Low‐Frequency Noise and Stability in Electrolyte‐Gated Nanoscale Silicon Field‐Effect Transistor Sensors

Electrolyte-gated nanoscale silicon field-effect transistors (Si FETs), including silicon nanoribbon FETs (SiNRFETs) and nanowire FETs (SiNWFETs), have emerged as highly promising platforms for chemical and biological sensing. As these sensors move from proof-of-concept demonstrations toward quantitative assays, practical performance is increasingly governed not only by nominal sensitivity, but also by their signal-to-noise ratio (SNR) and baseline stability. Low-frequency noise (LFN), typically arising from carrier-number and mobility fluctuations in the solid-state device, as well as reversible ion adsorption/desorption processes at the solid-liquid interfaces, is generally characterized by an approximately 1/f-dependent power spectral density. It limits the minimum resolvable signal and thus determines the limit-of-detection (LoD). In parallel, slower nonstationary processes, including ion penetration and reference-electrode drift, cause baseline instability that complicates quantitative sensing and array calibration. This review discusses LFN and instability in electrolyte-gated nanoscale Si FET sensors as a coupled device-interface-readout problem. Mitigation strategies are also summarized. Representative examples illustrate how dominant noise sources can be identified and suppressed. Finally, we highlight the applications of low-noise and low-drift FET sensors. Next-generation electrolyte-gated nanoscale Si FET sensors require codesign of the transducer, sensing interface, electrolyte/reference environment, and front-end electronics to achieve a low LoD and high detection accuracy.

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Publication Details

Journal
Small Methods
Published
2026-10-13
DOI
https://doi.org/10.1002/smtd.71112
Primary Topic
Analytical Chemistry and Sensors
Type
article
Field-Weighted Citation Impact
0.00

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article

Low‐Frequency Noise and Stability in Electrolyte‐Gated Nanoscale Silicon Field‐Effect Transistor Sensors

Zheqiang Xu, Paul Michael Solomon, Yingtao Yu, Qitao Hu et al.
Small Methods
Analytical Chemistry and Sensors
article

Low‐Frequency Noise and Stability in Electrolyte‐Gated Nanoscale Silicon Field‐Effect Transistor Sensors

Zheqiang Xu, Paul Michael Solomon, Yingtao Yu, Qitao Hu, Zhen Zhang, Yihan Wang
article en

Abstract

Electrolyte-gated nanoscale silicon field-effect transistors (Si FETs), including silicon nanoribbon FETs (SiNRFETs) and nanowire FETs (SiNWFETs), have emerged as highly promising platforms for chemical and biological sensing. As these sensors move from proof-of-concept demonstrations toward quantitative assays, practical performance is increasingly governed not only by nominal sensitivity, but also by their signal-to-noise ratio (SNR) and baseline stability. Low-frequency noise (LFN), typically arising from carrier-number and mobility fluctuations in the solid-state device, as well as reversible ion adsorption/desorption processes at the solid-liquid interfaces, is generally characterized by an approximately 1/f-dependent power spectral density. It limits the minimum resolvable signal and thus determines the limit-of-detection (LoD). In parallel, slower nonstationary processes, including ion penetration and reference-electrode drift, cause baseline instability that complicates quantitative sensing and array calibration. This review discusses LFN and instability in electrolyte-gated nanoscale Si FET sensors as a coupled device-interface-readout problem. Mitigation strategies are also summarized. Representative examples illustrate how dominant noise sources can be identified and suppressed. Finally, we highlight the applications of low-noise and low-drift FET sensors. Next-generation electrolyte-gated nanoscale Si FET sensors require codesign of the transducer, sensing interface, electrolyte/reference environment, and front-end electronics to achieve a low LoD and high detection accuracy.

Small Methods
Uppsala University (SE), IBM (United States) (US), IBM Research - Thomas J. Watson Research Center (US), Stanford Medicine (US), Stanford University (US)
Vetenskapsrådet
Openalex Percentile: Top 25%
Analytical Chemistry and Sensors
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