Journal of Computational Electronics最新文献

The quantum-dot cellular automata (QCA) technology is considered as a possible nanoelectronic technology for future computing facilities. The leading role of QCA wires makes it preferable for serial data transfer/processing. Many modern computer applications require direct processing of decimal information without representation and conversion errors. The main purpose of the research is to design a novel QCA serial decimal digit multiplier. A QCA wire can be considered as a virtual tape with written binary symbols. The designed multiplier uses the Turing machine run-time multiple tapes reconfiguration to multiply two decimal digits encoded in the 5-bit Johnson–Mobius code. The proposed multiplier has successfully passed verification. In comparison with possible QCA BCD multipliers, it shows significant hardware simplification.

Metasurfaces can flexibly regulate terahertz wave, but most of reported results are limited to single polarized terahertz wavefront manipulation. In this article, the propose metasurface can manipulate linearly polarized and circularly polarized terahertz waves. It consists of five metal layers (namely metal rectangular bars, metal rings, two orthogonal metal gratings, and I-shaped metal layers) separated by four polyimide dielectric layers. For circularly polarized wave incidence, the metasurface generates vortex beams with topological charges of l =  ± 1 and l =  ± 2 at frequency of 1.2 THz. In addition, the metasurface achieves “T” shaped near-field image at 0.931 THz. Under linearly polarized wave incidence, the metasurface produces polarization conversion with a conversion ratio over 98% within the frequency range of 0.6–0.8 THz. The proposed structure has potential application prospects in terahertz wave multi-polarized manipulation in future terahertz wireless communication.

In light of the continuously rising demand for portable handheld devices in day-to-day life and in specific applications such as biomedical systems (blood pressure monitors, pacemakers, and hearing aids), stable digital systems with low area and power consumption are required. Static random-access memory (SRAM) is a fundamental component of digital systems, and hence stable and efficient design of SRAM is critical. This paper reports on the stability and reliability of a SRAM device designed using a gate-stack junctionless double-gate transistor (GS-JLDGT). The proposed GS-JLDGT is used to implement a six-transistor (6T) SRAM, and the GS-JLDGT structure is then modified by adding an oxide layer in the middle and utilized to design a 3T SRAM. As a result, the area occupied by the proposed 3T SRAM is reduced by almost half as compared to a conventional 6T SRAM layout. The reliability assessment of the designed SRAM is carried out by the inclusion of interface trap charges at the oxide–semiconductor interface. The results show that the presence of the interface trap charges leads to degradation in the voltage transfer curve (VTC) and hence significant deviations in various stability parameters, including the retention noise margin (RNM), static noise margin (SNM), static voltage noise margin (SVNM), static current noise margin (SINM), write trip voltage (WTV), and write trip current (WTI) of the device. In addition, the impact of temperature variation along with trap charges is investigated with respect to the stability of the GS-JLDGT-based 6T SRAM. The results indicate that as the temperature increases, distortion due to trap charges also increases significantly.

Nanotechnology has revolutionized circuit design by enabling highly efficient and compact components. Central to this innovation is the two-input NOR logic gate, a universal element in logic circuits that facilitates the construction of diverse logic configurations. Its versatility plays a pivotal role in digital logic design, particularly within the realm of molecular transistor technology, where miniaturization and efficiency are paramount. In this paper, a novel device is presented based on the Oligo (phenylene ethynylene) (OPE) molecule. OPE molecules offers significant advantages in digital circuits due to their superior electronic properties, nanoscale size, self-assembling capabilities, and tunable characteristics. By leveraging this intriguing feature of the proposed dual-gate molecular transistor, a two-input NOR logic gate is realized. The study employs advanced simulation techniques, including Non-Equilibrium Green’s Function formalism and density functional theory, to model quantum transport properties. Insights gained from these simulations elucidate the performance and reliability of molecular transistors under varying operational conditions, advancing our understanding of their potential in future nanoelectronics applications.

Perovskite solar cells (PSCs) possess high potential to generate electricity. As, hole transport material (HTM) is the main factor of concern so, in current study, with the purpose of improving power efficiency ratio of PSCs, a series of five novel molecules, namely DTP1, DTP2, DTP3, DTP4 and DTP5 have been created computationally by structural modifications of dithieno [3,2-b:2′,3′-d]pyrol cored (DTP-C6TH) HTM. Five different electron-deficient acceptor moieties are substituted at the peripheral sites of the reference molecule (DTP-C6TH). To predict the efficiency of these newly fabricated molecules, their optoelectronic characteristics have been investigated by using MPW1PW91 DFT approach coupled to the basis set 6-31G (d, p). All structures are optimized by executing same DFT method by frontier molecular orbitals (FMOs) evaluations has been performed which suggests an excellent charge transport rate in all fabricated molecules (DTP1-DTP5). Further, density of states was studied that describes the involvement of all segments of recently designed molecules in the synthesis of molecular orbitals HOMO and LUMO. Results illustrate the energy gap estimations pertaining formulated molecules are significantly reduced relative to reference molecule (2.99 eV) with sequence of DTP5 = 2.29 eV > DTP1 = 2.11 eV > DTP2 = 2.04 > DTP3 = 1.93 eV > DTP4 = 1.73 eV. Absorption spectrum has been analyzed and a red shift in the wavelength is perceived  in all designed molecules (532–739 nm). Transition density matrix evaluations TDM, reorganizational energies (RE), open circuit voltage V_oc and power conversion efficiency (PCE) for all architecture molecules have been computed and it is concluded from the outcomes that these newly planned molecules possess efficient opto-electronic properties with enhanced PCE of up to 24.3% and can be used in future as HTMs for application in Perovskite solar cells.

