{"title":"Electrosynthesis of Ru (II)-Polypyridyl Oligomeric Films on ITO Electrode for Two Terminal Non-Volatile Memory Devices and Neuromorphic Computing.","authors":"Pradeep Sachan, Pritish Sharma, Rajwinder Kaur, Debashree Manna, Shubham Sahay, Prakash Chandra Mondal","doi":"10.1002/smtd.202401911","DOIUrl":null,"url":null,"abstract":"<p><p>Molecular electronics exhibiting resistive-switching memory features hold great promise for the next generation of digital technology. In this work, electrosynthesis of ruthenium polypyridyl nanoscale oligomeric films is demonstrated on an indium tin oxide (ITO) electrode followed by an ITO top contact deposition yielding large-scale (junction area = 0.7 × 0.7 cm<sup>2</sup>) two terminal molecular junctions. The molecular junctions exhibit non-volatile resistive switching at a relatively lower operational voltage, ±1 V, high ON/OFF electrical current ratio (≈10<sup>3</sup>), low-energy consumption (SET/RESET = 27.94/14400 nJ), good cyclic stability (>300 cycles), and switching speed (SET/RESET = 25 ms/20 ms). A computational study suggests that accessible frontier molecular orbitals of metal-complex to the Fermi level of ITO electrodes facilitate charge transport at a relatively lower bias followed by a filamentformation. An extensive analysis is performed of the performance of binary neural networks exploiting the current-voltage features of the devices as binary synaptic weights and exploring their potential for neuromorphic logic-in-memory implementation of IMPLICATION (IMPLY) operation which can realize universal gates. The comprehensive analysis indicates that the proposed redox-active complex-based memory device may be a promising candidate for high-density data storage, energy-efficient implementation of neuromorphic networks with software-level accuracy, and logic-in-memory implementations.</p>","PeriodicalId":229,"journal":{"name":"Small Methods","volume":" ","pages":"e2401911"},"PeriodicalIF":10.7000,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Small Methods","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/smtd.202401911","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Molecular electronics exhibiting resistive-switching memory features hold great promise for the next generation of digital technology. In this work, electrosynthesis of ruthenium polypyridyl nanoscale oligomeric films is demonstrated on an indium tin oxide (ITO) electrode followed by an ITO top contact deposition yielding large-scale (junction area = 0.7 × 0.7 cm2) two terminal molecular junctions. The molecular junctions exhibit non-volatile resistive switching at a relatively lower operational voltage, ±1 V, high ON/OFF electrical current ratio (≈103), low-energy consumption (SET/RESET = 27.94/14400 nJ), good cyclic stability (>300 cycles), and switching speed (SET/RESET = 25 ms/20 ms). A computational study suggests that accessible frontier molecular orbitals of metal-complex to the Fermi level of ITO electrodes facilitate charge transport at a relatively lower bias followed by a filamentformation. An extensive analysis is performed of the performance of binary neural networks exploiting the current-voltage features of the devices as binary synaptic weights and exploring their potential for neuromorphic logic-in-memory implementation of IMPLICATION (IMPLY) operation which can realize universal gates. The comprehensive analysis indicates that the proposed redox-active complex-based memory device may be a promising candidate for high-density data storage, energy-efficient implementation of neuromorphic networks with software-level accuracy, and logic-in-memory implementations.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.