Journal of Computational Electronics最新文献

In the present paper, a simple qualitative model is proposed to study the effect of dimension and crystal structure on the energy band gap of semiconducting nanomaterials. The energy band gap variation is studied for nanoparticles, nanowires and thin films. The model takes into account the crystal structure and to incorporate the effect of crystal structure on energy band gap, lattice packing fraction is included in the mathematical formulation. The model does not involve any approximation or adjustable parameter. The study on nanosized semiconductors is performed. The model results depict the increase in the energy bandgap of nanosized semiconductors with reduction in size to nanoscale. Based on dimensionality, increment in energy band gap of spherical nanoparticles (NP’s) is more than that in cylindrical nanowires (NW’s) and thin films. The model results are found in good agreement with compared experimental and stimulated data. Drastic increase in energy band gap in nano-semiconductor of diameter or height less than 10 nm is due to the quantum confinement of charge carriers with increase in the surface area/volume ratio. With reduction in size of the Nano semiconductor, increase in the Band gap is observed leading to the blue shift. The energy band gap dependence on size in the nanorange has opened the possibility of tuning the energy band gap of the nanomaterials and use them in the opto-electronic devices.

In this work, doped and dopant-free carrier-selective passivating contacts have been incorporated in Interdigitated Back Contact solar cells. TCAD simulation study was done to check the performance of an IBC-SHJ (Silicon Hetero-Junction) and IBC-POLO (POLy-silicon on Oxide as seen in TOPCon) cell structures for both p and n-type wafers. The IBC-POLO structure was also repeated with HfO₂ and ZrO₂ over electron transport and hole transport layers, respectively. Simulation study was done by replacing the doped silicon layers with dopant-free Transition Metal Oxides (TMOs). NiO was used as a dopant-free hole-selective contact, whereas Nb₂O₅ was used a dopant-free electron-selective contact. The fabrication of these materials is non-hazardous and at low temperatures due to which they are preferable over the doped Si layers that require toxic gases like phosphine, diborane, etc. and may also require high temperatures. For example, poly-Si layer applied in IBC-POLO requires an annealing temperature of over 800 °C; similarly, the diffusion of Front Surface Field (FSF) layer in normal IBC cells also requires the same high temperature. Temperature variation was done on these structures to check the dependence of solar PV parameters of each IBC structure on different temperatures. Same variation was checked with minority carrier lifetime of the silicon wafer.

This paper presents and investigates a new architecture of a computational cell based on nanoparticles of the phase-change material Ge₂Sb₂Te₅. Such a cell is a chaotic array of nanoparticles deposited between closely spaced electrical contacts. The state of such a structure is determined by the resistance of the nanoparticle array, which depends on the phase state of each particle of the material. Simulation results show that the proposed structure has a number of electrical states switching features that cannot be achieved using a thin film architecture. The proposed architecture allows for smoother and more controlled switching of the resistance by electrical pulses. Simulation of the evolution of the cell state using complex control actions showed that the proposed structure can behave as an artificial convolutional neuron with horizontal connections and also as a multi-level memory cell. In addition, the proposed design is technologically simple to achieve and inexpensive to manufacture.

The numerical and analytical results of a study on the paramagnetism of a two-dimensional electron gas depending on concentration and temperature are presented. The dependence of spin susceptibility on the width of the quantum well, temperature, concentration, and chemical potential at the resonance points and away from it was analyzed. The susceptibility was analyzed in the model of an ideal gas with a parabolic spectrum and a quantum well of infinite depth. The numerical results of the susceptibility calculation will be presented in graphs for different temperatures, quantum well widths, and concentrations.

We have simulated Ag–Ge–Te-based conductive bridge RAM (CBRAM) under RF electromagnetic wave input to investigate the RF effects on heat transfer and electrochemical reaction. The RF simulations agreed with the experimental transmission coefficient S₂₁ between 0.4 and 1 GHz, indicating an effective, uniform electric field applied in the RF-applicable CBRAMs. The heat transfer simulations showed a minimal temperature increase of about 1 K under the RF wave at 10 MHz and 10 dBm, indicating negligible thermal effects. The electrochemical simulations were based on the Nernst–Planck equation, taking into account the Ag ion transport in the Ag–GeTe electrolyte by diffusion and migration. Electrode kinetics were calculated for charge transfer reactions using the Butler–Volmer equation. The cathode electrode moved at a velocity equal to the rate of Ag electrodeposition on the cathode. The electrode movement represented filament growth. The electrochemical simulations successfully reproduced filament growth, bipolar resistive switching, experimental currents, and SET/RESET voltages. In addition, the electrochemical simulations under RF waves showed a decrease in the magnitude of SET and RESET voltages, consistent with experimental observations. The RF-induced SET/RESET voltage modulation was attributed to redox reactions that changed the average ion concentration during RF cycles, accelerating filament growth and dissolution.

