Semyon V. Bachinin, Sergey S. Rzhevskiy, Ivan Sergeev, Svyatoslav A. Povarov, Alena N. Kulakova, Anastasia Lubimova, Varvara Kharitonova and Valentin A. Milichko
{"title":"用于加密逻辑运算的基于 MOF 的误差补偿 ReRAM 阵列","authors":"Semyon V. Bachinin, Sergey S. Rzhevskiy, Ivan Sergeev, Svyatoslav A. Povarov, Alena N. Kulakova, Anastasia Lubimova, Varvara Kharitonova and Valentin A. Milichko","doi":"10.1039/D4DT02880E","DOIUrl":null,"url":null,"abstract":"<p >Metal–organic frameworks (MOFs) form a unique platform for operation with data using ReRAM technology. Here we report on a large-scale fabrication of a MOF-based ReRAM array with 6 × 6 cells, demonstrating 50% variation in their electronic parameters. Despite this inhomogeneity, such a “non-ideal” ReRAM array is used for recording binary information followed by deep learning processes to achieve 95% accuracy of reading. Next, the same ReRAM array is used to record numbers (from 0 to 15) followed by the operation of addition. For the correct performance of such an analogue algorithm, we determine a set of unique coefficients for each ReRAM cell, allowing us to use this set as an encrypted key to get access to logical operations. The obtained results, thereby, demonstrate the possibility of “non-ideal” MOF-based ReRAM for low error reading of information coupled with encrypted logical operations.</p>","PeriodicalId":71,"journal":{"name":"Dalton Transactions","volume":" 4","pages":" 1418-1424"},"PeriodicalIF":3.5000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Error compensated MOF-based ReRAM array for encrypted logical operations†\",\"authors\":\"Semyon V. Bachinin, Sergey S. Rzhevskiy, Ivan Sergeev, Svyatoslav A. Povarov, Alena N. Kulakova, Anastasia Lubimova, Varvara Kharitonova and Valentin A. Milichko\",\"doi\":\"10.1039/D4DT02880E\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Metal–organic frameworks (MOFs) form a unique platform for operation with data using ReRAM technology. Here we report on a large-scale fabrication of a MOF-based ReRAM array with 6 × 6 cells, demonstrating 50% variation in their electronic parameters. Despite this inhomogeneity, such a “non-ideal” ReRAM array is used for recording binary information followed by deep learning processes to achieve 95% accuracy of reading. Next, the same ReRAM array is used to record numbers (from 0 to 15) followed by the operation of addition. For the correct performance of such an analogue algorithm, we determine a set of unique coefficients for each ReRAM cell, allowing us to use this set as an encrypted key to get access to logical operations. The obtained results, thereby, demonstrate the possibility of “non-ideal” MOF-based ReRAM for low error reading of information coupled with encrypted logical operations.</p>\",\"PeriodicalId\":71,\"journal\":{\"name\":\"Dalton Transactions\",\"volume\":\" 4\",\"pages\":\" 1418-1424\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dalton Transactions\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2025/dt/d4dt02880e\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, INORGANIC & NUCLEAR\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dalton Transactions","FirstCategoryId":"92","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2025/dt/d4dt02880e","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, INORGANIC & NUCLEAR","Score":null,"Total":0}
Error compensated MOF-based ReRAM array for encrypted logical operations†
Metal–organic frameworks (MOFs) form a unique platform for operation with data using ReRAM technology. Here we report on a large-scale fabrication of a MOF-based ReRAM array with 6 × 6 cells, demonstrating 50% variation in their electronic parameters. Despite this inhomogeneity, such a “non-ideal” ReRAM array is used for recording binary information followed by deep learning processes to achieve 95% accuracy of reading. Next, the same ReRAM array is used to record numbers (from 0 to 15) followed by the operation of addition. For the correct performance of such an analogue algorithm, we determine a set of unique coefficients for each ReRAM cell, allowing us to use this set as an encrypted key to get access to logical operations. The obtained results, thereby, demonstrate the possibility of “non-ideal” MOF-based ReRAM for low error reading of information coupled with encrypted logical operations.
期刊介绍:
Dalton Transactions is a journal for all areas of inorganic chemistry, which encompasses the organometallic, bioinorganic and materials chemistry of the elements, with applications including synthesis, catalysis, energy conversion/storage, electrical devices and medicine. Dalton Transactions welcomes high-quality, original submissions in all of these areas and more, where the advancement of knowledge in inorganic chemistry is significant.