Electrical Characteristics Research Articles

Nanotransfer Printing for Synthesis of Vertically Aligned Carbon Nanotubes with Enhanced Atomic Penetration

AbstractVertically aligned carbon nanotubes (VACNTs) exhibit outstanding mechanical strength, chemical stability, and electrical characteristics; however, their constrained mechanical elasticity and chemical responsiveness spurred research on atomic decoration techniques for enhancing their mechanochemical attributes. Nevertheless, achieving uniform atomic decoration on the VACNT surface is difficult because of the high density and large aspect ratio of VACNT. Herein, a strategy to design and apply nanopatterned VACNTs (nVACNTs) based on a nanotransfer printing process is proposed to improve atomic penetrability. Nanopatterns inherent to nVACNTs facilitate atomic penetration, allowing for the more consistent and higher quality deposition of functional materials such as zinc oxide and alumina by atomic layer deposition. Furthermore, physical vapor deposition provides an improved coating of metal catalysts such as gold. The uniform deposition of ceramic layers on the entire surface of nVACNTs strengthens its mechanical resilience, owing to the diminished van der Waals forces of CNTs. Surface‐decorated nVACNTs display an increased sensitivity to NO2 gas, which is attributed to the enhanced quality of the reactive catalyst deposition and augmented permeability. This strategy achieves a larger decorated area while increasing a catalytically active reaction area. The obtained results promise that the enhanced nVACNTs will expand the industrial applications of carbon nanotubes.

Modeling and Experiments on Temperature and Electrical Conductivity Characteristics in High-Temperature Heating of Carbide-Bonded Graphene Coating on Silicon

Modeling and Experiments on Temperature and Electrical Conductivity Characteristics in High-Temperature Heating of Carbide-Bonded Graphene Coating on Silicon

Monolithic three-dimensional tier-by-tier integration via van der Waals lamination.

Two-dimensional (2D) semiconductors have shown great potential for monolithic three-dimensional (M3D) integration due to their dangling-bonds-free surface and the ability to integrate to various substrates without the conventional constraint of lattice matching1-10. However, with atomically thin body thickness, 2D semiconductors are not compatible with various high-energy processes in microelectronics11-13, where the M3D integration of multiple 2D circuit tiers is challenging. Here we report an alternative low-temperature M3D integration approach by van der Waals (vdW) lamination of entire prefabricated circuit tiers, where the processing temperature is controlled to 120 °C. By further repeating the vdW lamination process tier by tier, an M3D integrated system is achieved with 10 circuit tiers in the vertical direction, overcoming previous thermal budget limitations. Detailed electrical characterization demonstrates the bottom 2D transistor is not impacted after repetitively laminating vdW circuit tiers on top. Furthermore, by vertically connecting devices within different tiers through vdW inter-tier vias, various logic and heterogeneous structures are realized with desired system functions. Our demonstration provides a low-temperature route towards fabricating M3D circuits with increased numbers of tiers.

Highly reproducible and CMOS-compatible VO2-based oscillators for brain-inspired computing.

With remarkable electrical and optical switching properties induced at low power and near room temperature (68°C), vanadium dioxide (VO2) has sparked rising interest in unconventional computing among the phase-change materials research community. The scalability and the potential to compute beyond the von Neumann model make VO2 especially appealing for implementation in oscillating neural networks for artificial intelligence applications, to solve constraint satisfaction problems, and for pattern recognition. Its integration into large networks of oscillators on a Silicon platform still poses challenges associated with the stabilization in the correct oxidation state and the ability to fabricate a structure with predictable electrical behavior showing very low variability. In this work, the role played by the different annealing parameters applied by three methods (slow thermal annealing, flash annealing, and rapid thermal annealing), following the vanadium oxide atomic layer deposition, on the formation of VO2 grains is studied and an optimal substrate stack configuration that minimizes variability between devices is proposed. Material and electrical characterizations are performed on the different films and a step-by-step recipe to build reproducible VO2-based oscillators is presented, which is argued to be made possible thanks to the introduction of a hafnium oxide (HfO2) layer between the silicon substrate and the vanadium oxide layer. Up to seven nearly identical VO2-based devices are contacted simultaneously to create a network of oscillators, paving the way for large-scale implementation of VO2 oscillating neural networks.

