论文标题

Prussian蓝色模拟中的可调间隔电荷转移可实现稳定而有效的生物相容性人工突触

Tunable intervalence charge transfer in ruthenium Prussian blue analogue enables stable and efficient biocompatible artificial synapses

论文作者

Robinson, Donald A., Foster, Michael E., Bennett, Christopher H., Bhandarkar, Austin, Webster, Elizabeth R., Celebi, Aleyna, Celebi, Nisa, Fuller, Elliot J., Stavila, Vitalie, Spataru, Catalin D., Ashby, David S., Marinella, Matthew J., Krishnakumar, Raga, Allendorf, Mark D., Talin, A. Alec

论文摘要

神经形态计算,生物电子学和脑部计算机接口的新兴概念激发了新的研究途径,旨在了解未探索材料中氧化状态与电导率之间的关系。在这里,我们介绍了普鲁士蓝蓝色类似物(rupba),这是一种具有开放框架结构的混合价配位化合物,并且能够同时进行离子和电子电荷的能力,用于柔性人工突触,基于电化学上可调节的氧化态,可逆时地切换四个范围的量级。与经过广泛研究的有机聚合物相比,将近两个数量级的保留提高了近两个数量级,从而降低了与误差校正方案相关的频率,复杂性和能量成本。我们证明了使用rupba突触和与神经元细胞的生物相容性的多巴胺检测,从而引起了前瞻性应用脑部计算机接口的应用。通过将电子转移理论应用于间隔电荷转移的原位光谱概率,我们阐明了开关机制,从而在n配位的RU位点之间的混合价值程度控制着载体浓度和迁移率,并由DFT支持。

Emerging concepts for neuromorphic computing, bioelectronics, and brain-computer interfacing inspire new research avenues aimed at understanding the relationship between oxidation state and conductivity in unexplored materials. Here, we present ruthenium Prussian blue analogue (RuPBA), a mixed valence coordination compound with an open framework structure and ability to conduct both ionic and electronic charge, for flexible artificial synapses that reversibly switch conductance by more than four orders of magnitude based on electrochemically tunable oxidation state. Retention of programmed states is improved by nearly two orders of magnitude compared to the extensively studied organic polymers, thus reducing the frequency, complexity and energy costs associated with error correction schemes. We demonstrate dopamine detection using RuPBA synapses and biocompatibility with neuronal cells, evoking prospective application for brain-computer interfacing. By application of electron transfer theory to in-situ spectroscopic probing of intervalence charge transfer, we elucidate a switching mechanism whereby the degree of mixed valency between N-coordinated Ru sites controls the carrier concentration and mobility, as supported by DFT.

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