{"title":"Improvement of weight update and retention characteristics of Pr0.7Ca0.3MnO3-X ECRAM via elevated temperature training","authors":"Chuljun Lee, Seojin Cho, Daeseok Lee","doi":"10.1039/d4nr03264k","DOIUrl":null,"url":null,"abstract":"To achieve both excellent analog switching for training and retention for inference simultaneously, we investigated elevated-temperature (ET) training of Pr<small><sub>0.7</sub></small>Ca<small><sub>0.3</sub></small>MnO<small><sub>3-X</sub></small> (PCMO) electrochemical random access memory (ECRAM). Improved weight update characteristics can be obtained by thermally reduced ionic resistivity of the HfO<small><sub>x</sub></small> electrolyte at ET (413 K). Furthermore, excellent retention characteristics (10<small><sup>8</sup></small> s) was confirmed at room temperature, which can be explained by enhanced ion storage within the reservoir (or channel) layer via ET training. By adopting ET training on PCMO ECRAM, we can meet both training and inference accuracy of neural networks (NNs).","PeriodicalId":92,"journal":{"name":"Nanoscale","volume":"248 1","pages":""},"PeriodicalIF":5.8000,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nanoscale","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1039/d4nr03264k","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
To achieve both excellent analog switching for training and retention for inference simultaneously, we investigated elevated-temperature (ET) training of Pr0.7Ca0.3MnO3-X (PCMO) electrochemical random access memory (ECRAM). Improved weight update characteristics can be obtained by thermally reduced ionic resistivity of the HfOx electrolyte at ET (413 K). Furthermore, excellent retention characteristics (108 s) was confirmed at room temperature, which can be explained by enhanced ion storage within the reservoir (or channel) layer via ET training. By adopting ET training on PCMO ECRAM, we can meet both training and inference accuracy of neural networks (NNs).
期刊介绍:
Nanoscale is a high-impact international journal, publishing high-quality research across nanoscience and nanotechnology. Nanoscale publishes a full mix of research articles on experimental and theoretical work, including reviews, communications, and full papers.Highly interdisciplinary, this journal appeals to scientists, researchers and professionals interested in nanoscience and nanotechnology, quantum materials and quantum technology, including the areas of physics, chemistry, biology, medicine, materials, energy/environment, information technology, detection science, healthcare and drug discovery, and electronics.