Simple Circuit Research Articles

The effect of guided inquiry-based virtual and physical laboratories on science learning outcomes

ABSTRACT Background Developments in technology have rapidly advanced the variety, features, and applications of virtual labs (VL) in teaching. However, it is debated whether VL can be used instead of physical labs (PL) because more is needed to address the tactile and sensory senses and to gain motor skills that PL has. While many studies have compared VL and PL, few have examined the impact of these laboratories using contemporary learning methods. Purpose This study aims to comparatively examine the effects of guided inquiry-based learning of electrical circuits and Ohm’s law in VL and PL on the conceptual understanding, science process skills, problem-solving, and views of pre-service science teachers (PST). Sample The study was carried out with 26 PSTs studying in the first year of a science teaching program at a state university in Türkiye. Design and Methods The study is in a true experimental design with the pretest-posttest control group. The matched pairs of PSTs were randomly assigned to the VL (n = 13) and PL (n = 13). Three-tier simple electrical circuits concept test, science process skill test in multiple formats, problem-solving inventory, and open-ended questionnaire were used for completing the data collection process. Results Results revealed that guided inquiry-based VL and PL were equally effective in increasing PSTs’ conceptual understanding. While VL is more effective in completing knowledge gaps, PL is more effective in developing science process skills. Neither has a significant effect on problem-solving. Conclusions Both VL and PL have advantages and disadvantages in terms of the types of learning outcomes. Consequently, guided inquiry-based VL and PL are recommended to use in science teaching as complements to each other.

Ultrathin Transistors and Circuits for Conformable Electronics.

Adapting electronics to perfectly conform to nonplanar and rough surfaces, such as human skin, is a challenging task, which could open up new applications in fields of high economic and scientific interest, ranging from health to robotics, human-machine interface, and Internet of Things. The key to success lies in defining a technology that can lead to ultrathin devices, exploiting ultimately thin materials, with high mechanical flexibility and excellent electrical properties. Here, we report a hybrid approach for the development of high-performance, ultrathin and conformable electronic devices, based on the integration of semiconducting transition metal dichalcogenides, i.e., MoS2, with organic gate dielectric material, i.e., polyvinyl formal (PVF) combined with inkjet printed PEDOT:PSS electrodes. Through this novel approach, transistors and simple digital and analogue circuits are fabricated by a sequential stacking of ultrathin (nanometer) layers on a few micrometers thick polyimide substrate, which guarantees the high flexibility mandatory for the targeted applications.

Distinguishing between topological isomorphism and topological equivalence of power electronic converters

In the process of deducing the topology of power electronic converters, scholars often use topological equivalence or topological isomorphism to identify topologies with different structures but the same performance to avoid repeated research. However, the connotations of topological equivalence and topological isomorphism are not the same. This paper will clarify the method for accurately identifying topologies with the same performance by distinguishing the differences and connections between the two. First, it is derived that the necessary condition for topological isomorphism is that the determinants of their adjacency matrices are equal; then, it is derived that the necessary and sufficient conditions for topological equivalence are that their component composition is the same and their simple circuits correspond one to one; finally, the above two conditions are analyzed from the perspective of topological subgraphs, and it is found that topological isomorphism is a sufficient but not necessary condition for topological equivalence, and topological equivalence is a necessary and sufficient condition for the same topological performance. Therefore, in practice, equivalence rather than isomorphism should be used to identify topologies with the same performance. This paper verifies the correctness of the theoretical analysis through a case analysis. In addition, this paper also introduces a method for automatically determining equivalent topologies based on the depth-first search algorithm to help quickly and accurately identify converter topologies with the same performance.

Evolution of and Perspectives on Differential‐Pair‐Based CMOS Variable Gain Amplifiers With Linear‐in‐Decibel Gain Control: A Tutorial

ABSTRACTA variable gain amplifier (VGA) is an essential building block used in the automatic gain control (AGC) loop to provide a continuous, adjustable gain for the signal strength. To maintain the stability and consistency of the AGC loop, it is necessary to ensure that the gain of the VGA has an accurate dB‐linear characteristic. This tutorial provides a detailed overview of the development of dB‐linear VGAs based on differential pair structures over recent years. We categorize various VGA cells based on differential pair structures, analyze their operating principles, and explain the key features of each topology. Based on observation and extraction of the dB‐linear implementation schemes used by these VGAs, we summarize three basic methods for achieving dB‐linear gain control. We also discuss specific methods for realizing the exponential function, using a true exponential and a mathematical approximation, and present the different types of approximation functions adopted in the works described here. Considerations in regard to the tuning range, gain error, bandwidth, linearity, process‐temperature robustness, and circuit simplicity are also discussed. Finally, we draw comparisons and give perspectives for future dB‐linear VGAs.

