{"title":"Artificial nociceptor based on interface engineered ferroelectric volatile memristor","authors":"Joonbong Lee, Myeong Seop Song, Woo-Sung Jang, Hojin Lee, Sangwoo Lee, Turgun Boynazarov, Young-Min Kim, Seung Chul Chae, Haider Abbas, Taekjib Choi","doi":"10.1016/j.apmt.2024.102346","DOIUrl":null,"url":null,"abstract":"Recent advancements in neuromorphic computing driven by memristors, which emulate biological synapses and neurons, have spurred the development of innovative information technologies. To extend memristor applications to artificial nervous systems, electronic receptors are crucial for converting external stimuli into signals for the internal nervous system. Key requirements for integrating neuron devices into neuromorphic computing include achieving threshold behavior, minimizing power consumption, and ensuring compatibility with complementary metal-oxide semiconductor (CMOS) technology. Hafnium-based ferroelectric memristors are known for their robust ferroelectric properties at nanoscales and compatibility with CMOS technology. However, their non-volatile resistive switching has historically limited their suitability for neuron sensory applications requiring threshold switching. This study demonstrates threshold switching behavior in a TiN/HfZrO(HZO)/TiO/TiN heterostructure by incorporating a nanoscale TiO interfacial layer as an oxygen reservoir. This layer facilitates the formation of oxygen vacancies within the ferroelectric HZO layer, serving as internal charge trap sites. As a result, hafnium-based ferroelectric memristors exhibit volatile switching characteristics, enabling them to function as nociceptive devices through internal charge trapping and detrapping mechanisms. These volatile memristors are suitable for artificial nociceptor systems requiring responses such as threshold detection, relaxation, allodynia, and hyperalgesia to external stimuli. This capability opens avenues for developing advanced humanoid robots capable of rapid adaptation and response in challenging environments such as outer space or hazardous conditions, leveraging real-time sensory processing for effective operation and survival.","PeriodicalId":8066,"journal":{"name":"Applied Materials Today","volume":"13 1","pages":""},"PeriodicalIF":7.2000,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Materials Today","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1016/j.apmt.2024.102346","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Recent advancements in neuromorphic computing driven by memristors, which emulate biological synapses and neurons, have spurred the development of innovative information technologies. To extend memristor applications to artificial nervous systems, electronic receptors are crucial for converting external stimuli into signals for the internal nervous system. Key requirements for integrating neuron devices into neuromorphic computing include achieving threshold behavior, minimizing power consumption, and ensuring compatibility with complementary metal-oxide semiconductor (CMOS) technology. Hafnium-based ferroelectric memristors are known for their robust ferroelectric properties at nanoscales and compatibility with CMOS technology. However, their non-volatile resistive switching has historically limited their suitability for neuron sensory applications requiring threshold switching. This study demonstrates threshold switching behavior in a TiN/HfZrO(HZO)/TiO/TiN heterostructure by incorporating a nanoscale TiO interfacial layer as an oxygen reservoir. This layer facilitates the formation of oxygen vacancies within the ferroelectric HZO layer, serving as internal charge trap sites. As a result, hafnium-based ferroelectric memristors exhibit volatile switching characteristics, enabling them to function as nociceptive devices through internal charge trapping and detrapping mechanisms. These volatile memristors are suitable for artificial nociceptor systems requiring responses such as threshold detection, relaxation, allodynia, and hyperalgesia to external stimuli. This capability opens avenues for developing advanced humanoid robots capable of rapid adaptation and response in challenging environments such as outer space or hazardous conditions, leveraging real-time sensory processing for effective operation and survival.
期刊介绍:
Journal Name: Applied Materials Today
Focus:
Multi-disciplinary, rapid-publication journal
Focused on cutting-edge applications of novel materials
Overview:
New materials discoveries have led to exciting fundamental breakthroughs.
Materials research is now moving towards the translation of these scientific properties and principles.