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  5. Dynamic-Depleted Transistor Empowering Logic-in-Coding Computing

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Article
en
2025

Dynamic-Depleted Transistor Empowering Logic-in-Coding Computing

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en
2025
Vol 19 (49)
Vol. 19
DOI: 10.1021/acsnano.5c17139

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Lin Gu
Lin Gu

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Hang Zhao
Wenhui Tang
Xiaofu Wei
+9 more

Abstract

Reconfigurable transistors are crucial for the development of high-computing-power and highly flexible logic circuits. However, conventional reconfigurable transistors, which operate in either partially depleted or fully depleted states, are limited to basic logic functions. This often requires additional circuits to switch functions, resulting in circuit redundancy and high-power consumption. Here, we propose a dynamic-depletion transistor architecture that realizes the five reconfigurable logic functions through electrostatic modulation of carrier depletion profiles. By precisely regulating the electrostatic potential of the control gate, the spatial distribution of charge carriers within the two-dimensional (2D) channel can be precisely tailored. This modulation effectively screens the electrostatic fields of other gates, thereby enabling transitions between fully depleted and partially depleted states within the same device. The dynamic switching behavior of the depletion state in the 2D WSe2 transistor enables up to five functional integrations. Furthermore, these circuits can represent standard digital functions through inverse and additive reconfigurable logic operations, utilizing only 40 and 25% of the transistor count compared with complementary metal oxide semiconductor circuits. Building on this architecture, the designed circuit can be extended to implement a suite of reconfigurable digital image processing tasks, demonstrating a proof-of-concept for designing low-integration yet high-computing-power RLCs.

How to cite this publication

Hang Zhao, Wenhui Tang, Xiaofu Wei, Gao Li, Mengyu Hong, Huihui Yu, Qinghua Zhang, Lin Gu, Zhihong Cao, Xiankun Zhang, Zheng Zhang, Yue Zhang (2025). Dynamic-Depleted Transistor Empowering Logic-in-Coding Computing. , 19(49), DOI: https://doi.org/10.1021/acsnano.5c17139.

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Publication Details

Type

Article

Year

2025

Authors

12

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsnano.5c17139

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