Lei Li, Yihua Xu, Qunkai Peng, Pei Huang, Xinqing Duan, Mingqiang Wang, Yu Jiang, Jie Wang, Srinivasan Periasamy, Dar-Jen Hsieh and Kuan-Chang Chang*,
{"title":"Biocompatible Acellular Dermal Matrix-Based Neuromorphic Device with Ultralow Voltage, Ion Channel Emulation, and Synaptic Forgetting Visualization Computation","authors":"Lei Li, Yihua Xu, Qunkai Peng, Pei Huang, Xinqing Duan, Mingqiang Wang, Yu Jiang, Jie Wang, Srinivasan Periasamy, Dar-Jen Hsieh and Kuan-Chang Chang*, ","doi":"10.1021/acsnano.4c1038310.1021/acsnano.4c10383","DOIUrl":null,"url":null,"abstract":"<p >Neuromorphic bioelectronics aim to integrate electronics with biological systems yet encounter challenges in biocompatibility, operating voltages, power consumption, and stability. This study presents biocompatible neuromorphic devices fabricated from acellular dermal matrix (ADM) derived from porcine dermis using low-temperature supercritical CO<sub>2</sub> extraction. The ADM preserves the natural scaffold structure of collagen and minimizes immunogenicity by eliminating cells, fats, and noncollagenous impurities, ensuring excellent biocompatibility. The ADM-based devices emulate biological ion channels with biphasic membrane current modulation, exhibiting temperature dependency and pH sensitivity. It operates at an ultralow voltage of 1 mV and demonstrates reliable synaptic modulation exceeding 4 × 10<sup>4</sup> endurance cycles. The activation voltage can be theoretically as low as 59 μV, comparable to brainwave signals with a power of merely 7 aJ/event. Furthermore, a brain-like forgetting visualization algorithm is developed, leveraging the synaptic forgetting plasticity of ADM-based devices to achieve complex computing tasks in a highly energy-efficient manner. Neuromorphic devices based on ADM not only hold potential in implantable biointerfaces due to their exceptional biocompatibility, ultralow voltage, and power but also provide a feasible way for energy-efficient computing paradigms through a synergistic hardware-software approach.</p>","PeriodicalId":21,"journal":{"name":"ACS Nano","volume":"18 45","pages":"31309–31322 31309–31322"},"PeriodicalIF":15.8000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Nano","FirstCategoryId":"88","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsnano.4c10383","RegionNum":1,"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
Neuromorphic bioelectronics aim to integrate electronics with biological systems yet encounter challenges in biocompatibility, operating voltages, power consumption, and stability. This study presents biocompatible neuromorphic devices fabricated from acellular dermal matrix (ADM) derived from porcine dermis using low-temperature supercritical CO2 extraction. The ADM preserves the natural scaffold structure of collagen and minimizes immunogenicity by eliminating cells, fats, and noncollagenous impurities, ensuring excellent biocompatibility. The ADM-based devices emulate biological ion channels with biphasic membrane current modulation, exhibiting temperature dependency and pH sensitivity. It operates at an ultralow voltage of 1 mV and demonstrates reliable synaptic modulation exceeding 4 × 104 endurance cycles. The activation voltage can be theoretically as low as 59 μV, comparable to brainwave signals with a power of merely 7 aJ/event. Furthermore, a brain-like forgetting visualization algorithm is developed, leveraging the synaptic forgetting plasticity of ADM-based devices to achieve complex computing tasks in a highly energy-efficient manner. Neuromorphic devices based on ADM not only hold potential in implantable biointerfaces due to their exceptional biocompatibility, ultralow voltage, and power but also provide a feasible way for energy-efficient computing paradigms through a synergistic hardware-software approach.
期刊介绍:
ACS Nano, published monthly, serves as an international forum for comprehensive articles on nanoscience and nanotechnology research at the intersections of chemistry, biology, materials science, physics, and engineering. The journal fosters communication among scientists in these communities, facilitating collaboration, new research opportunities, and advancements through discoveries. ACS Nano covers synthesis, assembly, characterization, theory, and simulation of nanostructures, nanobiotechnology, nanofabrication, methods and tools for nanoscience and nanotechnology, and self- and directed-assembly. Alongside original research articles, it offers thorough reviews, perspectives on cutting-edge research, and discussions envisioning the future of nanoscience and nanotechnology.