Deterioration of Li-doped phenanthroline-based charge generation layer for tandem organic light-emitting diodes

Understanding the deterioration of the charge generation layer (CGL) is an uprising issue for efficient and stable tandem organic light-emitting diodes. Here, we comprehensively investigated the change in the electrical characteristics of Li-doped CGLs according to different stress conditions and compared the stability of Li diffusion in two phenanthroline-based electron transport materials. Through current density–voltage and capacitance-frequency measurements, it was revealed that electrical stress and thermal stress affect CGL’s electrical properties differently. Moreover, the exponential trap distribution model analysis informed that the Li diffusion is expedited toward narrowing depletion width in the CGL. Diffusion of Li and thermal effect to the diffusion was experimentally observed by X-ray photoelectron spectroscopy (XPS) depth profiling. We also evaluated variations in the operating voltage of tandem devices that differed only in nCGL. Overall, Li diffusion occurs more favorably in sparse Bphen film with weak binding energy rather than closely packed BPPB film with strong binding energy, which highlights that atomic geometry and morphological characteristics are crucial for the stability of tandem devices.

Effects of spacer layer thickness in InAlN/GaN double-channel HEMTs

In this paper, the impact of upper channel layer thickness on the electrical characteristics and hysteresis behavior of double-channel InAlN/GaN HEMTs were investigated. The devices with an upper channel layer thickness of 20 nm exhibit higher output current and lower R on compared to devices with a thickness of 10/6 nm. This is attributed to the higher sheet carrier density and the reduced scattering. However, a 20 nm thickness of the upper channel layer in HEMT exhibits hysteresis phenomena in its electrical characteristics. For this hysteresis phenomenon, capacitance measurements and TEM characterization indicate that it is caused by dislocations in the lower barrier layer under the gate. A thicker upper channel layer is beneficial to increasing the output current of the device but leads to degradation of the lower InAlN barrier layer, resulting in hysteresis. This study provides an optimized solution for the growth and device fabrication of double-channel InAlN materials.

Structural, dielectric and electrical characteristics of lead-free compound, SrBiLaNbVO9, for NTCR application

Structural, dielectric and electrical characteristics of lead-free compound, SrBiLaNbVO9, for NTCR application

Beta Irradiation Effects on Electrical Characteristics of Graphene-Doped PVA/n-type Si Nanostructures

Beta Irradiation Effects on Electrical Characteristics of Graphene-Doped PVA/n-type Si Nanostructures

Synthesis of Nano-electrolytic Manganese Dioxide for Alkaline Batteries Mediated by Organic Additives

This article discusses the impact of adding organic additives like glycine (GLY), sucrose (SUC), and saccharine (SACCH) on the electrical characteristics and microstructure of electrolytic manganese dioxide (EMD), which is made from an acidic aqueous sulphate solution. The structure and chemistry of EMD were ascertained by means of Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). To assess the material's potential for use in alkaline batteries, its charge-discharge properties were ascertained. It was found that the majority of MnO2 in all the EMD samples was in the γ-phase, which is electrochemically active and useful for energy storage applications. When glycine, sucrose, and saccharine were added to the solution as organic additives, the electrochemical deposition of manganese dioxide (MnO2) resulted in an increase in current efficiency and a decrease in energy consumption. The SEM images demonstrated that when EMD was deposited with an additive, small grain sizes and discrete particles free of agglomeration were formed, but large grain sizes were obtained in the absence of additives. Charge-discharge characteristics suggested that the additions improve the ability of MnO2 structure to store energy. This suggested that the additions may have an impact on the morphology and size of the particles, and consequently, the electrochemical activities of the material that was electrodeposited. In the case of the additives examined in this paper, the outcome was the creation of a material with possible use in battery technology.

Improving the optical and dielectric characteristics of PVA/PVP/PEG/ZnWO4/CdS blends

This work aims to create novel nanocomposite blended polymers by incorporating (1−x)ZnWO4-xCdS into poly (vinyl alcohol) (PVA)/polyvinyl pyrrolidone (PVP)/polyethylene glycol (PEG) blend to employ these nanocomposites in various optoelectronic applications. This study focused on investigating the structural, optical and electrical features of PVA/PVP/PEG/(1−x)ZnMn2O4-xCdS blends. The x-ray diffraction and scanning electron microscope techniques were used to explore the structure and morphology of the formed samples. The structure and percentages of ZnWO4 and CdS in different fillers were performed using Rietveld method. The doped blends exhibited significant absorption of UVA and UVB types. The greatest amounts of absorption were observed when the filler contained 25 % CdS. The direct and indirect optical band gaps of the doped blend became 5.02 and (1.88, 2.37) eV as the amount of CdS became 25 % in the filler sample. The refractive index, optical dielectric constant, optical conductivity, and nonlinear optical parameters are affected by the amount of CdS in the fillers. The fluorescence spectra for the blends affected by the excitation wavelength and amount of CdS in the filler. The maximum energy density of the doped blend was reached when the amount of CdS in the filler reached 25 %. The purities of emitted color in the undoped blend are 83 % and 74 % under excitation wavelengths of 317 nm and 380 nm. The purity of the blend experienced a slight change when loaded with filler samples. As the ZnWO4 doping of the PVA/PVP/PEG blended polymer rose, its electrical dielectric constant and ac conductivity first enhanced and then irregularly declined as the filler's CdS content rose. Incorporating (1−x)ZnWO4-xCdS into the nanocomposite enhanced their optical and electrical properties, making them a potential material for flexible optoelectronic and energy storage uses.

