2D materials-based 3D integration for neuromorphic hardware

IF 9.1 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Seung Ju Kim, Hyeon-Ji Lee, Chul-Ho Lee, Ho Won Jang
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引用次数: 0

Abstract

Neuromorphic hardware enables energy-efficient computing, which is essential for a sustainable system. Recently, significant progress has been reported in neuromorphic hardware based on two-dimensional materials. However, traditional planar-integrated architectures still suffer from high energy consumption. This review systematically explores recent advances in the three-dimensional integration of two-dimensional material-based neuromorphic hardware to address these challenges. The materials, process, device physics, array, and integration levels are discussed, highlighting challenges and perspectives.

Abstract Image

基于二维材料的神经形态硬件三维集成
神经形态硬件可实现高能效计算,这对可持续系统至关重要。最近,基于二维材料的神经形态硬件取得了重大进展。然而,传统的平面集成架构仍然存在能耗高的问题。本综述系统地探讨了基于二维材料的神经形态硬件三维集成的最新进展,以应对这些挑战。文章讨论了材料、工艺、器件物理、阵列和集成等层面的问题,重点介绍了面临的挑战和发展前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
npj 2D Materials and Applications
npj 2D Materials and Applications Engineering-Mechanics of Materials
CiteScore
14.50
自引率
2.10%
发文量
80
审稿时长
15 weeks
期刊介绍: npj 2D Materials and Applications publishes papers on the fundamental behavior, synthesis, properties and applications of existing and emerging 2D materials. By selecting papers with the potential for impact, the journal aims to facilitate the transfer of the research of 2D materials into wide-ranging applications.
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