Using Bifluxon Tunneling to Protect the Fluxonium Qubit

Encoding quantum information in quantum states with disjoint wave-function support and noise-insensitive energies is the key behind the idea of qubit protection. While fully protected qubits are expected to offer exponential protection against both energy relaxation and pure dephasing, simpler circuits may grant partial protection with currently achievable parameters. Here, we study a fluxonium circuit in which the wave functions are engineered to minimize their overlap while benefiting from a first-order-insensitive flux sweet spot. Taking advantage of a large superinductance (L∼1 μH), our circuit incorporates a resonant tunneling mechanism at zero external flux that couples states with the same fluxon parity, thus enabling bifluxon tunneling. The states |0⟩ and |1⟩ are encoded in wave functions with parities 0 and 1, respectively, ensuring a minimal form of protection against relaxation. Two-tone spectroscopy reveals the energy-level structure of the circuit and the presence of 4π quantum-phase slips between different potential wells corresponding to m=±1 fluxons, which can be precisely described by a simple fluxonium Hamiltonian or by an effective bifluxon Hamiltonian. Despite suboptimal fabrication, the measured relaxation (T1=177±3 μs) and dephasing (T2E=75±5 μs) times not only demonstrate the relevance of our approach but also open an alternative direction toward quantum computing using partially protected fluxonium qubits. Published by the American Physical Society 2024

Multibarrier Collaborative Modulation Devices with Ultra-High Logic Operation Density.

The demands for highly miniaturized and multifunctional electronics are rapidly increasing. As scaling-down processes of transistors are restricted by physical limits, reconfigurable electronics with switchable operation functions for different tasks are developed for higher function integration based on split- or vertical-dual-gate structures. To promote the present reconfigurable electronics and exceed the function integration limit, the critical issue is to integrate complex operations into simple circuit forms by establishing more control dimensions. This work proposes a multibarrier collaborative (MBC) modulation architecture to increase the control dimension by multiple forms of potential barriers and achieves combinational and reconfigurable logic operations by a single MBC device. The MBC architecture exhibits ultrahigh logic operation density, including 58.8% area reduction for multiplexer operations and 71.4% area reduction for 4-logic reconfigurable operations. Besides, a hardware security module composed of 4 MBC devices implementing 8 types of logic operations is demonstrated. This work reveals an effective design of function integration for next-generation electronics.

Simple integrated circuit reverse-engineering with deep learning: A proof of concept for automating die-polygon-capturing

The purpose of this research is to demonstrate the feasibility of automating ‘die-polygon-capturing’, an economical yet still labor-intensive technique for circuit extraction during the reverse-engineering of simple integrated circuits. As microchip designs become increasingly diverse with the ongoing trend of using application-specific integrated circuits, and considering the importance of reverse-engineering these components, die-polygon-capturing is set to play a more critical role in the future. Due to the apparent absence of prior scientific publications and limited automation efforts in this area, this paper presents a proof of concept for automating the die-polygon-capturing technique, thereby addressing a notable gap in the existing literature, with an overarching goal of reducing the labor-intensity of die-polygon-capturing. Our method consists of training deep neural networks on variations of a dataset and evaluating their segmentation capabilities of various layers and connections in an integrated circuit. Given the limited accessibility to high-quality labeled datasets, the dataset used for this research consists of two images of a single microchip, the AMD 9085D. We implemented a data augmentation process that expanded this dataset to as many as 4872 images. The experiment’s results proof the automation’s feasibility, demonstrating high scores on Intersection over Union and F-beta evaluation metrics. However the primary conclusion drawn is the need for focus on generalizability towards other types of microchips in order to effectively automate this technique for circuit extraction.

