从原子模拟中设计具有超快神经形态特征的极性纹理

S. Prosandeev, S. Prokhorenko, Y. Nahas, Yali Yang, Changsong Xu, J. Grollier, D. Talbayev, B. Dkhil, L. Bellaiche
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引用次数: 2

摘要

这篇综述总结了最近的工作,所有使用特定的原子方法,预测和解释了当三种典型的偶极材料受到太赫兹激发时,神经形态计算的关键特征的发生。提供了这种原子方法背后的主要思想,并给出了模型弛豫铁电体、反铁电体和正常铁电体的说明,强调了极性材料作为神经形态计算候选者的重要潜力。本综述特别强调了神经形态特征与渗透理论、能量路径的局部最小值、拓扑跃迁和/或非谐振子模型之间的联系,这取决于所研究的材料。通过考虑三种不同的主要极性材料家族,这项工作为设计基于极性的神经形态系统提供了一个完整和创新的工具箱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing polar textures with ultrafast neuromorphic features from atomistic simulations
This review summarizes recent works, all using a specific atomistic approach, that predict and explain the occurrence of key features for neuromorphic computing in three archetypical dipolar materials, when they are subject to THz excitations. The main ideas behind such atomistic approach are provided, and illustration of model relaxor ferroelectrics, antiferroelectrics, and normal ferroelectrics are given, highlighting the important potential of polar materials as candidates for neuromorphic computing. Some peculiar emphases are made in this Review, such as the connection between neuromorphic features and percolation theory, local minima in energy path, topological transitions and/or anharmonic oscillator model, depending on the material under investigation. By considering three different and main polar material families, this work provides a complete and innovative toolbox for designing polar-based neuromorphic systems.
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CiteScore
5.90
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