This paper evaluates the performance of electrostatic-doped silicene nanoribbon field-effect transistors (ED SiNR-FET) and graphene nanoribbon field-effect transistors (ED GNR-FET) through quantum-based electron transport simulations. It assesses the impact of ribbon widths and device geometry, revealing that ED SiNR-FET generally outperforms ED GNR-FET, particularly in terms of resistance to impurities and short-channel effects. The study identifies optimal ribbon widths for superior performance and introduces the extended channel ED (ECED) structure, which significantly enhances the I_ON/I_OFF ratio to 3.8 × 10⁵ in SiNR-FET compared to 3.9 × 10³ in GNR-FET for 15 nm devices. Additionally, analyses of ECED SiNR-FETs and ECED GNR-FET across various channel and gate lengths suggest that ECED devices are suitable for low-power and high-performance applications, with the ECED SiNR-FET displaying excellent subthreshold swing (SS) of 64 mV/dec and high transconductance (g_m) of 63 µS. This research confirms the advanced performance of SiNR-FETs over GNR-FETs and the potential of ECED SiNR-FETs in diverse applications.

In this paper, different modeling approaches to the drain current, including analytical and artificial neural network (ANN) modeling, are investigated. The adopted models address the inherent self-heating and kink effects, especially in high-power GaN-based high electron mobility transistors (HEMTs). Different optimization algorithms were demonstrated for extracting the model parameters, including genetic algorithm optimization (GAO), gray wolf optimization (GWO), growth optimization (GO), and particle swarm optimization (PSO). The modeling approaches are applied to DC IV measurements of 1-mm, 4-mm, and 2-mm GaN HEMTs on SiC and Si substrates. An improved optimization procedure was applied to the analytical models to find the main parameters responsible for fitting the general nonlinear behavior of the device. Then, the thermal or self-heating parameters are tuned for best fitting in the high-power dissipation region. The kink effect has been counted by adding another factor to the analytical formula to characterize the voltage dependency of this effect. The ANN modeling provides an efficient and cost-effective solution to accurately simulate the IV characteristics with less effort. In this technique, there is no need for a predefined closed formula or a complicated fitting parameter extraction process. Also, the model training was enhanced by using a genetic algorithm augmented backpropagation technique. The investigated analytical and ANN techniques were demonstrated by modeling the IV characteristics of the considered GaN HEMTs. The results obtained confirm the advantages of using ANN modeling for solving such problems and large-signal modeling applications.

The synergistic effect of total ionizing dose on single event gate rupture (SEGR) was simulated in the vertical double diffusion metal oxide semiconductor device with SiO₂–Si₃N₄ stacked gate layer. In comparison to the device with a single SiO₂ gate layer, the synergistic effect was revealed to be suppressed in the device with SiO₂–Si₃N₄ stacked layer. The mechanism is that the oxide layer is a sensitive area of the SEGR effect. Compared with the single SiO₂ layer, the superposition of the additional electric field formed by the trapped holes in the sensitive area of the stacked layer leads to a decrease in the sensitivity of the synergistic effect, which is more obvious with increasing the volume of the Si₃N₄ layer.

Perovskites possessing lead have gained immense consideration recently owing to their unique optoelectronic properties. Thus, they are considered highly suitable materials for solar power and harvesting applications. However, the instability of perovskites in air and moisture, along with the toxicity of lead, has limited their use in developing practical devices. In this work, detailed first-principles research was carried out to discover the basic structural, electronic, optical, and thermoelectric properties of cubic lead-free double perovskites K₂SnX₆ (X = Cl, Br, I). All structures exhibited good mechanical stability as they satisfied the Born criteria. The values of their Poisson’s (v) and Pugh’s ratios (B₀/G) exceeded the critical numbers of 0.26 and 1.75, respectively, revealing their ductile nature. The bandgap calculations for the structures were accomplished using the generalized gradient approximation (GGA), which revealed that these perovskites exhibited direct band gaps except K₂SnI₆, having metallic characteristics. The bandgaps were also calculated by adding the modified Becke–Johnson potential (TB-mBJ). Moreover, computed refractive indices for K₂SnBr₆ and K₂SnI₆ revealed excellent luminescent properties in the UV region. The figure of merit (ZT) for K₂SnCl₆ and K₂SnBr₆ approached 1, whereas its value was around 0.568 for K₂SnI₆ at room temperature. The conclusions of this study provide sufficient evidence that these perovskite structures K₂SnX₆ (X = Cl, Br, I) show immense potential for upcoming energy conversion and solar cell-based technologies.

Graphical abstract

In this work we studied the effects of negative hydroxyl ions at the SnO₂/perovskite layer interface with respect to the performance of perovskite solar cells (PSCs). We considered a layer of 1 nm thickness, containing fixed negative ions, at the SnO₂/perovskite layer interface. The density of the ions was set to 7 × 10¹⁹ cm⁻³ in our simulations. To maintain charge neutrality in the SnO2 electron transport layer (ETL), we calculated the number of negative ions in the 1-nm-thick layer and added the same number of positive ions to the remaining part of the ETL. According to our simulation results, the negative ions increased the internal potential drop, reducing the open-circuit voltage of the perovskite solar cell from 0.99 to 0.88 V. On the other hand, the negative non-mobile hydroxyl ions at the interface absorbed some of the mobile positive ions of the perovskite layer, which increased the hysteresis index from 0.177% to 0.707%.