{"title":"流体离子器件的进展:对神经形态集成电路设计的启示。","authors":"Honglin Lv, Rui Liu, Yin Zhang","doi":"10.1021/acssensors.5c01063","DOIUrl":null,"url":null,"abstract":"<p><p>Biological brains that use ions as signaling carriers exhibit powerful computing and learning capabilities. Inspired by this, ion-based neuromorphic devices have gained widespread attention. As a neuromorphic device, the fluidic ionic memristor can simulate not only synaptic plasticity but also the transduction of chemical-electrical signals because of unique ions biocompatibility. Furthermore, ionic circuits provide a versatile platform for constructing neural networks, demonstrating significant potential for simulating biologically inspired computations. However, ion-based neuromorphic computational circuits are still in their infancy, and there is an urgent need for comprehensive guidance on their development. In this perspective, we first describe the development of ionic devices and the working principle of fluidic ionic memristors as well as their application in the simulation of biological synapses systematically. We then summarize the construction of neuromorphic computing integrated circuits in a fluidic environment. Finally, a series of solutions to the challenges faced by ionic devices involving performance indexes and the design of neuromorphic circuits are also discussed.</p>","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":" ","pages":""},"PeriodicalIF":8.2000,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advancements in Fluidic Ionic Devices: Implications for Neuromorphic Integrated Circuit Design.\",\"authors\":\"Honglin Lv, Rui Liu, Yin Zhang\",\"doi\":\"10.1021/acssensors.5c01063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Biological brains that use ions as signaling carriers exhibit powerful computing and learning capabilities. Inspired by this, ion-based neuromorphic devices have gained widespread attention. As a neuromorphic device, the fluidic ionic memristor can simulate not only synaptic plasticity but also the transduction of chemical-electrical signals because of unique ions biocompatibility. Furthermore, ionic circuits provide a versatile platform for constructing neural networks, demonstrating significant potential for simulating biologically inspired computations. However, ion-based neuromorphic computational circuits are still in their infancy, and there is an urgent need for comprehensive guidance on their development. In this perspective, we first describe the development of ionic devices and the working principle of fluidic ionic memristors as well as their application in the simulation of biological synapses systematically. We then summarize the construction of neuromorphic computing integrated circuits in a fluidic environment. Finally, a series of solutions to the challenges faced by ionic devices involving performance indexes and the design of neuromorphic circuits are also discussed.</p>\",\"PeriodicalId\":24,\"journal\":{\"name\":\"ACS Sensors\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":8.2000,\"publicationDate\":\"2025-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Sensors\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1021/acssensors.5c01063\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Sensors","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acssensors.5c01063","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
Advancements in Fluidic Ionic Devices: Implications for Neuromorphic Integrated Circuit Design.
Biological brains that use ions as signaling carriers exhibit powerful computing and learning capabilities. Inspired by this, ion-based neuromorphic devices have gained widespread attention. As a neuromorphic device, the fluidic ionic memristor can simulate not only synaptic plasticity but also the transduction of chemical-electrical signals because of unique ions biocompatibility. Furthermore, ionic circuits provide a versatile platform for constructing neural networks, demonstrating significant potential for simulating biologically inspired computations. However, ion-based neuromorphic computational circuits are still in their infancy, and there is an urgent need for comprehensive guidance on their development. In this perspective, we first describe the development of ionic devices and the working principle of fluidic ionic memristors as well as their application in the simulation of biological synapses systematically. We then summarize the construction of neuromorphic computing integrated circuits in a fluidic environment. Finally, a series of solutions to the challenges faced by ionic devices involving performance indexes and the design of neuromorphic circuits are also discussed.
期刊介绍:
ACS Sensors is a peer-reviewed research journal that focuses on the dissemination of new and original knowledge in the field of sensor science, particularly those that selectively sense chemical or biological species or processes. The journal covers a broad range of topics, including but not limited to biosensors, chemical sensors, gas sensors, intracellular sensors, single molecule sensors, cell chips, and microfluidic devices. It aims to publish articles that address conceptual advances in sensing technology applicable to various types of analytes or application papers that report on the use of existing sensing concepts in new ways or for new analytes.