关键词: LiSiOx dual-ion effect memristor nociceptive blockade nociceptor

Mesh : Humans Nociceptors / physiology Artificial Intelligence Pain Bionics Ions / pharmacology

来  源:   DOI:10.1021/acsami.4c01406

Abstract:
An artificial nociceptor, as a critical and special bionic receptor, plays a key role in a bioelectronic device that detects stimuli and provides warnings. However, fully exploiting bioelectronic applications remains a major challenge due to the lack of the methods of implementing basic nociceptor functions and nociceptive blockade in a single device. In this work, we developed a Pt/LiSiOx/TiN artificial nociceptor. It had excellent stability under the 104 endurance test with pulse stimuli and exhibited a significant threshold current of 1 mA with 1 V pulse stimuli. Other functions such as relaxation, inadaptation, and sensitization were all realized in a single device. Also, the pain blockade function was first achieved in this nociceptor with over a 25% blocking degree, suggesting a self-protection function. More importantly, an obvious depression was activated by a stimulus over 1.6 V due to the cooperative effects of both lithium ions and oxygen ions in LiSiOx and the dramatic accumulation of Joule heat. The conducting channel ruptured partially under sequential potentiation, thus achieving nociceptive blockade, besides basic functions in one single nociceptor, which was rarely reported. These results provided important guidelines for constructing high-performance memristor-based artificial nociceptors and opened up an alternative approach to the realization of bioelectronic systems for artificial intelligence.
摘要:
一种人工伤害感受器,作为一种关键和特殊的仿生受体,在检测刺激并提供警告的生物电子设备中起着关键作用。然而,由于缺乏在单个设备中实现基本伤害感受器功能和伤害感受阻断的方法,充分利用生物电子应用仍然是一个主要挑战。在这项工作中,我们开发了Pt/LiSiOx/TiN人工痛觉感受器。在脉冲刺激的104耐力测试下具有出色的稳定性,并且在1V脉冲刺激下表现出1mA的显着阈值电流。其他功能,如放松,不适应,和敏化都在单个设备中实现。此外,疼痛阻滞功能首先在这种痛觉感受器中实现,阻滞程度超过25%,暗示自我保护功能。更重要的是,由于LiSiOx中锂离子和氧离子的协同作用以及焦耳热的急剧积累,超过1.6V的刺激激活了明显的抑制。传导通道在顺序增强作用下部分破裂,从而实现伤害性阻断,除了一个单一的伤害感受器的基本功能,这很少被报道。这些结果为构建基于高性能忆阻器的人工伤害感受器提供了重要指导,并为实现人工智能的生物电子系统开辟了另一种方法。
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