MXene-Ti3C2Tx-Based Neuromorphic Computing: Physical Mechanisms, Performance Enhancement, and Cutting-Edge Computing

Highlights This review reveals the advantages of MXene-Ti3C2Tx for neuromorphic devices, classifies the core physical mechanisms, and outlines strategies to drive targeted optimization and future innovation. The review outlines three key engineering strategies: doping engineering, interfacial engine...

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Bibliographic Details
Main Authors: Kaiyang Wang, Shuhui Ren, Yunfang Jia, Xiaobing Yan, Lizhen Wang, Yubo Fan
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:Nano-Micro Letters
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Online Access:https://doi.org/10.1007/s40820-025-01787-0
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Summary:Highlights This review reveals the advantages of MXene-Ti3C2Tx for neuromorphic devices, classifies the core physical mechanisms, and outlines strategies to drive targeted optimization and future innovation. The review outlines three key engineering strategies: doping engineering, interfacial engineering, and structural engineering, while also providing comprehensive guidance for material and device improvement. MXene-Ti3C2Tx-based devices demonstrate groundbreaking potential in next-generation computing, such as near-sensor computing and in-sensor computing, enabling faster and more energy-efficient data processing directly at the sensor level.
ISSN:2311-6706
2150-5551