Light-optimized photovoltaic self-powered NO2 gas sensing based on black silicon

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date

2021-08-01

Department

Department of Electronics and Nanoengineering

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Language

en

Pages

10

Series

Sensors and Actuators, B: Chemical, Volume 340

Abstract

The NO2 sensing performance of a special lateral photovoltaic self-powered gas sensor based on the N-hyperdoped microstructured silicon (N-Si) is systematically studied under the different light illumination. The dependence of sensing characteristics on light intensity and wavelength is obtained, respectively. Results show that the sensing properties can be changed effectively by the different intensities and wavelengths, suggesting that a multidimensional regulation/optimization for the sensing characteristics is possible by light. More interestingly, the light with wavelength of 940 nm and intensity of ∼18 μW/cm2 could bring a comprehensive optimization for gas sensing, under which the N-Si sensor exhibits the excellent overall performance with simultaneously the low light power needed, good gas response, high sensitivity, wide detectable range and short response time at room temperature.

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Funding Information: This work is supported by the National Natural Science Foundation of China under grant no. 6207030573 , the National Basic Research Program of China (973 Program) under grant no. 2012CB934200 , and the Specialized Research Fund for the Doctoral Program of Higher Education under grant no. 20130071110018 . Publisher Copyright: © 2021 Elsevier B.V. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

Black silicon, Gas sensor, Lateral photovoltaic effect, Nitrogen dioxide, Self-powered gas sensing

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DOI

10.1016/j.snb.2021.129985

Citation

Zhao, Y, Liu, X L, Ma, S X, Wang, W J, Ning, X J, Zhao, L & Zhuang, J 2021, 'Light-optimized photovoltaic self-powered NO 2 gas sensing based on black silicon', Sensors and Actuators, B: Chemical, vol. 340, 129985. https://doi.org/10.1016/j.snb.2021.129985

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https://urn.fi/URN:NBN:fi:aalto-202105056476

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