Junmei Du , Bai Sun , Chuan Yang , Zelin Cao , Guangdong Zhou , Hongyan Wang , Yuanzheng Chen
{"title":"铁电记忆电阻器及其神经形态计算应用","authors":"Junmei Du , Bai Sun , Chuan Yang , Zelin Cao , Guangdong Zhou , Hongyan Wang , Yuanzheng Chen","doi":"10.1016/j.mtphys.2024.101607","DOIUrl":null,"url":null,"abstract":"<div><div>Ferroelectric memristors, characterized by spontaneous polarization ferroelectric materials as a functional layer of memristor, yields unique ferroelectric resistive switching behaviours under a reversal electric field. This device demonstrates notable capability in the stable and precise emulation of synaptic and neuronal functions, analogous to those in the human brain, offering an attractive option for neuromorphic computing. With the development of nanotechnology and nano-ferroelectric materials, the advent of nano-ferroelectric memristors enables their incorporation into dense crossbar arrays, enhancing the density and efficiency of neuromorphic computing. In this review, we offer a comprehensive overview of ferroelectric memristor and its neuromorphic computing applications, including the recent progress, existing challenges and possible solutions, as well as future development direction.</div></div>","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"50 ","pages":"Article 101607"},"PeriodicalIF":10.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ferroelectric memristor and its neuromorphic computing applications\",\"authors\":\"Junmei Du , Bai Sun , Chuan Yang , Zelin Cao , Guangdong Zhou , Hongyan Wang , Yuanzheng Chen\",\"doi\":\"10.1016/j.mtphys.2024.101607\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Ferroelectric memristors, characterized by spontaneous polarization ferroelectric materials as a functional layer of memristor, yields unique ferroelectric resistive switching behaviours under a reversal electric field. This device demonstrates notable capability in the stable and precise emulation of synaptic and neuronal functions, analogous to those in the human brain, offering an attractive option for neuromorphic computing. With the development of nanotechnology and nano-ferroelectric materials, the advent of nano-ferroelectric memristors enables their incorporation into dense crossbar arrays, enhancing the density and efficiency of neuromorphic computing. In this review, we offer a comprehensive overview of ferroelectric memristor and its neuromorphic computing applications, including the recent progress, existing challenges and possible solutions, as well as future development direction.</div></div>\",\"PeriodicalId\":18253,\"journal\":{\"name\":\"Materials Today Physics\",\"volume\":\"50 \",\"pages\":\"Article 101607\"},\"PeriodicalIF\":10.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials Today Physics\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2542529324002839\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Today Physics","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2542529324002839","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}
Ferroelectric memristor and its neuromorphic computing applications
Ferroelectric memristors, characterized by spontaneous polarization ferroelectric materials as a functional layer of memristor, yields unique ferroelectric resistive switching behaviours under a reversal electric field. This device demonstrates notable capability in the stable and precise emulation of synaptic and neuronal functions, analogous to those in the human brain, offering an attractive option for neuromorphic computing. With the development of nanotechnology and nano-ferroelectric materials, the advent of nano-ferroelectric memristors enables their incorporation into dense crossbar arrays, enhancing the density and efficiency of neuromorphic computing. In this review, we offer a comprehensive overview of ferroelectric memristor and its neuromorphic computing applications, including the recent progress, existing challenges and possible solutions, as well as future development direction.
期刊介绍:
Materials Today Physics is a multi-disciplinary journal focused on the physics of materials, encompassing both the physical properties and materials synthesis. Operating at the interface of physics and materials science, this journal covers one of the largest and most dynamic fields within physical science. The forefront research in materials physics is driving advancements in new materials, uncovering new physics, and fostering novel applications at an unprecedented pace.