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基于可再生材料的用于尖峰神经网络的具有短期和长期记忆功能的人工突触。

Artificial Synapses with Short- and Long-Term Memory for Spiking Neural Networks Based on Renewable Materials.

机构信息

Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH) , Pohang 790-784, Republic of Korea.

出版信息

ACS Nano. 2017 Sep 26;11(9):8962-8969. doi: 10.1021/acsnano.7b03347. Epub 2017 Aug 28.

Abstract

Emulation of biological synapses that perform memory and learning functions is an essential step toward realization of bioinspired neuromorphic systems. Artificial synaptic devices have been developed based mostly on inorganic materials and conventional semiconductor device fabrication processes. Here, we propose flexible biomemristor devices based on lignin by a simple solution process. Lignin is one of the most abundant organic polymers on Earth and is biocompatible, biodegradable, as well as environmentally benign. This memristor emulates several essential synaptic behaviors, including analog memory switching, short-term plasticity, long-term plasticity, spike-rate-dependent plasticity, and short-term to long-term transition. A flexible lignin-based artificial synapse device can be operated without noticeable degradation under mechanical bending test. These results suggest lignin can be a promising key component for artificial synapses and flexible electronic devices.

摘要

生物突触的模拟,其具有记忆和学习功能,是实现仿生神经形态系统的重要步骤。基于无机材料和传统半导体器件制造工艺,已经开发出了人工突触器件。在这里,我们通过简单的溶液处理方法,提出了基于木质素的柔性生物忆阻器器件。木质素是地球上最丰富的有机聚合物之一,具有生物相容性、可生物降解性和环境友好性。这种忆阻器模拟了几种基本的突触行为,包括模拟存储开关、短期可塑性、长期可塑性、脉冲速率依赖性可塑性以及短期到长期的转变。在机械弯曲测试下,基于木质素的柔性人工突触器件在操作时没有明显的退化。这些结果表明木质素可以作为人工突触和柔性电子器件的有前途的关键组件。

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