Minseo Noh, Yongjin Byun, Gimun Kim, Junhyeok Park, Sungjoon Kim* and Sungjun Kim*,
{"title":"用于多比特神经形态和边缘计算的具有干扰抑制脉冲方案的阵列集成忆阻器","authors":"Minseo Noh, Yongjin Byun, Gimun Kim, Junhyeok Park, Sungjoon Kim* and Sungjun Kim*, ","doi":"10.1021/acsaelm.5c01300","DOIUrl":null,"url":null,"abstract":"<p >In this study, we developed a Pt/Al/TiO<sub><i>y</i></sub>/TiO<sub><i>x</i></sub>/HfO<sub>2</sub>/Pt memristor device featuring an optimized annealing process and an integrated TiO<sub><i>y</i></sub> overshoot layer to mitigate current overshoot during electroforming, achieving current-compliant-free and forming-free features. Extensive characterization demonstrated stable resistive switching properties, including a high on/off ratio (∼10), reliable retention, and endurance across a 24 × 24 crossbar array. Multilevel cell operation enabled precise programming, achieving up to 6-bit levels through the Incremental Step Pulse with Verify Algorithm (ISPVA) method. The device’s synaptic potential was further evaluated using the Extended Modified National Institute of Standards and Technology (EMNIST) data set. ISPVA-based training achieved superior classification accuracy of 92.6% for a subset (<i>N</i> = 6) and 83.34% for the full alphabet (<i>N</i> = 26), outperforming conventional incremental pulse methods. Furthermore, resistive switching voltage range-based program sequencing makes weight transfer accurate. These findings highlight the Pt/Al/TiO<sub><i>y</i></sub>/TiO<sub><i>x</i></sub>/HfO<sub>2</sub>/Pt memristor as a core synaptic element for scalable, high-density, and energy-efficient neuromorphic computing systems.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":"7 17","pages":"8211–8226"},"PeriodicalIF":4.7000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Array-Integrated Memristor with an Interference-Suppressed Pulse Scheme for Multibit Neuromorphic and Edge Computing\",\"authors\":\"Minseo Noh, Yongjin Byun, Gimun Kim, Junhyeok Park, Sungjoon Kim* and Sungjun Kim*, \",\"doi\":\"10.1021/acsaelm.5c01300\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >In this study, we developed a Pt/Al/TiO<sub><i>y</i></sub>/TiO<sub><i>x</i></sub>/HfO<sub>2</sub>/Pt memristor device featuring an optimized annealing process and an integrated TiO<sub><i>y</i></sub> overshoot layer to mitigate current overshoot during electroforming, achieving current-compliant-free and forming-free features. Extensive characterization demonstrated stable resistive switching properties, including a high on/off ratio (∼10), reliable retention, and endurance across a 24 × 24 crossbar array. Multilevel cell operation enabled precise programming, achieving up to 6-bit levels through the Incremental Step Pulse with Verify Algorithm (ISPVA) method. The device’s synaptic potential was further evaluated using the Extended Modified National Institute of Standards and Technology (EMNIST) data set. ISPVA-based training achieved superior classification accuracy of 92.6% for a subset (<i>N</i> = 6) and 83.34% for the full alphabet (<i>N</i> = 26), outperforming conventional incremental pulse methods. Furthermore, resistive switching voltage range-based program sequencing makes weight transfer accurate. These findings highlight the Pt/Al/TiO<sub><i>y</i></sub>/TiO<sub><i>x</i></sub>/HfO<sub>2</sub>/Pt memristor as a core synaptic element for scalable, high-density, and energy-efficient neuromorphic computing systems.</p>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":\"7 17\",\"pages\":\"8211–8226\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2025-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acsaelm.5c01300\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"88","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsaelm.5c01300","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Array-Integrated Memristor with an Interference-Suppressed Pulse Scheme for Multibit Neuromorphic and Edge Computing
In this study, we developed a Pt/Al/TiOy/TiOx/HfO2/Pt memristor device featuring an optimized annealing process and an integrated TiOy overshoot layer to mitigate current overshoot during electroforming, achieving current-compliant-free and forming-free features. Extensive characterization demonstrated stable resistive switching properties, including a high on/off ratio (∼10), reliable retention, and endurance across a 24 × 24 crossbar array. Multilevel cell operation enabled precise programming, achieving up to 6-bit levels through the Incremental Step Pulse with Verify Algorithm (ISPVA) method. The device’s synaptic potential was further evaluated using the Extended Modified National Institute of Standards and Technology (EMNIST) data set. ISPVA-based training achieved superior classification accuracy of 92.6% for a subset (N = 6) and 83.34% for the full alphabet (N = 26), outperforming conventional incremental pulse methods. Furthermore, resistive switching voltage range-based program sequencing makes weight transfer accurate. These findings highlight the Pt/Al/TiOy/TiOx/HfO2/Pt memristor as a core synaptic element for scalable, high-density, and energy-efficient neuromorphic computing systems.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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