CuO nanoflowers: Multifaceted implications of various precipitating agents on rectification behaviour

In order to achieve the best possible use of traditional energy resources for the preservation of the environment, semiconductor-based optoelectronic devices are one of the most intriguing methods for converting light energy into electrical energy. CuO has been extensively explored as a material for energy conversion and the development of photo-detectors due to its notable characteristics among other metals, especially its non-toxicity, abundance, high efficiency, electrochemical stability and low cost/promising photodiode. However, some drawbacks limit its practical application in white light and photo-detector, including the rapid recombination rate of photo-generated electron-hole pairs and destitute response to visible light. As a result, several strategies have been developed from an optoelectronics perspective to eradicate these deficiencies and make an effort to enhance CuO photodiode activities. In this research work, the electrical characteristics and rectification behaviour of CuO with various precipitating agents have been examined. The CuO nanoparticles can be synthesized by co-precipitation technique prepared with different precipitants. Through this research, several parameters, such as the structural, functional, morphological, optical and electrical characteristics, were investigated by changing the precipitants. The functional group formation of pure CuO phase was confirmed by FT-IR studies. UV–Vis absorption measurements indicate that the band gap of the CuO nanoparticles was ranging from 2.40 to 2.85 eV. As a diode, CuO/p-Si exhibits a non-ideal behaviour and under light conditions with Na2CO3 precipitant, the better ideality factor is about 2.35. The barrier height is determined by the thermionic emission theory to be 0.77 and 0.79 eV in the dark and light conditions respectively.

Exploring the Post-Annealing Influence on Stannous Oxide Thin Films via Chemical Bath Deposition Technique: Unveiling Structural, Optical, and Electrical Dynamics

Stannous oxide (SnO2) thin films have garnered significant attention for their promising applications in various electronic and optoelectronic devices. In this study, we investigate the impact of post-annealing on the structural, optical, and electrical properties of stannous oxide thin films deposited using the chemical bath deposition (CBD) technique. The thin films were prepared on a Borosilicate glass substrate, followed by a controlled annealing process to enhance their performance. Structural analysis was conducted using techniques such as X-ray diffraction (XRD) to examine the cubic crystalline structure and the crystallite size increase induced by post-annealing. The results revealed alterations in grain size from the SEM and the purity of samples confirmed from EDX results. The optical properties of the Stannous oxide thin films were examined using UV-Vis spectroscopy. The optical absorption and bandgap characteristics were analyzed to understand how post-annealing influences the optical behavior of the thin films. Where the optical absorption was 320nm and the bandgap ranges were 3.86eV to 3.83eV. Furthermore, the electrical properties of the thin films were evaluated semiconducting nature, and conductivity increased with rising post-annealing. The findings from this study contribute to the understanding of the role of post-annealing in tailoring the properties of Stannous oxide thin films. The optimization of structural, optical, and electrical characteristics is crucial for their successful integration into electronic and optoelectronic devices.

UV-Irradiation Effects on the Structural, Optical and Electrical Characteristics of Soft Blended Polymeric Materials Loaded with Multi-Walled Carbon Nanotubes (MWCNTs)

Undoped and doped polyvinylpyrrolidone/carboxy-methyl cellulose/zinc sulfide/nickel oxide (PVP/CMC/ZnS/NiO) nanocomposite blends with multi-walled carbon nanotubes (MWCNTs) were prepared using sol-gel and solid-state reactions and casting techniques. Various blends were formed and their composition and morphologies were characterized using X-ray diffraction (XRD) and scanning electron microscope (SEM) techniques. The structures of the nano-fillers were examined using the XRD technique. The influence of the concentrations of MWCNTs on the linear and nonlinear optical parameters of PVP/CMC/ZnS/NiO nanocomposite blends was examined. The optical band gap energies were decreased from (direct, indirect: 5.31, 5.06) eV for undoped blends to 4.38 and 3.34 eV for the blends doped with the highest concentration of MWCNTs (0.15 wt%). The refractive indices of the various blends were calculated based on the obtained optical band gap energies using various models. The effect of MWCNTs concentrations on the dielectric constants, energy density, electric modulus and ac conductivity at room temperature of the PVP/CMC/0.5ZnS-0.5NiO/x wt% MWCNTs samples were explored using an Inductance, L, Capacitance, C, and Resistance, R (LCR) meter bridge.

