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Nano Research 2024, 17(4): 3079-3086 https://doi.org/10.1007/s12274-023-6148-2
Research Article | Issue | Published: 23 October 2023

Electrolyte-gated SrCoOx FET sensor for highly sensitive detecting pH in extreme alkalinity solution

Show Author's Information Han Zhou,  Gaocan Qi( ),  Wenbin Li,  Yuhang Wang,  Zhihao Yuan( )
School of Materials Science and Engineering, Tianjin Key Lab of Photoelectric Materials & Devices, and Key Laboratory of Display Materials and Photoelectric Devices (Ministry of Education), Tianjin University of Technology, Tianjin 300384, China
Keywords:
pH sensor, extreme alkaline solution, oxygen-ion migration, field-effect-transistor (FET), SrCoOx
Topics:
Crystal defectsCrystalline materials Field effect transistorsGelspH sensorsSemiconducting films
Cite this article:
Zhou H, Qi G, Li W, et al. Electrolyte-gated SrCoOx FET sensor for highly sensitive detecting pH in extreme alkalinity solution. Nano Research, 2024, 17(4): 3079-3086. https://doi.org/10.1007/s12274-023-6148-2
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Abstract Full text Electronic supplementary material About this article

The pH monitoring is significantly important in chemical industry, biological process, and pollution treatment. However, it remains a great challenge to measure pH in extreme alkalinity conditions. Herein, we employ an electrolyte-gated field-effect-transistor (FET) strategy using non-stoichiometric SrCoOx with rich oxygen-vacancy defects as channel materials for detecting extreme alkalinity. The corresponding channel can provide effective oxygen-ion-migration sites for reversible transformation of OH− ↔ O2− + H+ driven by electric field. The resultant electrolyte-gated FET sensor exhibits a sensitive linear response to high concentrations of alkaline solution, 1–20 M. Significantly, the sensor has the ability to directly indicate the pH values ranging from 14.0 to 17.0 in consideration of ion-activity coefficient data. This work offers a great possibility for directly detecting base concentration as well as pH values in extreme alkaline solutions.


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Electronic supplementary material
About this article

Electrolyte-gated SrCoOx FET sensor for highly sensitive detecting pH in extreme alkalinity solution

Show Author's information Han Zhou, Gaocan Qi( ), Wenbin Li, Yuhang Wang, Zhihao Yuan( )
School of Materials Science and Engineering, Tianjin Key Lab of Photoelectric Materials & Devices, and Key Laboratory of Display Materials and Photoelectric Devices (Ministry of Education), Tianjin University of Technology, Tianjin 300384, China

Abstract

The pH monitoring is significantly important in chemical industry, biological process, and pollution treatment. However, it remains a great challenge to measure pH in extreme alkalinity conditions. Herein, we employ an electrolyte-gated field-effect-transistor (FET) strategy using non-stoichiometric SrCoOx with rich oxygen-vacancy defects as channel materials for detecting extreme alkalinity. The corresponding channel can provide effective oxygen-ion-migration sites for reversible transformation of OH− ↔ O2− + H+ driven by electric field. The resultant electrolyte-gated FET sensor exhibits a sensitive linear response to high concentrations of alkaline solution, 1–20 M. Significantly, the sensor has the ability to directly indicate the pH values ranging from 14.0 to 17.0 in consideration of ion-activity coefficient data. This work offers a great possibility for directly detecting base concentration as well as pH values in extreme alkaline solutions.

Keywords: pH sensor, extreme alkaline solution, oxygen-ion migration, field-effect-transistor (FET), SrCoOx

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Publication history
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Acknowledgements

Publication history

Received: 16 August 2023
Revised: 30 August 2023
Accepted: 30 August 2023
Published: 23 October 2023
Issue date: April 2024

Copyright

© Tsinghua University Press 2023

Acknowledgements

Acknowledgements

This work was supported by the National Nature Science Foundation of China (No. 21501132), the Natural Science Foundation of Tianjin City (No. 20JCZDJC00280), and the National Key R&D Program of China (No. 2017YFA0700104). We are grateful to Dr. Xudong Zhao, Dr. Jia He and Dr. Yuehu Wang from Tianjin University of Technology for their technical assistance and valuable discussions on DFT calculations.

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