push voltage controller in 38-nm COMPLEMENTARY METAL OXIDE SEMICONDUCTOR with an on-chip patch antenna, a 128 GHz Schottky diode frequency doubler, a 170 GHz Schottky diode detector, a 600 GHz plasma wave detector in 122-nm COMPLEMENTARY METAL OXIDE SEMICONDUCTOR and a 40 GHz phase-locked loop with a frequency doubled output at 110 GHz. Given this and the trends in performance of n METAL OXIDE SEMICONDUCTOR transistors and Schottky diodes produced in complementary metal-oxide semiconductors, we lay out a plan for terahertz COMPLEMENTARY METAL OXIDE SEMICONDUCTOR systems and circuits, highlighting critical challenges that need to be addressed. With the advent of terahertz COMPLEMENTARY METAL OXIDE SEMICONDUCTOR

Innovative circuit training for children 10-12 years old to improve forehand and backhand drive skills

Mastery of forehand and backhand drive skills is crucial for the foundational development of table tennis athletes. This study aims to introduce an engaging training methodology for children aged 10-12 to enhance their table tennis abilities. Utilizing a mixed-methods approach, data were collected through the Delphi technique and repeated measures. Participants included three academic experts, four professional table tennis coaches, and nine young table tennis players. The research employed a questionnaire featuring a rating scale from one to four (very relevant, relevant, somewhat relevant, not relevant) for content validity and a one to three scale for assessing the practicality of the instruments. Data analysis was conducted using Aiken's formula. Results. The innovation in training methodology using the circuit approach to enhance beginner-level forehand and backhand drives in table tennis demonstrated significant effectiveness. The first aspect, alignment of the training concept with objectives, received a validation score of V = 0.952. Similarly, the training movements' relevance to objectives and the modifications introduced both scored V = 0.952. The suitability of the training procedures received a slightly lower score of V = 0.857. A practicality assessment of all components yielded scores exceeding 80%. Conclusion. The circuit training methodology designed for children aged 10-12 significantly improves forehand and backhand drive skills, demonstrating high content validity and practicality. Consequently, this study's findings endorse the circuit training approach as an effective means to enhance table tennis skills among young athletes.