High-Entropy Perovskite Oxide Photonic Synapses,Advanced Optical Materials

当前位置： X-MOL 学术 › Adv. Opt. Mater. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

High-Entropy Perovskite Oxide Photonic Synapses
Advanced Optical Materials ( IF 8.0 ) Pub Date : 2024-02-22 , DOI: 10.1002/adom.202303248
Zhongwei Bai ₁ , Bingcheng Luo ₁ , Tao Peng ₁ , Jianyuan Wang ₁

Affiliation

High-entropy oxides are garnering increased attention due to their unique properties engineered by chemical disorders. Chemical disorders can cause random potential spatial fluctuations and the resulting anomalous photoconductivity, while they have not yet been exploited in high-entropy oxides for usefulness. In this work, persistent photoconductivity (PPC) behavior in high-entropy perovskite Ba(Zr_0.2Sn_0.2Ti_0.2Hf_0.2Nb_0.2)O₃ thin films is reported and used it as a basis to develop artificial photonic synapses. This photonic synapse can emulate distinctive biological synaptic features such as excitatory postsynaptic current, paired-pulse facilitation, transition from short-term memory to long-term memory, and learning-forgetting processes. This photonic synapse can also implement the basic “AND” and “OR” logic operations. In addition, a 5×5 photonic synaptic array is built to mimic the spatiotemporal sensing and memory functions of a visual sensing-memory system, exhibiting the improved accuracy of dynamic machine vision classification tasks as compared to traditional visual sensing systems. This study highlights the potential of high-entropy oxides for application in neuromorphic computing and dynamic machine vision systems.

中文翻译：

高熵钙钛矿氧化物光子突触

高熵氧化物由于其由化学紊乱引起的独特性质而受到越来越多的关注。化学紊乱会导致随机的潜在空间波动以及由此产生的异常光电导性，但它们尚未在高熵氧化物中得到利用。在这项工作中，高熵钙钛矿Ba(Zr _0.2 Sn _0.2 Ti _0.2 Hf _0.2 Nb中的持久光电导(PPC)行为 _0.2 )O ₃ 薄膜被报道，并将其作为开发人工光子突触的基础。这种光子突触可以模拟独特的生物突触特征，例如兴奋性突触后电流、配对脉冲促进、从短期记忆到长期记忆的转变以及学习遗忘过程。该光子突触还可以实现基本的“AND”和“OR”逻辑运算。此外，还构建了 5×5 光子突触阵列来模拟视觉传感记忆系统的时空传感和记忆功能，与传统视觉传感系统相比，动态机器视觉分类任务的准确性得到了提高。这项研究强调了高熵氧化物在神经形态计算和动态机器视觉系统中应用的潜力。

更新日期：2024-02-22

点击分享查看原文

点击收藏

阅读更多本刊新发论文本刊介绍/投稿指南