Investigation on oxygen vacancy regulation mechanism of ZnO gas sensors under temperature modulation mode to distinguish alcohol homologue gases

Homologous gases are difficult to be detected due to their similar chemical properties, especially for metal oxide semiconductor gas sensors whose selectivity has always been a significant challenge. Dynamic temperature modulation method with periodically changing operating temperature was used to detect alcohol homologous gases. However, there are still problems with the deviceization of heating control circuits. In this paper, dynamic temperature modulated method which needs a simple heating circuit is used to distinguish alcohol homologous gases in combination with oxygen vacancy modulation of ZnO gas sensors. Ethyl alcohol, n-propyl alcohol, isopropyl alcohol and n-butyl alcohol were measured by ZnO gas sensors with different oxygen vacancies content ratios under rectangular wave with a voltage range of 2–6 V. It was found that the greatest difference among the response curves when the material calcined at 600°C which has the largest oxygen vacancies content ratio. Finally, the recognition of the four homologue gases measured by ZnO-600 sensor was achieved by dynamic time warping and the recognition accuracy is 99.33 %.

Terminal differentiation precedes functional circuit integration in the peduncle neurons in regenerating Hydra vulgaris

Understanding how neural circuits are regenerated following injury is a fundamental question in neuroscience. Hydra is a powerful model for studying this process because it has a simple neural circuit structure, significant and reproducible regenerative abilities, and established methods for creating transgenics with cell-type-specific expression. While Hydra is a long-standing model for regeneration and development, little is known about how neural activity and behavior is restored following significant injury. In this study, we ask if regenerating neurons terminally differentiate prior to reforming functional neural circuits, or if neural circuits regenerate first and then guide the constituent naive cells toward their terminal fate. To address this question, we developed a dual-expression transgenic Hydra line that expresses a cell-type-specific red fluorescent protein (tdTomato) in ec5 peduncle neurons, and a calcium indicator (GCaMP7s) in all neurons. With this transgenic line, we can simultaneously record neural activity and track the reappearance of the terminally-differentiated ec5 neurons. Using SCAPE (Swept Confocally Aligned Planar Excitation) microscopy, we monitored both calcium activity and expression of tdTomato-positive neurons in 3D with single-cell resolution during regeneration of Hydra’s aboral end. The synchronized neural activity associated with a regenerated neural circuit was observed approximately 4 to 8 hours after expression of tdTomato in ec5 neurons. These data suggest that regenerating ec5 neurons undergo terminal differentiation prior to re-establishing their functional role in the nervous system. The combination of dynamic imaging of neural activity and gene expression during regeneration make Hydra a powerful model system for understanding the key molecular and functional processes involved in neural regeneration following injury.

A simple electrical circuit model for impedance spectroscopy with cochlear implant electrodes

Although cochlear implants are an established method of restoring hearing, they can have limitations such as increasing current spread and decreasing frequency resolution due to tissue growth around the electrode array. Impedance measurements in cochlear implants have become a versatile tool for intra- and post-operative diagnosis of cochlear implant state. However, most clinical devices use current pulse stimulation already available in the implants and analyze the voltage response in the time-domain and spread along the cochlea. To use the full potential of impedance spectroscopy in differentiating cell types, measurement over an extended frequency range is required. This study presents a simple electrical equivalent circuit for impedance spectroscopy with cochlear implants in a 2-pole configuration. The electrical equivalent circuit describes the electrical properties of the cochlear implant electrode and its electrochemical behavior at the electrode-electrolyte interface by comparing two non-linear bilayer models, Cole-Cole and Schwan-Faraday. The model is validated for four cochlear implant electrodes from four different manufacturers (MED-EL FlexSoft, AB HiFocus SlimJ, Oticon EVO, Cochlear Nucleus CI622) characterized by impedance spectroscopy between 5 Hz and 13 MHz. In the future, this electrical equivalent circuit may help to extract parameters for differentiating cell types around the cochlear implant electrode from an impedance spectroscopic measurement.

Synaptic weight dynamics underlying memory consolidation: Implications for learning rules, circuit organization, and circuit function

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We provide two biologically plausible implementations for this reset that propose functional roles in stabilizing consolidation for core elements of the cerebellar circuit.

