Thermoelectric materials interconvert thermal gradients and electric fields for power generation or for refrigeration. Thermoelectrics currently find only niche applications because of their limited efficiency, which is measured by the dimensionless parameter ZT-a function of the Seebeck coefficient or thermoelectric power, and of the electrical and thermal conductivities. Maximizing ZT is challenging because optimizing one physical parameter often adversely affects another. Several groups have achieved significant improvements in ZT through multi-component nanostructured thermoelectrics, such as Bi(2)Te(3)/Sb(2)Te(3) thin-film superlattices, or embedded PbSeTe quantum dot superlattices. Here we report efficient thermoelectric performance from the single-component system of silicon nanowires for cross-sectional areas of 10 nm x 20 nm and 20 nm x 20 nm. By varying the nanowire size and impurity doping levels, ZT values representing an approximately 100-fold improvement over bulk Si are achieved over a broad temperature range, including ZT approximately 1 at 200 K. Independent measurements of the Seebeck coefficient, the electrical conductivity and the thermal conductivity, combined with theory, indicate that the improved efficiency originates from phonon effects. These results are expected to apply to other classes of semiconductor nanomaterials.
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http://dx.doi.org/10.1038/nature06458 | DOI Listing |
Sensors (Basel)
January 2025
Department of Computer Science, Faculty of Sciences and Humanities Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.
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.
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December 2024
CNRS, LAAS, 7 Avenue du Colonel Roche, F-31400 Toulouse, France.
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).
View Article and Find Full Text PDFChem Commun (Camb)
January 2025
Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou 510006, China.
We fabricated flexible, three-dimensional (3D) ordered silicon nanowire (SiNW) arrays decorated with high-density silver nanoparticles (AgNPs) for the sensitive and reproducible detection of pesticide residues. These sensors demonstrated a detection limit of 10 M for methyl parathion (MPT) on curved surfaces.
View Article and Find Full Text PDFAnal Chem
December 2024
School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, PR China.
Conventional wearable flexible sensing systems typically comprise three components: a flexible substrate that contacts the skin, a signal processing module, and a signal output module. These components function relatively independently, resulting in a complex system that lacks sufficient integration. Therefore, developing an integrated wearable flexible sensing system by combining the flexible substrate, the signal processing module, and the signal output module not only enhances performance and comfort, but also reduces manufacturing costs and the risk of failure.
View Article and Find Full Text PDFNanomaterials (Basel)
November 2024
Instituto de Ciencia de Materiales Nicolás Cabrera, Universidad Autónoma de Madrid, 28049 Madrid, Spain.
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 MoS, single-walled carbon nanotubes (SWNTs), and crystalline silicon nanowires (SiNWs) to create the MoS-SiNWs-SWNTs@ZnONPs nanocomposites. A comparative analysis of MoS synthesized through chemical and physical exfoliation methods revealed that the chemically exfoliated MoS exhibited superior performance, thereby being selected for all subsequent measurements. The nanostructured materials demonstrated exceptional surface characteristics, with specific surface areas exceeding 300 m g.
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