Search Results (357)

Epitaxial growth of β-Ga₂O₃ nanowires on silicon substrates was realized by the low-pressure chemical vapor deposition (LPCVD) method. The as-grown Si/Ga₂O₃ heterojunctions were employed in the Underwater DUV detection. It is found that the carrier type as well as the carrier concentration of the silicon substrate significantly affect the performance of the Si/Ga₂O₃ heterojunction. The p-Si/β-Ga₂O₃ (2.68 × 10¹⁵ cm⁻³) devices exhibit a responsivity of up to 205.1 mA/W, which is twice the performance of the devices on the n-type substrate (responsivity of 93.69 mA/W). Moreover, the devices’ performance is enhanced with the increase in the carrier concentration of the p-type silicon substrates; the corresponding device on the high carrier concentration substrate (6.48 × 10¹⁷ cm⁻³) achieves a superior responsivity of 845.3 mA/W. The performance enhancement is mainly attributed to the built-in electric field at the p-Si/n-Ga₂O₃ heterojunction and the reduction in the Schottky barrier under high carrier concentration. These findings would provide a strategy for optimizing carrier transport and interface engineering in solar-blind UV photodetectors, advancing the practical use of high-performance solar-blind photodetectors for underwater application. Full article

The study of the processes of low-temperature synthesis of one-dimensional particles, which are the basis for two- and three-dimensional structures, is relevant for materials science. The modified metal-stimulated electrochemical etching method made it possible to synthesize silicon nanowires with an average thickness of about 292.6 nm. Scanning electron microscopy has shown the formation of nanowires, flower-like structures, and clusters of matter after the deposition of zinc oxide on the porous surface. The hexagonal structure of ZnO crystallites was determined by X-ray diffraction spectroscopy. Studies of the initial sample by electron paramagnetic resonance (EPR) spectroscopy revealed a narrow signal in the center of the spectrum. The subtraction of the EPR spectra with a sequential increase in microwave power up to 8 mW shows the absence of saturation of the signal. This indicates an almost free flow of charges through the surface nanostructures under the influence of an external field. Heat treatment in an air atmosphere at 300 °C caused a significant increase in the intensity of the EPR spectrum. This led to an increase in the intensity of charge transfer through paramagnetic centers. Full article

The synthesis and characterization of MgO-ZrO₂ heterostructures are examined in this work. To promote the creation of nanowires, the Si substrate is first covered with a catalyst layer of various Au thicknesses. Sputtering is used to achieve this deposition. After that, chemical vapor deposition (CVD) with a Au catalyst layer is used to create MgO nanowire arrays on the silicon substrate. Second, MgO/ZrO₂ Core–shell Nanowire Arrays are created by applying ZrO₂ layers to the surface of MgO nanowires of different diameters using chemical vapor deposition (CVD) procedures. The presence of both magnesium oxide (MgO) and zirconium dioxide (ZrO₂) in their oxidized forms was shown by the detailed characterization of the MgO-ZrO₂ core–shell nanowire samples utilizing a variety of methods. Phase formation, mechanical homogeneity, optical characteristics, and topographical structure and roughness were all thoroughly examined at various stresses. MgO hardness values ranged from 1.4 to 3.2 GPa, whereas MgO-ZrO₂ ranged from 0.38 to 1.2 GPa. The I–V parameter study was a further step in the examination of the heterostructure’s electrical properties. The structural, morphological, optical, mechanical, and electrical properties of the MgO-ZrO₂ heterostructure were all thoroughly described using these techniques. Full article

With the rapid advancement of artificial intelligence and machine learning technologies, the demand for enhanced device computing capabilities has significantly increased. Neuromorphic computing, an emerging computational paradigm inspired by the human brain, has garnered growing attention as a promising research frontier. Inspired by the human brain’s functionality, this technology mimics the behavior of neurons and synapses to enable efficient, low-power computing. Unlike conventional digital systems, this approach offers a potentially superior alternative. This article delves into the application of nanowire materials (and devices) in neuromorphic computing simulations: First, it introduces the synthesis and preparation methods of nanowire materials. Then, it analyzes in detail the key role of nanowire devices in constructing artificial neural networks, especially their advantages in simulating the functions of neurons and synapses. Compared with traditional silicon-based material devices, it focuses on how nanowire devices can achieve higher connection density and lower energy consumption, thereby enabling new types of neuromorphic computing. Finally, it looks forward to the application potential of nanowire devices in the field of future neuromorphic computing, expecting them to become a key force in promoting the development of intelligent computing, with extensive application prospects in the fields of informatics and medicine. Full article

