Unlocking Predictive Capability and Enhancing Sensing Performances of Plasmonic Hydrogen Sensors via Phase Space Reconstruction and Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Unlocking Predictive Capability and Enhancing Sensing Performances of Plasmonic Hydrogen Sensors via Phase Space Reconstruction and Convolutional Neural Networks

Published:2024-05-14 Issue:8 Volume:9 Page:3877-3888
ISSN:2379-3694
Container-title:ACS Sensors
language:en
Short-container-title:ACS Sens.

Author:

Lin Xiangxin¹,Cheng Mingyu¹,Chen Xinyi¹^ORCID,Zhang Jinglan¹,Zhao Yiping²^ORCID,Ai Bin¹^ORCID

Affiliation:

1. School of Microelectronics and Communication Engineering, Chongqing Key Laboratory of Bio-perception & Intelligent Information Processing, Chongqing University, Chongqing 400044 , P.R. China

2. Department of Physics and Astronomy, The University of Georgia, Athens, Georgia 30602 , United States

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acssensors.3c02651

Reference53 articles.

1. Homogeneous Catalysis for Sustainable Energy: Hydrogen and Methanol Economies, Fuels from Biomass, and Related Topics

2. Hydrogen energy future: Advancements in storage technologies and implications for sustainability

3. Chemiresistive Hydrogen Sensors: Fundamentals, Recent Advances, and Challenges

4. Hydrogen gas sensing methods, materials, and approach to achieve parts per billion level detection: A review

5. Plasmonic Hydrogen Sensors

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