A progressive overview of the mainstream additive manufacturing of ceramic components for industrial advancement

Additive manufacturing (AM), well-known as 3D printing, has revolutionized traditional manufacturing methods, particularly in the production of ceramic components. These techniques offer unique advantages and challenges in ceramic component production. Developing specific ceramic materials with AM improves the finished products' mechanical, thermal, and electrical characteristics. Integrating artificial intelligence and machine learning shows promise in improving process control and design optimization, spurring innovation and opening previously unimaginable possibilities, although problems such as material shrinkage, microstructural control, and surface polish remain crucial research areas. This review article presents a comprehensive overview of the advancements and applications of AM for ceramic pieces in the industrial sector. This study highlights the fundamental principles of AM, focusing on their difficulties and potential in ceramic fabrication. A comprehensive review of AM will deliver an understanding of its ability to alter industrial manufacturing and open the door to a new era of ceramic fabrication and applications.

Prediction of electrical properties of GAAFET based on integrated learning model

As device feature sizes continue to decrease and fin field effect transistors reach their physical limits, gate all around field effect transistors (GAAFETs) have emerged with larger gate control areas and stackable characteristics for better suppression of second-order effects such as short-channel effects due to their gate encircling characteristics. Traditional methods for studying the electrical characteristics of devices are mostly based on the technology computer-aided design. Still, it is not conducive to developing new devices due to its time-consuming and inefficient drawbacks. Deep learning (DL) and machine learning (ML) have been well-used in recent years in many fields. In this paper, we propose an integrated learning model that integrates the advantages of DL and ML to solve many problems in traditional methods. This integrated learning model predicts the direct current characteristics, capacitance characteristics, and electrical parameters of GAAFET better than those predicted by DL or ML methods alone, with a linear regression factor (R 2) greater than 0.99 and very small root mean square error. The proposed integrated learning model achieves fast and accurate prediction of GAAFET electrical characteristics, which provides a new idea for device and circuit simulation and characteristics prediction in microelectronics.

First-Principles and Experimental Study of Ge, V, Ta-Doped AgNi Electrical Contact Materials

To explore the stability, electrical, and mechanical characteristics of undoped AgNi alongside AgNi doped with elemental Ge, V, and Ta, we performed calculations on their electronic structures using density functional theory from first-principles. We also prepared AgNi(17) and AgNi-x(Ge, V, Ta) electrical contact materials using the powder metallurgy technique, and they were subsequently assessed experimentally. The electrical properties of these materials were evaluated under a 24 V/15 A DC-resistive load using the JF04D contact material testing system. A three-dimensional morphology scanner was employed to examine the contact surface and investigate the erosion patterns of the materials. Our findings indicate that doping with metal elements significantly enhanced the mechanical properties of electrical contacts, including conductivity and hardness, and optimizes arc parameters while improving resistance to arc erosion. Notably, AgNi-Ge demonstrated superior conductivity and arc erosion resistance, showing significant improvements over the undoped AgNi contacts. This research provides a theoretical foundation for selecting doping elements aimed at enhancing the performance of AgNi electrical contact materials.

Establishing the NiMo6Se8 Chevrel Phase as a Promising Material Using DFT

AbstractIn this study, the NiMo6Se8 Chevrel phase is analyzed using Density Functional Theory (DFT) and the Vienna Ab‐initio Simulation Package (VASP). The analysis focuses on the phase's structural, electrical, and mechanical characteristics to fill gaps in the current literature. The presence of a rhombohedral crystal structure confirms its thermodynamic stability, as indicated by a negative formation enthalpy, which suggests that it can be synthesized under favorable conditions. The electronic properties of the phase are analyzed, indicating that it exhibits semiconductor characteristics with a bandgap of 1.07 eV. This makes it appropriate for various technological applications. The estimated elastic constants provide an indication of mechanical strength and flexibility, with a noticeable presence of anisotropic elasticity. The confirmation of dynamical stability is achieved by analyzing the phonon dispersion curve, which reveals the absence of any negative frequencies. Furthermore, the material has a low thermal conductivity, increasing its suitability for thermoelectric applications. The analysis emphasizes the versatile capabilities of the NiMo6Se8 Chevrel phase, especially in thermoelectric and energy storage applications, showcasing its promising potential for future technological implementation.

