Physical Circuit Research Articles

Fabrication and Characterization of 2-Bit per Capacitor as Functional Structures for Physical Unclonable Function Circuits

Currently, security issues for semiconductor chips are counterfeiting and night shift problems. These factors might lead to insecure supply chains in the automotive industry. This can be avoided by using coating Physical Unclonable Functions (PUFs). The coating can be applied to every semiconductor chip in order to create a unique fingerprint. In this work, a 2-bit key per capacitor for Physical Unclonable Functions is presented for the first time. For this reason, 49 chips on a wafer with 195 metal oxide semiconductor (MOS) capacitors were fabricated. A large and random fluctuation of the capacitances was achieved by using a self-developed layer, which consisted of aluminum particles and spin-on glass. Due to the random variation in size and change in distribution of the particles, the fluctuation of capacitance varied from chip to chip and from wafer to wafer. The achieved large range in capacitance was used to create a 390-bit string out of 195 capacitors. Although the length of the bit string was doubled, the area of the structure remained constant. This led to a more secure PUF with a low error rate of 0.21% and an inter-chip Hamming distance (HD <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">inter</sub> ) of 49%.

Teaching Design of Senior High School Physical Logic Gate Circuit

Teaching Design of Senior High School Physical Logic Gate Circuit

Neuromorphic behaviors of N-type locally-active memristor

Owing to the advantages of high integration, low power consumption and locally active characteristics, locally-active memristor (LAM) has shown great potential applications in neuromorphic computing. To further investigate the neuromorphic dynamics of LAMs, a simple N-type LAM mathematical model is proposed in this work. By analyzing its voltage-current characteristic and small-signal equivalent circuit, a neuron circuit based on the N-type LAM is designed, where a variety of neuromorphic behaviors are successfully simulated, such as “all-or-nothing” behavior, spikes, bursting, periodic oscillation, etc. Moreover, Hopf bifurcation theory and numerical analysis method are used to study the dynamics of the circuit quantitatively. Then, an artificial tactile neuron and its frequency characteristics are presented by using the proposed neuron circuit topology. The simulation results show that when the amplitude of the input signal is lower than the threshold, the oscillation frequency of the output signal of the artificial neuron circuit is positively correlated with the intensity of the input signal, and reaches a maximum value at the threshold. The above frequency characteristics are consistent with those of the exciting state of biological sensory system. Subsequently, if the incentive intensity continues to increase, the oscillation frequency will gradually decrease, corresponding to the protective inhibition behavior. Finally, the physical circuit of the N-type LAM, and artificialneuron circuit are realized. The experimental results accord well with the simulation results and theoreticalanalyses, manifesting the practicability of the N-type LAM model and the feasibility of artificial neuron circuit.

Distributed Hierarchical Control for Fast Frequency Restoration in VSG-Controlled Islanded Microgrids

As microgrids develop rapidly, more inverters are adopted to achieve DC&#x002F;AC or AC&#x002F;DC&#x002F;AC conversion of distributed generators (DGs). The virtual synchronous generator (VSG) control has started to replace the traditional droop control for inverters. In order to restore the frequency to its nominal value, most existing secondary frequency control (SFC) methods are based on frequency measurements. However, while reducing the rate of change of frequency (ROCOF), virtual inertia also slows down the convergence of frequency-based SFC. Therefore, this paper proposes a new distributed hierarchical control for fast frequency restoration. Based on the real-time VSG control at the bottom level, a novel frequency restoration control is designed. The power reference values generated by the proposed control can accelerate the frequency restoration with accurate power sharing. Meanwhile, by designing event-triggering conditions, parallel inverter controllers only need to communicate with neighbors at the event-triggered moments. Simulations have been performed in MATLAB&#x002F;Simulink environment. Furthermore, the proposed control has also been tested on the experiment platform, which contains practical physical circuits and real-time controllers. Both simulation and experiment results verify the effectiveness of the proposed control strategy.

