Suppr超能文献

用于神经形态计算智能应用的基于二维MXene的先进传感器

Two-Dimensional MXene-Based Advanced Sensors for Neuromorphic Computing Intelligent Application.

作者信息

Lu Lin, Sun Bo, Wang Zheng, Meng Jialin, Wang Tianyu

机构信息

School of Integrated Circuits, Shandong University, Jinan, 250100, China.

Suzhou Research Institute of Shandong University, Suzhou, 215123, People's Republic of China.

出版信息

Nanomicro Lett. 2025 Sep 12;18(1):64. doi: 10.1007/s40820-025-01902-1.

Abstract

As emerging two-dimensional (2D) materials, carbides and nitrides (MXenes) could be solid solutions or organized structures made up of multi-atomic layers. With remarkable and adjustable electrical, optical, mechanical, and electrochemical characteristics, MXenes have shown great potential in brain-inspired neuromorphic computing electronics, including neuromorphic gas sensors, pressure sensors and photodetectors. This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved. Key bottlenecks such as insufficient long-term stability under environmental exposure, high costs, scalability limitations in large-scale production, and mechanical mismatch in wearable integration hinder their practical deployment. Furthermore, unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neuromorphic signal conversion demand urgent attention. The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.

摘要

作为新兴的二维材料,碳化物和氮化物(MXenes)可以是固溶体或由多原子层组成的组织结构。MXenes具有卓越且可调节的电学、光学、机械和电化学特性,在受大脑启发的神经形态计算电子学领域展现出巨大潜力,包括神经形态气体传感器、压力传感器和光电探测器。本文对MXenes在神经形态传感领域的研究进展进行了前瞻性综述,并讨论了需要解决的关键挑战。诸如在环境暴露下长期稳定性不足、成本高昂、大规模生产中的可扩展性限制以及可穿戴集成中的机械不匹配等关键瓶颈阻碍了它们的实际应用。此外,异质结构中的界面兼容性以及神经形态信号转换中的能量效率低下等未解决问题亟待关注。该综述为未来的研究方向提供了见解,以加深对MXene特性的基本理解,并通过与各种新兴技术融合促进其进一步集成到神经形态计算应用中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b845/12432000/d2b9b5b73f3b/40820_2025_1902_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验