High-Performance Proton Field-Effect Transistor Based on Two-Dimensional Cd Vacancy-Resided Cd<sub>0.85</sub>PS<sub>3</sub>Li<sub>0.15</sub>H<sub>0.15</sub>

Ion transport is a critical phenomenon underpinning numerous biological, physical, and chemical systems. Proton transistors leveraging proton transport face significant limitations, such as a low on-off ratio and deficient carrier mobility, which restrict their applicability in biological and other scenarios. This study explores the use of two-dimensional (2D) vacancy-residing transition metal phosphorus trichallcogenide-based membranes as the active layer for proton field-effect transistors. The synthesized Cd<sub>0.85</sub>PS<sub>3</sub>Li<sub>0.15</sub>H<sub>0.15</sub> membrane exhibits a well-organized layered structure and high hydrophilicity, with nanometer-sized interlayers containing interconnected water networks. These distinct features facilitate proton conduction, leading to a high proton conductivity value of 0.83 S cm<sup>-1</sup> at 98% relative humidity and 90 °C, with an activation energy of 0.26 eV. The Cd<sub>0.85</sub>PS<sub>3</sub>Li<sub>0.15</sub>H<sub>0.15</sub>-based proton transistor demonstrates tunability via gate voltage, thereby enabling effective modulation of proton flow across source and drain electrodes. The transistor notably showcases superior switching characteristics, with an on/off ratio surpassing 5.51 and a carrier mobility of 8.84 × 10<sup>-2</sup> cm<sup>2</sup> V<sup>-1</sup> s<sup>-1</sup>. The underlying mechanism for this performance enhancement is attributed to electric-field-induced switching in Cd vacancies. This research boosts the development of highly versatile ionotropic devices by introducing advanced 2D ion-conductive membranes.

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Publication Details

Journal
ACS Nano
Published
2024-08-15
DOI
https://doi.org/10.1021/acsnano.4c03649
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.21

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article

High-Performance Proton Field-Effect Transistor Based on Two-Dimensional Cd Vacancy-Resided Cd0.85PS3Li0.15H0.15

Wenhao Shi, Xitang Qian, Chenhui Huang, Lei Ye et al.
1 citations
ACS Nano
Advanced Memory and Neural Computing
0.21
article

High-Performance Proton Field-Effect Transistor Based on Two-Dimensional Cd Vacancy-Resided Cd0.85PS3Li0.15H0.15

Wenhao Shi, Xitang Qian, Chenhui Huang, Lei Ye, Meng Zhang, Xiangshui Miao, Chuankai Zou
article en
1 citations

Abstract

Ion transport is a critical phenomenon underpinning numerous biological, physical, and chemical systems. Proton transistors leveraging proton transport face significant limitations, such as a low on-off ratio and deficient carrier mobility, which restrict their applicability in biological and other scenarios. This study explores the use of two-dimensional (2D) vacancy-residing transition metal phosphorus trichallcogenide-based membranes as the active layer for proton field-effect transistors. The synthesized Cd<sub>0.85</sub>PS<sub>3</sub>Li<sub>0.15</sub>H<sub>0.15</sub> membrane exhibits a well-organized layered structure and high hydrophilicity, with nanometer-sized interlayers containing interconnected water networks. These distinct features facilitate proton conduction, leading to a high proton conductivity value of 0.83 S cm<sup>-1</sup> at 98% relative humidity and 90 °C, with an activation energy of 0.26 eV. The Cd<sub>0.85</sub>PS<sub>3</sub>Li<sub>0.15</sub>H<sub>0.15</sub>-based proton transistor demonstrates tunability via gate voltage, thereby enabling effective modulation of proton flow across source and drain electrodes. The transistor notably showcases superior switching characteristics, with an on/off ratio surpassing 5.51 and a carrier mobility of 8.84 × 10<sup>-2</sup> cm<sup>2</sup> V<sup>-1</sup> s<sup>-1</sup>. The underlying mechanism for this performance enhancement is attributed to electric-field-induced switching in Cd vacancies. This research boosts the development of highly versatile ionotropic devices by introducing advanced 2D ion-conductive membranes.

ACS NanoVol. 18(34)
Hong Kong University of Science and Technology (HK), Huazhong University of Science and Technology (CN), University of Hong Kong (HK), University of South China (CN)
National Natural Science Foundation of China, University of South China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 49%
Advanced Memory and Neural Computing
0.21
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