{"title":"用于图像处理和模式识别的空位有序双过氧化物忆阻器","authors":"Wentong Li, Yanyun Ren, Tianwei Duan, Hao Tang, Hao Li, Kaihuan Zhang, Yu Sun, Xiaoyu Zhang, Weitao Zheng, Martyn A. McLachlan, Zhongrui Wang, Yuanyuan Zhou, Jiaqi Zhang","doi":"10.1016/j.matt.2024.10.006","DOIUrl":null,"url":null,"abstract":"High-performance memristors have emerged as efficient hardware for integrating noisy image recognition and noise reduction. Herein, we report a fast-switching memristor featuring tens of nanoseconds switching time fabricated using a vacancy-ordered double perovskite, Cs<sub>2</sub>TiBr<sub>6</sub> nanocrystals. The spatially ordered vacancies in the double perovskite facilitate the predictable formation and rupture of conductive filaments, which are explored through a comprehensive simulation using the finite element analysis physical model. These unique microscopic features suppress random conducting filament growth and enhance bromine vacancy diffusion, boosting memristor switching speed. A further study of synapse-like behaviors reveals that Cs<sub>2</sub>TiBr<sub>6</sub>-based memristors exhibit high robustness and reproducibility. We further developed the crossbar-array memristors as artificial neural networks for image denoising and classification, achieving a 10% increase in recognition accuracy for pre-denoised images over non-denoised samples. Our work highlights the potential of intrinsic vacancy-ordered memristive materials for advancing efficient, real-time, robust visual recognition.","PeriodicalId":17,"journal":{"name":"ACS Infectious Diseases","volume":"213 1","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vacancy-ordered double-perovskite-based memristors for image processing and pattern recognition\",\"authors\":\"Wentong Li, Yanyun Ren, Tianwei Duan, Hao Tang, Hao Li, Kaihuan Zhang, Yu Sun, Xiaoyu Zhang, Weitao Zheng, Martyn A. McLachlan, Zhongrui Wang, Yuanyuan Zhou, Jiaqi Zhang\",\"doi\":\"10.1016/j.matt.2024.10.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-performance memristors have emerged as efficient hardware for integrating noisy image recognition and noise reduction. Herein, we report a fast-switching memristor featuring tens of nanoseconds switching time fabricated using a vacancy-ordered double perovskite, Cs<sub>2</sub>TiBr<sub>6</sub> nanocrystals. The spatially ordered vacancies in the double perovskite facilitate the predictable formation and rupture of conductive filaments, which are explored through a comprehensive simulation using the finite element analysis physical model. These unique microscopic features suppress random conducting filament growth and enhance bromine vacancy diffusion, boosting memristor switching speed. A further study of synapse-like behaviors reveals that Cs<sub>2</sub>TiBr<sub>6</sub>-based memristors exhibit high robustness and reproducibility. We further developed the crossbar-array memristors as artificial neural networks for image denoising and classification, achieving a 10% increase in recognition accuracy for pre-denoised images over non-denoised samples. Our work highlights the potential of intrinsic vacancy-ordered memristive materials for advancing efficient, real-time, robust visual recognition.\",\"PeriodicalId\":17,\"journal\":{\"name\":\"ACS Infectious Diseases\",\"volume\":\"213 1\",\"pages\":\"\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Infectious Diseases\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1016/j.matt.2024.10.006\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Infectious Diseases","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1016/j.matt.2024.10.006","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
Vacancy-ordered double-perovskite-based memristors for image processing and pattern recognition
High-performance memristors have emerged as efficient hardware for integrating noisy image recognition and noise reduction. Herein, we report a fast-switching memristor featuring tens of nanoseconds switching time fabricated using a vacancy-ordered double perovskite, Cs2TiBr6 nanocrystals. The spatially ordered vacancies in the double perovskite facilitate the predictable formation and rupture of conductive filaments, which are explored through a comprehensive simulation using the finite element analysis physical model. These unique microscopic features suppress random conducting filament growth and enhance bromine vacancy diffusion, boosting memristor switching speed. A further study of synapse-like behaviors reveals that Cs2TiBr6-based memristors exhibit high robustness and reproducibility. We further developed the crossbar-array memristors as artificial neural networks for image denoising and classification, achieving a 10% increase in recognition accuracy for pre-denoised images over non-denoised samples. Our work highlights the potential of intrinsic vacancy-ordered memristive materials for advancing efficient, real-time, robust visual recognition.
期刊介绍:
ACS Infectious Diseases will be the first journal to highlight chemistry and its role in this multidisciplinary and collaborative research area. The journal will cover a diverse array of topics including, but not limited to:
* Discovery and development of new antimicrobial agents — identified through target- or phenotypic-based approaches as well as compounds that induce synergy with antimicrobials.
* Characterization and validation of drug target or pathways — use of single target and genome-wide knockdown and knockouts, biochemical studies, structural biology, new technologies to facilitate characterization and prioritization of potential drug targets.
* Mechanism of drug resistance — fundamental research that advances our understanding of resistance; strategies to prevent resistance.
* Mechanisms of action — use of genetic, metabolomic, and activity- and affinity-based protein profiling to elucidate the mechanism of action of clinical and experimental antimicrobial agents.
* Host-pathogen interactions — tools for studying host-pathogen interactions, cellular biochemistry of hosts and pathogens, and molecular interactions of pathogens with host microbiota.
* Small molecule vaccine adjuvants for infectious disease.
* Viral and bacterial biochemistry and molecular biology.