In this article, we simulated the Interdigitated Back Contact (IBC) solar cell using Quokka3 simulation, highlighting a detailed approach to front and back passivation and sheet resistance that significantly enhances cell performance. The antireflective coating (ARC) and the front passivation layer, after fine-tuning variation of recombination current density J₀ (fA/cm²), dictate the recombination losses at these interfaces, therefore playing a critical role on cell efficiency. The rear passivation layer complements the front in mitigating recombination to optimize light capture within the silicon wafer. When the emitter fraction is approximately 40% at 100 Ω/Sq, the rear boron sheet resistance showed the enhanced V_oc, J_sc, FF, and η as 719.2 mV, 41.66 mA/cm², 84.71%, and 25.2%. These results demonstrate how J₀ and rear boron area variability, influenced by both front and back passivation, affects the FF and η of the IBC cell. Furthermore, variations in the bulk lifetime of crystalline silicon (c-Si), resistivity of the wafer, and rear boron sheet resistance (R_sh) offer pathways to improve overall cell performance.

Process variation leads to variability in key device parameters such as plug separation, recess depth, epi-plug doping, and epi-plug height, which play a vital role in 3D NAND performance during scaling. Machine learning (ML) offers an alternate approach to predict and optimize performance by analyzing variable nonlinearity. However, in recent work, device optimization has been done over a narrow range, resulting in local rather than global optima. Additionally, these methods rely on extensive datasets, which increase costs and reduce the practicality of TCAD-ML models. This paper uses transfer learning to optimize the above parameters by integrating a long short-term memory (LSTM) model with the JAYA optimization algorithm. This approach considers a wide range of device parameters for optimization. By training on well-calibrated TCAD-generated data, we achieve an impressive accuracy rate of 98.5% in forecasting the values of threshold voltage (V_th), on current (I_on), subthreshold swing (SS), and transconductance (g_m). Our results reveal that the LSTM uses fewer datasets and outperforms feedforward neural networks with a performance improvement of 67%. Further, we achieve a mean-squared error of 0.217 using the JAYA optimization algorithm.

The invention of new transistors and their channel length reduction are challenging processes. The carbon nanotube field-effect transistor (CNTFET), especially the gate-all-around (GAA) type, is an encouraging technology to solve the short channel effect. In this paper, changing doping concentration and finding the best coordination for contacts and spacer are promising approaches that are discussed. A highly doped 5 nm GAA CNTFET is presented and its functionality is evaluated in the device, layout, and circuit states. By the Monte Carlo method, the best structure coordination of drain and source contacts, spacer, width, and height are extracted. The device is evaluated for different supply voltages and the best voltage for its operation is 0.5 V. The concentration of dopants for n-type devices is found to be N_D0 = 1 × 10²¹ cm⁻³ and N_A = 1 × 10¹⁸ cm⁻³ for the donor and acceptor, respectively, and for the p-type, N_A and N_D0 are replaced. Also, the I_on/I_OFF ratio of n-type and p-type are 2.3 × 10⁴ and 1.6 × 10⁴, respectively, which are achieved by double optimization. The optimized devices are implemented in an inverter. The resulting noise margin of the inverter demonstrates its high accuracy. The customized device is a qualified candidate for sophisticated structures.

The characterization of silver nanoparticles is vital for understanding unique properties and potential applications in various fields. This research aims to explore and evaluate characterization techniques to assess the quality and behavior of silver nanoparticles. Understanding characteristics is crucial for optimizing synthesis methods and ensuring safe and effective use in nanotechnology applications. In this research, bidirectional long short-term memory-Mantis search algorithm is deployed to characterizations of silver nanoparticle and also evaluates the characteristics of silver nanoparticle such as the accuracy, precision, recall, and f1-score values are recorded. The outcome of the recommended technique is implemented in MATLAB and benchmarked against existing approaches, demonstrating its effectiveness in achieving the proper characterization. The results indicate that the given approach outperforms existing techniques, demonstrating its effectiveness and also reduces the weighted square error by 0.6 and enhances the precession by 98.8%. This signifies not only the effectiveness, but also the efficiency of the given approach, indicating its potential for streamlining characterization processes and enhancing productivity in nanotechnology research and development.

Water is one of the essential requirements for human life. Various types of impurities that are present in the drinking water can produce grave health concerns, affect body tissues, and may lead to death. Protozoan parasites are one of the major biological pollutants in the water, which are ordinarily transferred across during the oral-fecal path. Cryptosporidium parvum oocysts (CPO) and Giardia lamblia (GL) are two frequently observed waterborne protozoan organisms. They have different values of index of refraction (IOR). Novel detector can be established with real-time detection based on this biophysical consideration. Here, an optical surface plasmon resonance biosensor (OSPRB) is developed for discovery of CPO and GL in drinking water. Angular examination and Kretschmann design are employed to explain the conception of the setup. An angular sensitivity (AS) of 188 Deg./RIU is attained by the suggested OSPRB with very low limit of detection (LOD) of 2.64 × 10⁻⁵ RIU. Other functioning factors are calculated for offered OSPRB. The achieved outcomes indicate that the suggested OSPRB has conspicuously improved performance as contrasted to aforementioned outcomes in the literatures. The suggested OSPRB can accelerate a substantial biological detecting tool with accurate and fast sensing at early point.