СМАРТ-КОНТРАКТЫ В УПРАВЛЕНИИ ЛОГИСТИКОЙ БИЗНЕС-СИСТЕМ ИНДУСТРИИ 4.0

The problem of managing logistics supply chains in the business processes of interaction of economic entities using smart contracts in economic practice is considered. The objects of the study are the business processes of the movement of commodity-material (physical products) and intangible (digital products) values created by Industry 4.0 factories that carry out activities in the industrial segment of the economy. The purpose of the study is to synthesize an economic management system containing smart contracts in local and global circuits and regulating intra- and inter-company business relations of digital (product development), smart (product production) and virtual (product maintenance) factories. A feature of the regulatory processes applied to the management of economic entities is the deep digitalization of information and communication channels of interaction between factories, through which the mechanism of economic influence on the material and service flows of the logistics movement of products is implemented. The scheme is proposed and the management principle is described, based on cost, time and other criteria and providing end-to-end economic regulation of material, service, financial and information flows that characterize the logistics movement of products in the course of its full life cycle and its individual stages. The novelty of the research results lies in the complementary use in the management system of the advantages of economic regulation of logistics business processes implemented jointly by means of physical and virtual (digital) control circuits.

Cytomorphic Electronic Systems: A review and perspective.

Boltzmann-exponential thermodynamic laws govern noisy molecular flux in chemical reactions as well as noisy subthreshold electron current flux in transistors. These common mathematical laws enable one to map and simulate arbitrary stochastic biochemical reaction networks in highly efficient cytomorphic systems built on subthreshold analog circuits. Such simulations can accurately model noisy, nonlinear, asynchronous, stiff, and non-modular feedback dynamics in interconnected networks in the physical circuits, automatically. The scaling in simulation time for stochastic networks with the number of reactions or molecules is constant in cytomorphic systems. In contrast, it grows rapidly in digital systems, which are not parallelizable. Therefore, cytomorphic systems enable large-scale supercomputing systems-biology simulations of arbitrary and highly computationally intensive biochemical reaction networks that can nevertheless be compiled to them via digitally programmable parameters and connectivity. We outline how cytomorphic systems can be utilized for rapid drug-cocktail formulation and discovery in future pandemics like COVID-19; can simulate networks important in cancer; and can help automate the design of synthetic biological circuits, e.g. a synthetic biological operational amplifier for robust and precise drug delivery. Thus, just as neuromorphic systems have enabled multiple applications in A.I., cytomorphic systems will enable multiple applications in biology and medicine.

Dissipativity analysis of negative resistance circuits

This paper deals with the analysis of nonlinear circuits that interconnect passive elements (capacitors, inductors, and resistors) with nonlinear resistors exhibiting a range of negative resistance. Active elements are necessary to design physical circuits that switch and oscillate. We generalize the classical passivity theory of circuit analysis to develop a port interconnection theory for such non-equilibrium behaviors. The approach closely mimics the classical methodology of (incremental) dissipativity theory, but with dissipation inequalities that combine signed storage functions and signed supply rates to account for the port interconnection of passive and active elements.

A Physically Inspired Equivalent Neural Network Circuit Model for SoC Estimation of Electrochemical Cells

Battery Management System (BMS) design for Lithium-ion batteries State of Charge (SoC) prediction has a crucial role in Electric Vehicles (EVs) and smart grids development. The need to design compact, light and fast devices requires finding a suitable trade-off between effectiveness and efficiency. In the literature, it is well emphasized that the application of electrochemical-based methods such as the Pseudo-Two-Dimensional (P2D) model is computationally prohibitive and requires significant simplifications. Conversely, plain Equivalent Circuit Models (ECM) are too simple and unable to represent the cell dynamics. The application of an Ensemble Neural Network (ENN) as Equivalent Neural Network Circuit (ENNC) emerged as a promising solution able to synthesize expressive and computationally efficient models. Indeed, with the support of a suitable dataset, an ENN can be configured to represent a given ECM, modeling each lumped parameter through an assigned Neural Network (NN). Accordingly, the ENNC system is able to keep a physical description of the battery cell while approximating the non-linear dynamic of each component. The paper proposes a novel ENNC battery named Physical Inspired-Equivalent Neural Network Circuit (PI-ENNC) whose ensemble architecture relies on a fractional-order Extended Single Particle (ESP) Lithium-ion cell formulation. The PI-ENNC is designed to approximate the ESP transfer functions referred to the ohmic effects, the electrolyte diffusion and the non-uniform charge distribution in the cell. The proposed model has been tested with three publicly available datasets, investigating the model behavior according to two different training strategies and with different input configurations. In order to prove its effectiveness, results have been compared with a simpler version proposed in a previous work. Results highlight the effectiveness of PI-ENNC in SoC prediction, underlining the importance of designing an ENN architecture that leverages on equations and constraints that reflect the physical phenomena of the cell.

