journal article·2021-11-10

Enhancing the Hydrogen-Sensing Performance of p-Type PdO by Modulating the Conduction Model

Shuang Yang, Qian Li, Chao Li, Tianlong Cao, Tieqiang Wang, Fuqiang Fan, Xuemin Zhang, Yu Fu

ACS Applied Materials & Interfaces· Volume 13· Issue 44
Publisher page

Abstract

The implementation of the p-type metal oxide semiconductor (MOS) in modern sensing systems requires a strategy to effectively enhance its inherent low response. However, for p-type MOS sensors, conventional methods such as catalyst nanoparticle (NP) decoration and grain size regulation do not work as effectively as they do for n-type MOS sensors, which is basically due to the fact that the p-type MOS adopts an unfavorable parallel conduction model. Herein, taking Au@PdO as an example, we demonstrate that the conduction model of the p-type MOS can be manipulated into the series conduction model by inserting a high-conductive metallic core into less-conductive p-type MOS NPs. This unique series conduction model makes the sensor response of Au@PdO nanoparticle arrays (NAs) very sensitive to the catalyst NP decoration as well as the change of structural parameters. For example, Au@PdO NAs demonstrate an ∼9000 times increase in sensor response when decorated with Pd NPs, whereas there is only ∼100 times increase for PdO NAs. This greatly improved response value outperforms all previously reported PdO-based (and most other p-type semiconductor-based) H2 sensors, which helps the obtained sensor to achieve an ultralow detection limit of ∼0.1 ppm at room temperature. Additionally, Au@PdO NAs inherit the high surface reactivity and gas adsorption property of p-type PdO. As a result, the as-prepared sensor exhibits high humidity-resistive property and excellent selectivity. This work provides a new strategy to significantly enhance the sensing performance of p-type gas sensors by manipulating their conduction model.
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Research context

OpenAlex topics: Gas Sensing Nanomaterials and Sensors · Advanced Chemical Sensor Technologies · Analytical Chemistry and Sensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110189, P. R. China

Funding

Ministry of Education of the People's Republic of China · China Postdoctoral Science Foundation · State Key Laboratory of Supramolecular Structure and Materials · National Natural Science Foundation of China

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