Surface functionalization is very effective in enhancing sensing properties of a chemiresistive gas sensor. In this work, we develop a novel and cost-effective process to prepare Ag-modified silicon nanowire (SiNW) sensors and further suggest a resistance effect model to clarify the enhanced sensing mechanism of Ag-modified SiNWs. The SiNWs were formed via metal-assisted chemical etching (MACE), and the Ag nanoparticle (NP) modification was achieved in situ based on the MACE-produced Ag dendrites by involving a crucial anisotropic postetching of TMAH. The TMAH etching induces a loose array of needle-like, rough SiNWs (RNWs) with firm attachment of tiny Ag NPs. Comparative investigations for NH-sensing properties indicate that the RNWs modified by discrete Ag NPs (Ag@RNWs) display an ∼3-fold enhancement in gas response at room temperature compared with pristine SiNWs. Meanwhile, transient response and ultrafast recovery are observed for the Ag@RNW sensor (t ≤ 2 s and t ≤ 9 s to 0.33-10 ppm of NH). The study demonstrates the considerable effect and potential of the Ag modification process developed in this work. A resistance effect model was further suggested to clarify the underlying mechanism of the enhanced response and the response saturation characteristic of the Ag@RNWs. The promotion of TMAH etching-induced microstructure modulation to sensing properties was also demonstrated.
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http://dx.doi.org/10.1021/acsami.7b10584 | DOI Listing |
Sensors (Basel)
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.
View Article and Find Full Text PDFNanomaterials (Basel)
November 2024
Faculty of Physics, St. Petersburg State University, Universitetskaya Emb. 13B, 199034 St. Petersburg, Russia.
This study investigates the growth of gallium arsenide nanowires, using lead as a catalyst. Typically, nanowires are grown through the vapor-solid-liquid mechanism, where a key factor is the reduction in the nucleation barrier beneath the catalyst droplet. Arsenic exhibits limited solubility in conventional catalysts; however, this research explores an alternative scenario in which lead serves as a solvent for arsenic, while gallium and lead are immiscible liquids.
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