Shuang Ge, Qiang Wang, Jingyao Bian, Zhuangzhuang Li, Ye Tao, Meng Qi, Zewei Wang, Siyu Liu, Zhongqiang Wang, Yongxing Zhu, Ya Lin, Xiaoning Zhao, Haiyang Xu and Yichun Liu
{"title":"利用MoTe2光电忆阻器与氧等离子体处理进行传感器内储层计算的生物启发多感官融合","authors":"Shuang Ge, Qiang Wang, Jingyao Bian, Zhuangzhuang Li, Ye Tao, Meng Qi, Zewei Wang, Siyu Liu, Zhongqiang Wang, Yongxing Zhu, Ya Lin, Xiaoning Zhao, Haiyang Xu and Yichun Liu","doi":"10.1039/D5TC02712H","DOIUrl":null,"url":null,"abstract":"<p >Biological multimodal perception systems play a pivotal role in environmental interactions through the sophisticated integration of multisensory information. Inspired by this natural paradigm, we demonstrate a breakthrough two-dimensional MoTe<small><sub>2</sub></small>-based optoelectronic memristor capable of synergistically processing infrared optical and electrical signals in a monolithic device – a critical advancement toward artificial multimodal sensing systems. The developed structure demonstrates superior biorealistic synaptic functionalities, including tunable short-term plasticity, paired-pulse facilitation, and spike-time-dependent plasticity through photoelectronic co-modulation. More significantly, we construct a multimodal reservoir computing architecture that synergistically combines optical and electrical inputs, achieving higher pattern recognition accuracy compared to the single mode. This work establishes a new dimension in neuromorphic hardware design through inherent multimodal signal fusion capabilities. Our findings provide fundamental insights into photoelectronic coupling mechanisms while demonstrating practical pathways toward high-efficiency neuromorphic computing systems with biological sensory integration.</p>","PeriodicalId":84,"journal":{"name":"Journal of Materials Chemistry C","volume":" 41","pages":" 21006-21014"},"PeriodicalIF":5.1000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bioinspired multisensory fusion using a MoTe2 optoelectronic memristor with oxygen plasma treatment for in-sensor reservoir computing\",\"authors\":\"Shuang Ge, Qiang Wang, Jingyao Bian, Zhuangzhuang Li, Ye Tao, Meng Qi, Zewei Wang, Siyu Liu, Zhongqiang Wang, Yongxing Zhu, Ya Lin, Xiaoning Zhao, Haiyang Xu and Yichun Liu\",\"doi\":\"10.1039/D5TC02712H\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Biological multimodal perception systems play a pivotal role in environmental interactions through the sophisticated integration of multisensory information. Inspired by this natural paradigm, we demonstrate a breakthrough two-dimensional MoTe<small><sub>2</sub></small>-based optoelectronic memristor capable of synergistically processing infrared optical and electrical signals in a monolithic device – a critical advancement toward artificial multimodal sensing systems. The developed structure demonstrates superior biorealistic synaptic functionalities, including tunable short-term plasticity, paired-pulse facilitation, and spike-time-dependent plasticity through photoelectronic co-modulation. More significantly, we construct a multimodal reservoir computing architecture that synergistically combines optical and electrical inputs, achieving higher pattern recognition accuracy compared to the single mode. This work establishes a new dimension in neuromorphic hardware design through inherent multimodal signal fusion capabilities. Our findings provide fundamental insights into photoelectronic coupling mechanisms while demonstrating practical pathways toward high-efficiency neuromorphic computing systems with biological sensory integration.</p>\",\"PeriodicalId\":84,\"journal\":{\"name\":\"Journal of Materials Chemistry C\",\"volume\":\" 41\",\"pages\":\" 21006-21014\"},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2025-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Materials Chemistry C\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2025/tc/d5tc02712h\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Materials Chemistry C","FirstCategoryId":"1","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2025/tc/d5tc02712h","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Bioinspired multisensory fusion using a MoTe2 optoelectronic memristor with oxygen plasma treatment for in-sensor reservoir computing
Biological multimodal perception systems play a pivotal role in environmental interactions through the sophisticated integration of multisensory information. Inspired by this natural paradigm, we demonstrate a breakthrough two-dimensional MoTe2-based optoelectronic memristor capable of synergistically processing infrared optical and electrical signals in a monolithic device – a critical advancement toward artificial multimodal sensing systems. The developed structure demonstrates superior biorealistic synaptic functionalities, including tunable short-term plasticity, paired-pulse facilitation, and spike-time-dependent plasticity through photoelectronic co-modulation. More significantly, we construct a multimodal reservoir computing architecture that synergistically combines optical and electrical inputs, achieving higher pattern recognition accuracy compared to the single mode. This work establishes a new dimension in neuromorphic hardware design through inherent multimodal signal fusion capabilities. Our findings provide fundamental insights into photoelectronic coupling mechanisms while demonstrating practical pathways toward high-efficiency neuromorphic computing systems with biological sensory integration.
期刊介绍:
The Journal of Materials Chemistry is divided into three distinct sections, A, B, and C, each catering to specific applications of the materials under study:
Journal of Materials Chemistry A focuses primarily on materials intended for applications in energy and sustainability.
Journal of Materials Chemistry B specializes in materials designed for applications in biology and medicine.
Journal of Materials Chemistry C is dedicated to materials suitable for applications in optical, magnetic, and electronic devices.
Example topic areas within the scope of Journal of Materials Chemistry C are listed below. This list is neither exhaustive nor exclusive.
Bioelectronics
Conductors
Detectors
Dielectrics
Displays
Ferroelectrics
Lasers
LEDs
Lighting
Liquid crystals
Memory
Metamaterials
Multiferroics
Photonics
Photovoltaics
Semiconductors
Sensors
Single molecule conductors
Spintronics
Superconductors
Thermoelectrics
Topological insulators
Transistors