DataVXAdvanced Functional MaterialsPaper
journal article·2025-12

Gaussian‐Sigmoid Reinforcement Transistors: Resolving Exploration‐Exploitation Trade‐Off Through Gate Voltage‐Controlled Activation Functions (Adv. Funct. Mater. 49/2025)

Jisoo Park, Juhyung Seo, Ryun‐Han Koo, Dinithi Jayasuriya, Nethmi Jayasinghe, Wonjun Shin, Amit R. Trivedi, Hocheon Yoo

Advanced Functional Materials· Volume 35· Issue 49
Publisher page
Source abstract

Abstract

Gaussian-Sigmoid Reinforcement Transistors In their Research Article (10.1002/adfm.202512407), Wonjun Shin, Amit R. Trivedi, Hocheon Yoo, and co-workers present an organic/inorganic heterostructure transistor with a spatially separating polymer dielectric. The device mimics Gaussian, sigmoid, and mixed activation functions, demonstrating improved reinforcement learning and neural network performance with reduced circuit complexity.
Source: openalex_inverted_index · Quality: baseline

Research context

PolymersElectronic materialsComposites

OpenAlex topics: Advancements in Semiconductor Devices and Circuit Design · Ferroelectric and Negative Capacitance Devices · Advanced Memory and Neural Computing

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Affiliations

Department of Semiconductor Engineering Gachon University 1342 Seongnam‐daero Seongnam 13120 Republic of Korea

Department of Electronic Engineering Hanyang University Seoul 04763 Republic of Korea

Department of Electrical and Computer Engineering and Inter‐University Semiconductor Research Center (ISRC) Seoul National University Seoul 08826 South Korea

Department of Electrical and Computer Engineering University of Illinois Chicago IL 60607 USA

Department of Semiconductor Convergence Engineering Sungkyunkwan University Suwon 16419 Republic of Korea

References

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