Design and testing of 1 phase semi-controlled rectifier circuit (experiment scale): a part of green laboratory project

This paper discussed design and testing of one (1) phase semi-controlled full wave rectifier circuit (experiment scale) as a part of green laboratory project. The research method was divided by two stages: design and testing. The design stage included: component selection and calculation, conceptual design and circuit physical implementation. The three main components included 2 diodes, 2 thyristors (SCR), resistive (R) and inductive (L) load with varying values. The testing stage was physical rectifier circuit operation with R (220; 580; 1,500 ohm) and R-L (L=2.37 H) load. The voltage waveform, voltage and current were observed during this stage. The testing results (voltage and current) in rms value were compared with theoretical calculation for validation. The testing results showed that the rectifier circuit working optimally. The testing results were differed by small percentage with theoretical calculation. The output voltage was differed by 1.085%. The output current for R and R-L load were differed by 4.590% and 6.457%, respectively.

Filtering Antennas: Design Methods and Recent Developments

With wireless communication technologies continually and rapidly developing, RF front-end systems are experiencing a profound evolution toward the goal of highly integrated and miniaturized RF front ends with improved performance. Traditionally, passive components in the RF front end, such as filters, antennas, and duplexers, have been designed individually and cascaded through a 50-Ω interface. This inevitably leads to bulky physical dimensions and complex circuits, high insertion loss, and signal distortion, especially at the band edges. In multiband or multistandard communication systems, multiple operating bands of the base station antenna are normally achieved using several separate subarrays operating at different frequencies, which can cause serious interference among different bands for various services due to the limited space on the antenna platform. Highly integrated multifunctional RF front ends would provide a high-efficiency solution to those advanced and miniaturized wireless systems. As the key components in any RF front-end system, the integration of filters and antennas can significantly improve the frequency selectivity and bandwidth; stability of the in-band gain, out-of-band rejection, and system efficiency. They have therefore received much research interest and opened up a broad avenue for antenna R&D in recent years.

Analysis and design of diode physical limit bandwidth efficient rectification circuit for maximum flat efficiency, wide impedance, and efficiency bandwidths

Generally, a conventional voltage doubler circuit possesses a large variation of its input impedance over the bandwidth, which results in limited bandwidth and low RF-dc conversion efficiency. A basic aspect for designing wideband voltage doubler rectifiers is the use of complex matching circuits to achieve decade and octave impedance and RF-dc conversion efficiency bandwidths. Still, the reported techniques till now have been accompanied by a large fluctuation of the RF-dc conversion efficiency over the operating bandwidth. In this paper, we propose a novel rectification circuit with minimal inter-stage matching that consists of a single short-circuit stub and a virtual battery, which contributes negligible losses and overcomes these existing problems. Consequently, the proposed rectifier circuit achieves a diode physical-limit-bandwidth efficient rectification. In other words, the rectification bandwidth, as well as the peak efficiency, are controlled by the length of the stub and the physical limitation of the diodes.

Duality-Derived Models of High-Speed Electromagnetic Valves

The article analyzes a high-speed solenoid valve (HSV) whose core and moving armature are massive elements characterized by strong eddy currents, hysteresis, and saturation. The feedback control employed in obtaining a predetermined nonsinusoidal current in the core coil necessitates the use of a high-frequency pulsewidth modulation (PWM)-like voltage with parameters varying in a manner unknown in advance during the uninterrupted transient. In view of the known difficulties in using finite-element solvers, physical Cauer circuits are found to be a reliable engineering alternative. The use of the duality transformation is proposed to obtain a pure electric model of the core and armature. As a preliminary result, it is found that a threefold reduction in eddy-current loss is achieved by using the slotted core. The results obtained with the model are in a reasonable agreement with the experimental magnetizing current and the armature movement during successive valve operations.

