Tilt‐Engineered Molecular‐Scale Selector for Enhanced Learning in Artificial Neural Networks

Miniaturization of individual selectors in crossbar‐array‐based artificial neural networks is essential for the advancement of the underlying neuromorphic electronics, as it improves learning, recognition, and prediction accuracies. This study proposes a tilt‐engineered molecular‐scale selector comp...

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Bibliographic Details
Published in:	Advanced functional materials Vol. 34; no. 16
Main Authors:	Eo, Jung Sun, Shin, Jaeho, Jeon, Takgyeong, Jang, Jingon, Wang, Gunuk
Format:	Journal Article
Language:	English
Published:	Hoboken Wiley Subscription Services, Inc 01.04.2024
Subjects:	Arrays artificial neural network Artificial neural networks Atomic radius Configurations crossbar array Heterojunctions Heterostructures Learning Mathematical analysis molecular heterojunction molecular tilt configuration molecular‐scale selector Molybdenum disulfide Neural networks Pattern recognition Selectors
ISSN:	1616-301X, 1616-3028
Online Access:	Get full text
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