This paper reports the field emission (FE) current stability of a diamond nanowire (DNW) array. Assembled with a silicon anode with a 1.03 μm gap, the FE properties, as well as the current stability of the DNW cathode, were systematically evaluated in a vacuum test system under different vacuum degrees, current densities, and atmospheres. Experiments demonstrate that lower pressure and current density can improve FE properties and current stability. In addition, compared to air and compressed air, DNWs exhibit higher FE properties and current stability in N₂. DNWs achieve a remarkably low turn-on field of 1.65 V/μm and a high current density of 265.38 mA/cm². Notably, they demonstrate merely 0.70% current fluctuation under test conditions of 1.2 × 10⁻⁴ Pa and 0.1 mA/cm². Additionally, based on the Fowler–Nordheim theory, the change in work function after gas adsorption was analyzed, and the noise generation mechanism was derived from the noise power spectrum. The current exponent is determined as 1.94, while the frequency exponent ranges from 0.92 to 1.32, confirming that the dominant noise mechanism in DNWs arises from surface work function fluctuations due to the adsorption and desorption of residual gas. Full article

Silicon-based materials provide a new pathway to break through the energy storage limits of battery systems but their industrialization process is still constrained by inherent diffusion hysteresis and unstable electrode structures. In this work, we propose a novel structural design strategy employing a modified spray freeze drying technique to construct multidimensional carbon nanostructures. The continuous morphological transition from carbon nanowires to carbon nanosheets was facilitated by the inducement of ultralow-temperature phase separation and the effect of polymer self-assembly. The unique wrinkled carbon nanosheet encapsulation effectively mitigated the stress concentration induced by the aggregation of silicon nanoparticles, while the open two-dimensional structure buffered the volume changes of silicon. As expected, the SSC-5M composite retained a reversible capacity of 1279 mAh g⁻¹ after 100 cycles at 0.2 C (1 C = 1700 mAh g⁻¹) and exhibited a capacity retention of 677.1 mAh g⁻¹ after 400 cycles at 1 C, demonstrating excellent cycling stability. This study offers a new strategy for the development of silicon-based energy storage devices. Full article

In situ-grown SiC nanowires (SiCnws) on SiC porous material (SiCnws@SiC) were prepared using sol–gel and carbothermal reduction methods, which substantially improves the electromagnetic wave absorption property of composite material. The crystallinity and purity of SiCnws are the best when the sintering temperature is 1600 °C. When the ratio of the carbon source (C) to the silicon source (Si) is 1:1, SiCnws@SiC composite exhibits excellent electromagnetic wave absorption performance, the minimum reflection loss is −56.95 dB at a thickness of 2.30 mm, and the effective absorption bandwidth covers 1.85 GHz. The optimal effective absorption bandwidth is 4.01 GHz when the thickness is 2.59 mm. The enhancement of the electromagnetic wave absorption performance of SiCnws is mainly attributed to the increase in the heterogeneous interface and multiple reflection and scattering caused by the network structure, increasing dielectric loss and conduction loss. In addition, defects could occur during the growth of SiCnws, which could become the center of dipole polarization and increase the polarization loss of composite materials. Therefore, in situ growth of SiCnws on SiC porous ceramics is a promising method to improve electromagnetic wave absorption. Full article

This paper reviews various design approaches for sensing schemes that utilize silicon nanowire (SiNW) ion-sensitive field-effect transistors (ISFETs) for pH-sensing applications. SiNW ISFETs offer advantageous characteristics, including a high surface-to-volume ratio, fast response time, and suitability for integration with complementary metal oxide semiconductor (CMOS) technology. This review focuses on SiNW ISFET-based biosensors in three key aspects: (1) major fabrication processes and device structures; (2) theoretical analysis of key performance parameters in readout circuits such as sensitivity, linearity, noise immunity, and output range in different system configurations; and (3) an overview of existing readout circuits with quantitative evaluations of N-type and P-type current-mirror-based circuits, highlighting their strengths and limitations. Finally, this paper proposes a modified N-type readout scheme integrating an operational amplifier with a negative feedback network to overcome the low sensitivity of conventional N-type circuits. This design enhances gain control, linearity, and noise immunity while maintaining stability. These advancements are expected to contribute to the advancement of the current state-of-the-art SiNW ISFET-based readout circuits. Full article