The Embedded System of Battery Charging with Constant Current System using Microcontroller and IC LM338

The battery has the function of an electrical energy storage system. However, charging the battery is prone to damage. Damage to the battery is often caused by overcharging. The time used during the battery charging process is an important factor that must be considered when charging. thus, efficient battery charging is important and very necessary to avoid damage. An another important aspect of a battery charging method is the current and voltage values supplied during its charging process. The presence of inappropriate values damages and reduce battery life, while the maintenance of a constant current is an important charging process step that extends service life. This research is expected to create a safe and optimal battery charging system with a simple low-cost circuit based on constant current by utilizing the LM388 Integrated Circuit (IC) regulator. This study discusses a 12 V battery charging system with monitored and controlled constant current using an R-Shunt sensor. Voltage monitoring while charging was carried out with voltage sensors using a constant current of 0.1 to 1.3 Ampere. Furthermore, voltages and currents were displayed through a Liquid Crystal Display (LCD) screen controlled with Arduino Uno during battery charging. The measurement results showed that the circuit reached voltages and currents of 14.07 V and 0.19 A respectively for a charge duration of 8 hours.

Exploiting Spatial Ionic Dynamics in Solid-State Organic Electrochemical Transistors for Multi-Tactile Sensing and Processing.

The human nervous system inspires the next generation of sensory and communication systems for robotics, human-machine interfaces (HMIs), biomedical applications, and artificial intelligence. Neuromorphic approaches address processing challenges; however, the vast number of sensors and their large-scale distribution complicate analog data manipulation. Conventional digital multiplexers are limited by complex circuit architecture and high supply voltage. Large sensory arrays further complicate wiring. An 'in-electrolyte computing' platform is presented by integrating organic electrochemical transistors (OECTs) with a solid-state polymer electrolyte. These devices use synapse-like signal transport and spatially dependent bulk ionic doping, achieving over 400 times modulation in channel conductance, allowing discrimination of locally random-access events without peripheral circuitry or address assignment. It demonstrates information processing from 12 tactile sensors with a single OECT output, showing clear advantages in circuit simplicity over existing all-electronic, all-digital implementations. This self-multiplexer platform offers exciting prospects for circuit-free integration with sensory arrays for high-quality, large-volume analog signal processing.

Simple reciprocal electric circuit exhibiting exceptional point of degeneracy

Simple reciprocal electric circuit exhibiting exceptional point of degeneracy

Biological Cell Response to Electric Field: A Review of Equivalent Circuit Models and Future Challenges.

Biological cells, characterized by complex and dynamic structures, demand precise models for comprehensive understanding, especially when subjected to external factors such as electric fields (EF) for manipulation or treatment. This interaction is integral to technologies like pulsed electric fields (PEF), inducing reversible and irreversible structural variations. Our study explores both simplified and sophisticated equivalent circuit models for biological cells under the influence of an external EF, covering diverse cell structures from single- to double-shell configurations. The paper highlights challenges in circuit modeling, specifically addressing the incorporation of reversible or irreversible pores in the membrane during external EF interactions, emphasizing the need for further research to refine technical aspects in this field. Additionally, we review a comparative analysis of the performance and applicability of the proposed circuit models, providing insights into their strengths and limitations. This contributes to a deeper insight of the complexities associated with modeling biological cells under external EF influences, paving the way for enhanced applications in medical and technological domains in future.&#xD.

A Novel Sinusoidal Oscillator Using Single Voltage Differencing Buffered Amplifier

In this paper, a voltage differencing buffered amplifier (VDBA)-based second-order sinusoidal oscillator (SO) configuration, which provides voltage output at low impedance, is proposed. The circuit employs single VDBA, three resistors and two grounded capacitors, which presume its easy monolithic integration with preferred circuit simplicity. The nonidealities of VDBA due to parasitic and tracking errors are taken into consideration to study the nonideal behavior of proposed SO. Mathematical modeling of phase noise is computed in the paper. Active and passive sensitivities are calculated for the proposed configuration and are found to be less than unity rendering circuit insensitive to component variations followed by phase noise study. The functionality of the proposed topology is validated through cadence virtuoso ADE spectre tool at 180-nm technology node. Experimental verification is executed through commercially available ICs AD844 by good results. The total harmonic distortion (THD) is found to be below 3.5%. The observed frequency of oscillation is found to be in close agreement with the theoretical values. The PVT and Monte Carlo statistical analyses are also carried out to confirm the sensitivity of the proposed SO.

