{"title":"分子晶体忆阻器。","authors":"Lanhao Qin, Pengfei Guan, Jiefan Shao, Yu Xiao, Yimeng Yu, Jie Su, Conghui Zhang, Yanyong Li, Shenghong Liu, Pengyu Li, Decai Ouyang, Wenke He, Fenghao Liu, Kaichen Zhu, Kailang Liu, Zhenpeng Yao, Jinsong Wu, Yinghe Zhao, Huiqiao Li, Fei Hui, Peng Lin, Mario Lanza, Yuan Li, Tianyou Zhai","doi":"10.1038/s41565-025-02013-z","DOIUrl":null,"url":null,"abstract":"<p><p>Memristors have emerged as a promising hardware platform for in-memory computing, but many current devices suffer from channel material degradation during repeated resistive switching. This leads to high energy consumption and limited endurance. Here we introduce a molecular crystal memristor, of which the representative channel material, Sb<sub>2</sub>O<sub>3</sub>, possesses a molecular crystal structure where molecular cages are interconnected via van der Waals forces. This unique configuration allows ions to migrate through intermolecular spaces with relatively low energy input, preserving the integrity of the crystal structure even after extensive switching cycles. Our molecular crystal memristor thus exhibits low energy consumption of 26 zJ per operation, with prominent endurance surpassing 10<sup>9</sup> switching cycles. The device delivers both reconfigurable non-volatile and volatile resistive switching behaviours over a broad range of device scales, from micrometres down to nanometres. Furthermore, we establish the scalability of this technology by fabricating large crossbar arrays on an 8 inch wafer. This enables the successful implementation of reservoir computing on a single CMOS-integrated chip using these memristors, achieving 100% accuracy in dynamic vision recognition.</p>","PeriodicalId":18915,"journal":{"name":"Nature nanotechnology","volume":" ","pages":""},"PeriodicalIF":34.9000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Molecular crystal memristors.\",\"authors\":\"Lanhao Qin, Pengfei Guan, Jiefan Shao, Yu Xiao, Yimeng Yu, Jie Su, Conghui Zhang, Yanyong Li, Shenghong Liu, Pengyu Li, Decai Ouyang, Wenke He, Fenghao Liu, Kaichen Zhu, Kailang Liu, Zhenpeng Yao, Jinsong Wu, Yinghe Zhao, Huiqiao Li, Fei Hui, Peng Lin, Mario Lanza, Yuan Li, Tianyou Zhai\",\"doi\":\"10.1038/s41565-025-02013-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Memristors have emerged as a promising hardware platform for in-memory computing, but many current devices suffer from channel material degradation during repeated resistive switching. This leads to high energy consumption and limited endurance. Here we introduce a molecular crystal memristor, of which the representative channel material, Sb<sub>2</sub>O<sub>3</sub>, possesses a molecular crystal structure where molecular cages are interconnected via van der Waals forces. This unique configuration allows ions to migrate through intermolecular spaces with relatively low energy input, preserving the integrity of the crystal structure even after extensive switching cycles. Our molecular crystal memristor thus exhibits low energy consumption of 26 zJ per operation, with prominent endurance surpassing 10<sup>9</sup> switching cycles. The device delivers both reconfigurable non-volatile and volatile resistive switching behaviours over a broad range of device scales, from micrometres down to nanometres. Furthermore, we establish the scalability of this technology by fabricating large crossbar arrays on an 8 inch wafer. This enables the successful implementation of reservoir computing on a single CMOS-integrated chip using these memristors, achieving 100% accuracy in dynamic vision recognition.</p>\",\"PeriodicalId\":18915,\"journal\":{\"name\":\"Nature nanotechnology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":34.9000,\"publicationDate\":\"2025-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature nanotechnology\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1038/s41565-025-02013-z\",\"RegionNum\":1,\"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":"Nature nanotechnology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1038/s41565-025-02013-z","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Memristors have emerged as a promising hardware platform for in-memory computing, but many current devices suffer from channel material degradation during repeated resistive switching. This leads to high energy consumption and limited endurance. Here we introduce a molecular crystal memristor, of which the representative channel material, Sb2O3, possesses a molecular crystal structure where molecular cages are interconnected via van der Waals forces. This unique configuration allows ions to migrate through intermolecular spaces with relatively low energy input, preserving the integrity of the crystal structure even after extensive switching cycles. Our molecular crystal memristor thus exhibits low energy consumption of 26 zJ per operation, with prominent endurance surpassing 109 switching cycles. The device delivers both reconfigurable non-volatile and volatile resistive switching behaviours over a broad range of device scales, from micrometres down to nanometres. Furthermore, we establish the scalability of this technology by fabricating large crossbar arrays on an 8 inch wafer. This enables the successful implementation of reservoir computing on a single CMOS-integrated chip using these memristors, achieving 100% accuracy in dynamic vision recognition.
期刊介绍:
Nature Nanotechnology is a prestigious journal that publishes high-quality papers in various areas of nanoscience and nanotechnology. The journal focuses on the design, characterization, and production of structures, devices, and systems that manipulate and control materials at atomic, molecular, and macromolecular scales. It encompasses both bottom-up and top-down approaches, as well as their combinations.
Furthermore, Nature Nanotechnology fosters the exchange of ideas among researchers from diverse disciplines such as chemistry, physics, material science, biomedical research, engineering, and more. It promotes collaboration at the forefront of this multidisciplinary field. The journal covers a wide range of topics, from fundamental research in physics, chemistry, and biology, including computational work and simulations, to the development of innovative devices and technologies for various industrial sectors such as information technology, medicine, manufacturing, high-performance materials, energy, and environmental technologies. It includes coverage of organic, inorganic, and hybrid materials.