New Bursting Patterns in the Lü System Driven by Orthogonal Parametric Excitation and External Excitation

Compared with the general nonlinear system, multi-timescale system has complex dynamical characteristics of bursting oscillations, which has received extensive attention. This paper aims to show and study the bursting oscillations and bifurcation phenomena in the Lü systems driven by orthogonal parametric excitation and external excitation. By using the fast–slow analysis, we were able to get two different fast subsystems corresponding to different bifurcation diagrams when the slow variable increased and decreased. Several novel bursting modes have been discovered, namely, delayed supHopf/cascaded with PD and IPD/Fold/cascaded with PD and IPD/supHopf-Fold bursting, delayed supHopf/supHopf/Fold-Fold bursting and delayed supHopf/cascaded with PD and IPD/supHopf-Fold bursting. Finally, a simulation circuit of the multi-timescale system is established in Multisim, and a real physical circuit is also built. The experimental results effectively verify the research results.

Power module stray inductance extraction: Theoretical and experimental analysis

We propose a stray inductance extraction method on power modules of the few-kilovolts/several-hundred-amperes class using only low voltages and low currents. The method incorporates a double-pulse generator, a level shifter, a switching device, and a load inductor. The conventional approach generally requires a high voltage of more than half the power module's rated voltage and a high current of around half the rated current. In contrast, the proposed method requires a low voltage and low current environment regardless of the power module's rated voltage because the module is measured in a turn-off state. Both theoretical and experimental results are provided. A physical circuit board was fabricated, and the method was applied to three commercial power modules with EconoDUAL3 cases. The obtained stray inductance values differed from the manufacturer-provided values by less than 1.65 nH, thus demonstrating the method's accuracy. The greatest advantage of the proposed approach is that high voltages or high currents are not required.

Symmetry enriched phases of quantum circuits

Quantum circuits consisting of random unitary gates and subject to local measurements have been shown to undergo a phase transition, tuned by the rate of measurement, from a state with volume-law entanglement to an area-law state. From a broader perspective, these circuits generate a novel ensemble of quantum many-body states at their output. In this paper, we characterize this ensemble and classify the phases that can be established as steady states. Symmetry plays a nonstandard role in that the physical symmetry imposed on the circuit elements does not on its own dictate the possible phases. Instead, it is extended by dynamical symmetries associated with this ensemble to form an enlarged symmetry. Thus, we predict phases that have no equilibrium counterpart and could not have been supported by the physical circuit symmetry alone. We give the following examples. First, we classify the phases of a circuit operating on qubit chains with Z2 symmetry. One striking prediction, corroborated with numerical simulation, is the existence of distinct volume-law phases in one dimension, which nonetheless support true long-range order. We furthermore argue that owing to the enlarged symmetry, this system can in principle support a topological area-law phase, protected by the combination of the circuit symmetry and a dynamical permutation symmetry. Second, we consider a Gaussian fermionic circuit that only conserves fermion parity. Here the enlarged symmetry gives rise to a U(1) critical phase at moderate measurement rates and a Kosterlitz–Thouless transition to area-law phases. We comment on the interpretation of the different phases in terms of the capacity to encode quantum information. We discuss close analogies to the theory of spin glasses pioneered by Edwards and Anderson as well as crucial differences that stem from the quantum nature of the circuit ensemble.

Learning to Tune a Class of Controllers with Deep Reinforcement Learning

Control systems require maintenance in the form of tuning their parameters in order to maximize their performance in the face of process changes in minerals processing circuits. This work focuses on using deep reinforcement learning to train an agent to perform this maintenance continuously. A generic simulation of a first-order process with a time delay, controlled by a proportional-integral controller, was used as the training environment. Domain randomization in this environment was used to aid in generalizing the agent to unseen conditions on a physical circuit. Proximal policy optimization was used to train the agent, and hyper-parameter optimization was performed to select the optimal agent neural network size and training algorithm parameters. Two agents were tested, examining the impact of the observation space used by the agent and concluding that the best observation consists of the parameters of an auto-regressive with exogenous input model fitted to the measurements of the controlled variable. The best trained agent was deployed at an industrial comminution circuit where it was tested on two flow rate control loops. This agent improved the performance of one of these control loops but decreased the performance of the other control loop. While deep reinforcement learning does show promise in controller tuning, several challenges and directions for further study have been identified.