A Flyback Converter with a Simple Passive Circuit for Improving Power Efficiency

This paper proposes an effective method to improve the power efficiency of the flyback converter in the continuous conduction mode (CCM). The proposed converter uses a simple passive circuit to reduce the switching power losses. The current through the output diode can be shifted to a new branch where one diode, one inductor, and one auxiliary winding of the transformer are included. The output diode current can be reduced to zero for the zero-current switching of the output diode. The additional inductor is used to control the changing rate of the additional diode current to reduce the reverse-recovery current. Keeping the simplicity of the passive method, the proposed converter improves the power efficiency compared to the conventional converter. The circuit configuration and the operation principle are described. The design considerations are presented, including the simulation verification. The experimental results for a 45 W prototype are discussed to evaluate the performance of the proposed converter. The proposed converter has achieved a power efficiency of 93.5% for the rated load condition, improving the power efficiency. The applications of the proposed converter are also discussed for the future research directions.

High-Precision Angle Measurement for Position Control in Industrial Drives Systems with Shaft Resolver

Resolver is a shaft angle sensor, which is mechanically connected to the motor shaft and operates according to the induction principle. A high frequency sinusoidal signal is applied to its input and produces two signals in the form of sine and cosine at its output. The output signals include the angle information of the motor shaft. Using these signals, the shaft angle of the motor is determined. In the study, a sinusoidal signal at the 5 kHz frequency was applied to an input resolver as the conventional method. After, the fact that applied to two PWM signals which has a duty ratio d=0.5 at 20 kHz and 100 kHz frequency is proposed as different from the conventional method. These PWM signals are the input signals of the resolver. Thus, complex equipment will not be needed to produce the high frequency sinusoidal signal. With only a simple amplifier circuit, a high frequency input signal will be produced. More sensitive angle information will be obtained with high frequency stimulation. A simulation study of conventional and proposed methods has been performed in MATLAB/Simscape environment. As a result of the simulation study, the information on the motor angle obtained from both methods was compared by using figures and details. By increasing the applied PWM signal from 20 kHz to 100 kHz, measurement errors related to shaft angle change were minimized and more precise position information was obtained.

Exploring electricity in early childhood education: A 5E-based learning approach

This paper presents a teaching scenario designed to introduce preschool children to electricity, structured around the 5E instructional model (Engage, Explore, Explain, Elaborate, Evaluate). The study involves 18 children from an urban kindergarten with diverse backgrounds and learning needs. Over four weeks, children engage in interactive activities to understand electrical devices, electric current, static electricity, conductors, insulators, electricity generation, and safety. The curriculum integrates interdisciplinary learning, combining literacy and science, and uses hands-on experiments and digital tools to enhance engagement. Activities include constructing simple circuits, experimenting with static electricity, and role-playing. Emphasis is placed on practical applications and safety. Findings highlight the effectiveness of a constructivist approach, where children build understanding through exploration. The study underscores the need for resources, teacher preparedness, and inclusive strategies to address diverse learning needs. This scenario provides insights into effective early childhood science education, emphasizing the potential to build a strong foundation for future learning and curiosity in young children.

Coherence resonance in a memristive map neuron and adaptive energy regulation

Involvement of memristive term and additive physical variables including magnetic flux and charge can enhance the physical description of the biophysical neurons. Neural circuits coupled with memristors can be built and tamed to mimic the intrinsic biophysical characteristics and dynamical properties of biological neurons, and these memristive oscillator models are effective in predicting the mode transition in neural activities and self-organization in collective electric behaviors of neural networks. Any proposal of memristive map neurons requires reliable physical description. For example, the energy definition and self-adaptive working mechanism are crucial to verify the reliability of memristive maps. A capacitive variable is useful to describe the membrane potential, while the complexity of ion channels requires careful evaluation and description by using inductive variables relative to the electromagnetic field. In this work, a charge-controlled memristor is connected to an inductor in series for building a hybrid ion channel, and then a capacitor and a nonlinear resistor are combined to couple the ion channel. As a result, a simple memristive neural circuit is designed to discern the inner effect of electric field and magnetic field synchronously. The energy function is defined and verified with theoretical proof. Furthermore, a linear transformation is applied to convert this memristive neuron into a memristive map with an exact energy description, in which its dynamics and mode transition will be controlled by an adaptive law when its energy is beyond the threshold. Additive noise is imposed to induce coherence resonance, which can be detected by using the statistical analysis and average value for Hamilton energy function during changes in noise intensity. This scheme provides guidance for energy definition in memristive maps and the intrinsic energy regulation mechanism in neural activities is explained from physical and dynamical aspects.