Solar-blind ultraviolet photodetectors are gaining attention for their high signal-to-noise ratio and strong anti-interference capabilities. With the rising demand for applications in high-strain environments, such as fire rescue robots and smart firefighting suits, a flexible photodetector that maintains stable performance under bending strain is needed. Current devices struggle to balance strain cycle stability and responsivity. This paper presents a β-Ga₂O₃ nanowire photodetector on a flexible ultra-thin silicon substrate, fabricated using microchannel engraving and chemical vapor deposition. The device achieves a responsivity of 266 mA W⁻¹ without strain, with less than 5.5% variation in photogenerated current under bending strain (0–60°), and a response time of 360 ms. After 500 cycles of 60° bending, the photogenerated current changes by only 1.5%, demonstrating excellent stability and responsivity, with broad application potential in flame detection and biological sensing. Full article

Typical wet-chemical methods for the preparation of silica nanowires use polyvinylpyrrolidone and n-pentanol. This study presents a polyethylene glycol-based emulsion template method for the synthesis of SiO₂ nanowires (SiO₂NWs) in isopropanol. By systematically optimizing key parameters (type of solvent, polyethylene glycol molecular weight and dosage, dosage of sodium citrate, ammonium and tetraethyl orthosilicate, incubation temperature and time), SiO₂NWs with diameters about 530 nm were obtained. Replacing polyvinylpyrrolidone with polyethylene glycol enabled anisotropic growth in isopropanol, overcoming the dependency on traditional solvents like n-pentanol. Scale-up experiments (10× volume) demonstrated robust reproducibility, yielding nanowires with consistent morphology (~580 nm diameter). After calcination at 500 °C for 1 h, the morphology of the nanowires did not change significantly. Full article

Using gradient-corrected density functional theory we investigate the mechanical properties of ultrathin boron (B) and phosphorus (P) doped silicon nanowires (SiNWs) along the [001] and [111] orientations within the PBE approximation. Both pristine and doped SiNWs under study have diameters ranging from 5 to 8 Å. Our results show that doping significantly enhances the bulk modulus ($B_0$), shear modulus ($G_V$), Young’s modulus (Y), and other mechanical parameters. The significant anisotropy observed in the mechanical properties of Si[111] NWs, with varying moduli along different axes, further illustrates the complex interplay between mechanical behavior and electronic structure at the nanoscale. The mechanical flexibility of SiNWs, combined with their tunable electronic properties due to quantum confinement, makes them promising candidates for advanced nanoelectronic devices, nanoelectromechanical systems (NEMS), and advanced technologies. Full article

The development of reliable, highly sensitive hydrogen sensors is crucial for the safe implementation of hydrogen-based energy systems. This paper proposes a novel way to enhance the performance of hydrogen sensors through integrating Pd-SnO₂ nanofilms on the substrate with silicon nanowires (SiNWs). The samples were fabricated via a simple and cost-effective process, mainly consisting of metal-assisted chemical etching (MaCE) and electron beam evaporation. Structural and morphological characterizations were conducted using scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). The experimental results showed that, compared to those without SiNW structure or decorative Pd nanoparticles, the Pd-decorated SnO₂ nanofilm integrated on the SiNW substrates exhibited significantly improved hydrogen sensing performance, achieving a response time of 9 s at 300 °C to 1.5% H₂ and a detection limit of 1 ppm. The enhanced performance can be primarily attributed to the large surface area provided by SiNWs, the efficient hydrogen spillover effect facilitated by Pd nanoparticles, and the abundant oxygen vacancies present on the surface of the SnO₂ nanofilm, as well as the Schottky barrier formed at the heterojunction interface between Pd and SnO₂. This study demonstrates a promising approach for developing high-performance H₂ sensors characterized by ultrafast response times and ultralow detection limits. Full article