Evaluation of plastic injection molding for PA6/ABS/CaCO3 nanocomposites using Taguchi method and Moldflow simulation approach

Nowadays, nanocomposites are widely used in the industry. Polymer nanocomposites are widely used in the automotive industry because they have very favorable properties. These properties, including mechanical, electrical, and thermal characteristics, change depending on the combination of materials used in composite synthesis. In this paper, the injection molding of an automobile part called a control arm protector is investigated. Since warpage and shrinkage are general and important challenges in injection molded parts, Taguchi test design and Autodesk Moldflow® simulation approach are used to find the best injection condition for the mentioned part. To perform this, PA6/ABS polymer composite combined with nano CaCO3 is used. Three main injection molding process parameters, including melt temperature, mold temperature, and injection pressure, as well as nano CaCO3 amount, are evaluated. Moreover, analysis of the gate location is investigated. In the following, an analysis of variance is conducted to identify the significant parameters. Regression correlations were also established. Finally, optimization of the process is carried out by the desirability method.

NanoMUD: Profiling of pseudouridine and N1-methylpseudouridine using Oxford Nanopore direct RNA sequencing

Nanopore direct RNA sequencing provided a promising solution for unraveling the landscapes of modifications on single RNA molecules. Here, we proposed NanoMUD, a computational framework for predicting the RNA pseudouridine modification (Ψ) and its methylated analog N1-methylpseudouridine (m1Ψ), which have critical application in mRNA vaccination, at single-base and single-molecule resolution from direct RNA sequencing data. Electric signal features were fed into a bidirectional LSTM neural network to achieve improved accuracy and predictive capabilities. Motif-specific models (NNUNN, N = A, C, U or G) were trained based on features extracted from designed dataset and achieved superior performance on molecule-level modification prediction (Ψ models: min AUC = 0.86, max AUC = 0.99; m1Ψ models: min AUC = 0.87, max AUC = 0.99). We then aggregated read-level predictions for site stoichiometry estimation. Given the observed sequence-dependent bias in model performance, we trained regression models based on the distribution of modification probabilities for sites with known stoichiometry. The distribution-based site stoichiometry estimation method allows unbiased comparison between different contexts. To demonstrate the feasibility of our work, three case studies on both in vitro and in vivo transcribed RNAs were presented. NanoMUD will make a powerful tool to facilitate the research on modified therapeutic IVT RNAs and provides useful insight to the landscape and stoichiometry of pseudouridine and N1-pseudouridine on in vivo transcribed RNA species.

Optimization Decomposition of Monthly Contracts for Integrated Energy Service Provider Considering Spot Market Bidding Equilibria

Under the current power trading model, especially in the context of the large-scale penetration of renewable energy and the rapid integration of renewable energy into the power system, reasonable medium- and long-term decomposition can reduce the fluctuation in the energy price when the integrated energy service provider (IESP) participates in the spot market. It helps to avoid the price risk of the spot market. Additionally, it promotes the optimization of the operation of the regional energy day-ahead scheduling. At the present stage, most of the medium- and long-term contract decomposition methods focus on the decomposition of a single power and take less consideration of the bidding space in the spot market. This limitation makes it challenging to achieve efficient interaction and interconnection among multi-energy resources and smooth integration between the medium- and long-term market and the spot market. To address these issues, this paper proposes an optimal monthly contract decomposition method for IESPs that takes into account the equilibrium of spot bidding. First, the linking process and rolling framework of multi-energy transactions between the medium- and long-term market and the spot market are designed. Second, an optimal decomposition model for monthly contracts is constructed, and a daily decomposition method for monthly medium- and long-term contracts that accounts for the spot bidding equilibrium is proposed. Then, the daily preliminary decomposition result of medium- and long-term multi-energy contracts is used as the boundary condition of the day-ahead scheduling model, and the coupling characteristics of the multi-energy networks of electricity, gas, and heat are taken into account, as well as the operational characteristics. Then, considering the coupling characteristics and operating characteristics of electricity, gas, and heat networks, the optimal scheduling model of a multi-energy network is constructed to minimize the sum of cumulative daily operating costs, and the monthly final contract decomposition value and daily spot bidding space are derived. Finally, examples are calculated to verify the validity of the decomposition model, and the examples show that the proposed method can reduce the variance in spot energy purchase by about 4.64%, and, at the same time, reduce the cost of contract decomposition by about USD 0.33 million.