Logic Locking in Single Flux Quantum Circuits

The hardware security of RSFQ circuits has become an issue of growing importance for prospective exascale computing systems. Hardware security in RSFQ circuits is particularly relevant to large scale data centers operating with sensitive information. The number of fabrication facilities for superconductive niobium-based technology is limited, and the supply chain for distributing fabricated circuits can be compromised. Logic locking is widely used in modern CMOS circuits to enhance security by masking the functionality of the circuit using a secret key. If an attacker possesses a physical circuit secured by logic locking, the attacker would be unable to determine the intended function. In this paper, a novel methodology for logic locking is proposed for SFQ circuits. Mutual inductances are used to apply additional currents to some or all of the logic gates. These currents behave as keys to access the functionality of the SFQ logic elements. In the proposed technique, only after an additional correct current is applied to all of the locked gates will the circuit produce the proper output. By using inductors with a positive and negative mutual inductance connected to the internal inductances of the gates, the range of current required to unlock a secured circuit is greatly narrowed. In this work, the operation of this proposed logic locking technique is demonstrated using modified SFQ OR gates to enable security while maintaining proper functionality. Less than 4% area overhead is achieved.

The deep-DRT: A deep neural network approach to deconvolve the distribution of relaxation times from multidimensional electrochemical impedance spectroscopy data

Electrochemical impedance spectroscopy (EIS) is an experimental technique ubiquitously used to study electrochemical systems. However, conventional EIS data interpretation through physical and equivalent circuit models is challenging because physical models are problem-specific, and equivalent circuits are often just lumped-element analogs lacking physical meaning. The distribution of relaxation times (DRT) has emerged as a complementary approach to resolve these issues. One drawback of conventional DRT deconvolution is that the EIS data is understood to be (only) a function of frequency (i.e. 1D data) and deconvolved accordingly. This work proposes a novel deconvolution method based on deep neural networks (DNNs), allowing the analysis of multidimensional EIS spectra to bridge data dependency on both frequencies and experimental conditions. Two particularly appealing traits of the deep-DRT method developed in this article are that neither regularization nor specific spacing on the state variables defining the experiment are required. Leveraging DNN to examine complex EIS spectra and their dependence on experimental conditions, this work opens a new research direction in the area of EIS analysis and DRT deconvolution.

Activity-aware prediction of Critical Paths Aging in FDSOI technologies

Modern CMOS technologies such as FDSOI are affected by severe aging effects that do not only depend on physical issues related to nanoscale technologies, but also on the circuit environment and its run-time activity. Therefore it is extremely difficult to reliably establish a-priori guard bands for Critical Path estimations, usually leading to both large delay penalties (and therefore loss of performances) or too short operating lifetime. In this paper, we propose an approach that uses Machine Learning techniques to obtain reliable predictions of the aging of the Near Critical Paths. Starting from a limited set of measurements and simulation data, our framework is able to accurately estimate Critical Path delay degradation in time depending on physical parameters, environment conditions and circuit activity. Further to that, the corresponding regression models are applied to obtain dynamic aging-aware Operating Performance Point selection strategies.

Comparison of Male Adolescents' Physical Fitness Using Physical Activity Promotion System and Circuit Exercise Program.

The purpose of this study is to compare the physical fitness level of adolescents through a physical fitness assessment and a circuit exercise program. A total of 142 middle school students participated. Physical education class consists of a physical fitness assessment, namely, physical activity promotion system (PAPS), and a circuit exercise program. The PAPS measurements include endurance, flexibility, strength, power, body mass index, and total score. The circuit exercise program consists of twist spine, hand walking, rolling squat, cross knee up, jumping and squat, and level-up pacer. First, there were significant differences in PAPS and circuit exercise program according to grade. Second, there was a significant difference in the results of the circuit exercise program according to the level of each physical fitness variable of PAPS. Third, significant correlations were found in the results of the PAPS and circuit exercise program. The use of a circuit exercise program to measure fitness for adolescents can offer convenience for school physical education and be of value as a measure of physical fitness for adolescents. In addition, the circulatory exercise programs used in this study are thought to be applicable to exercise prescriptions to improve endurance, strength, and BMI.