Impedance-based biosensing has emerged as a critical technology for high-sensitivity biomolecular detection, yet traditional approaches often rely on bulky, costly impedance analyzers, limiting their portability and usability in point-of-care applications. Addressing these limitations, this paper proposes an advanced biosensing system integrating a Silicon Nanowire Field-Effect Transistor (SiNW-FET) biosensor with a high-gain amplification circuit and a 1D Convolutional Neural Network (CNN) implemented on FPGA hardware. This attempt combines SiNW-FET biosensing technology with FPGA-implemented deep learning noise reduction, creating a compact system capable of real-time viral detection with minimal computational latency. The integration of a 1D CNN model on FPGA hardware for adaptive, non-linear noise filtering sets this design apart from conventional filtering approaches by achieving high accuracy and low power consumption in a portable format. This integration of SiNW-FET with FPGA-based CNN noise reduction offers a unique approach, as prior noise reduction techniques for biosensors typically rely on linear filtering or digital smoothing, which lack adaptive capabilities for complex, non-linear noise patterns. By introducing the 1D CNN on FPGA, this architecture enables real-time, high-fidelity noise reduction, preserving critical signal characteristics without compromising processing speed. Notably, the findings presented in this work are based exclusively on comprehensive simulations using COMSOL and MATLAB, as no physical prototypes or biomarker detection experiments were conducted. The SiNW-FET biosensor, functionalized with antibodies specific to viral antigens, detects impedance shifts caused by antibody–antigen interactions, providing a highly sensitive platform for viral detection. A high-gain folded-cascade amplifier enhances the Signal-to-Noise Ratio (SNR) to approximately 70 dB, verified through COMSOL and MATLAB simulations. Additionally, a 1D CNN model is employed for adaptive noise reduction, filtering out non-linear noise patterns and achieving an approximate 75% noise reduction across a broad frequency range. The CNN model, implemented on an Altera DE2 FPGA, enables high-throughput, low-latency signal processing, making the system viable for real-time applications. Performance evaluations confirmed the proposed system’s capability to enhance the SNR significantly while maintaining a compact and energy-efficient design suitable for portable diagnostics. This integrated architecture thus provides a powerful solution for high-precision, real-time viral detection, and continuous health monitoring, advancing the role of biosensors in accessible point-of-care diagnostics. Full article

The development of ion-sensitive field-effect transistor (ISFET) sensors based on silicon nanowires (SiNW) has recently seen significant progress, due to their many advantages such as compact size, low cost, robustness and real-time portability. However, little work has been done to predict the performance of SiNW-ISFET sensors. The present study focuses on predicting the performance of the silicon nanowire (SiNW)-based ISFET sensor using four machine learning techniques, namely multilayer perceptron (MLP), nonlinear regression (NLR), support vector regression (SVR) and extra tree regression (ETR). The proposed ML algorithms are trained and validated using experimental measurements of the SiNW-ISFET sensor. The results obtained show a better predictive ability of extra tree regression (ETR) compared to other techniques, with a low RMSE of 1 × 10⁻³ mA and an R² value of 0.9999725. This prediction study corrects the problems associated with SiNW -ISFET sensors. Full article

This study explores the hydrogen generation potential via water-splitting reactions under UV-vis radiation by using a synergistic assembly of ZnO nanoparticles integrated with MoS₂, single-walled carbon nanotubes (SWNTs), and crystalline silicon nanowires (SiNWs) to create the MoS₂-SiNWs-SWNTs@ZnONPs nanocomposites. A comparative analysis of MoS₂ synthesized through chemical and physical exfoliation methods revealed that the chemically exfoliated MoS₂ exhibited superior performance, thereby being selected for all subsequent measurements. The nanostructured materials demonstrated exceptional surface characteristics, with specific surface areas exceeding 300 m² g⁻¹. Notably, the hydrogen production rate achieved by a composite comprising 5% MoS₂, 1.7% SiNWs, and 13.3% SWNTs at an 80% ZnONPs base was approximately 3909 µmol h⁻¹g⁻¹ under 500 nm wavelength radiation, marking a significant improvement of over 40-fold relative to pristine ZnONPs. This enhancement underscores the remarkable photocatalytic efficiency of the composites, maintaining high hydrogen production rates above 1500 µmol h⁻¹g⁻¹ even under radiation wavelengths exceeding 600 nm. Furthermore, the potential of these composites for energy storage and conversion applications, specifically within rechargeable lithium-ion batteries, was investigated. Composites, similar to those utilized for hydrogen production but excluding ZnONPs to address its limited theoretical capacity and electrical conductivity, were developed. The focus was on utilizing MoS₂, SiNWs, and SWNTs as anode materials for Li-ion batteries. This strategic combination significantly improved the electronic conductivity and mechanical stability of the composite. Specifically, the composite with 56% MoS₂, 24% SiNWs, and 20% SWNTs offered remarkable cyclic performance with high specific capacity values, achieving a complete stability of 1000 mA h g⁻¹ after 100 cycles at 1 A g⁻¹. These results illuminate the dual utility of the composites, not only as innovative catalysts for hydrogen production but also as advanced materials for energy storage technologies, showcasing their potential in contributing to sustainable energy solutions. Full article