SemiSynbio-II: Toward Biological-Level Power in Information Processing, Storage, Sensing and Bio-interfacing

SemiSynbio-II：在信息处理、存储、传感和生物接口方面迈向生物级能力

• 批准号: 2027102
• 负责人: Jun Yao
• 金额: $ 147.43万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2027102&HistoricalAwards=false
• 关键词: SemiSynbio; II; Toward; Biological; Level

Nontechnical Abstract:The electrical systems that living organisms employ for bio- computations, such as sensing, intelligent responsiveness, and adaptation, require much less power than currently available man-made electronic systems. This project is developing ultralow-power electronic components and systems for signal retrieval, processing, and storage with power consumption comparable to biological systems. The project takes a fundamentally new approach to improving computing efficiency and storage capacity that can form the basis for self-sustained living or hybrid micro-electronic systems. These electronics that have power requirements similar to biology can naturally interface with biological systems, which is important for potential applications in brain-mimic computation, self-sustained microbots, advanced human-machine interfaces, and prosthetics. The interdisciplinary nature of the research provides an excellent platform for outreach and broadening participation in STEM education. Technical Abstract:Bioinspired electronics, such as sensing, computing, and memory devices, have generated substantial interest because of their potential high efficiency in information retrieval, processing, and storage. Although functional emulation of biological systems has led to many emerging high-performance electronic devices, there is a fundamental difference in the signal amplitude and power requirements. Biological signal processing, such as sensory detection, neural computation, and memory consolidation, uses action potentials (50-100 mV) that approach the thermodynamic limit, whereas conventional electronic systems function with much higher amplitude ( 0.5 V). As a result, the functional emulation of biosystems has not yet reached the ultralow-power information processing found in biosystems, ultimately limiting the integration density or capacity of computation and storage. The goal of the project is to investigate mechanisms and integrate principles in synthetic materials, electronics, and biology to realize computing devices, memory, and sensors that can function at biological-power levels. Borrowing materials and principles from microbes, the general method is to develop hybrid electronic materials, components, and systems. The research team employs specific approaches including: (i) harnessing catalytic principles in microbial systems to lower the functional voltage in electronics, (ii) incorporating bio-derived materials in devices to improve performance, and (iii) creating efficient interfaces between electronics and microbes to enable self-supported systems. These advances are expected to establish the foundation for future ultralow-power information processing, which is fundamentally related to the ultimate computing efficiency and storage capacity.This SemiSynBio-II program (NSF 20-518) grant supports research on biological signal processing, such as sensory detection, neural computation, and memory consolidation with funding from the Division of Materials Research (DMR) of the Mathematical and Physical Sciences Directorate (MPS), the Division of Molecular and Cellular Biosciences (MCB) of the Biological Sciences Directorate (BIO),the Division of Computing and Communication Foundations (CCF) of the Computer and Information Science and Engineering Directorate (CISE), and the Division of Electrical,Communications and Cyber Systems (ECCS) of the Engineering Directorate (ENG).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非技术摘要：生物有机体用于生物计算的电气系统，如传感、智能响应和适应，比目前可用的人造电子系统需要更少的功率。该项目正在开发超低功耗电子元件和系统，用于信号检索、处理和存储，其功耗可与生物系统相媲美。该项目采用了一种全新的方法来提高计算效率和存储容量，可以形成自我维持生活或混合微电子系统的基础。这些具有类似于生物学的电力需求的电子设备可以自然地与生物系统进行交互，这对于模拟大脑计算、自我维持的微型机器人、先进的人机界面和假肢的潜在应用非常重要。该研究的跨学科性质为拓展和扩大STEM教育的参与提供了一个极好的平台。技术摘要：生物启发电子学，如传感、计算和存储设备，由于其在信息检索、处理和存储方面的潜在高效率而引起了极大的兴趣。虽然生物系统的功能仿真导致了许多新兴的高性能电子设备，但在信号幅度和功率要求方面存在根本差异。生物信号处理，如感官检测、神经计算和记忆巩固，使用接近热力学极限的动作电位（50-100 mV），而传统的电子系统则使用更高的振幅（0.5 V）。因此，生物系统的功能模拟尚未达到生物系统中的超低功耗信息处理，最终限制了计算和存储的集成密度或容量。该项目的目标是研究合成材料、电子学和生物学的机制和整合原理，以实现可以在生物功率水平上运行的计算设备、存储器和传感器。借鉴微生物的材料和原理，一般的方法是开发混合电子材料、组件和系统。研究团队采用的具体方法包括：(i)利用微生物系统中的催化原理来降低电子设备中的功能电压，（ii）在设备中加入生物衍生材料以提高性能，以及（iii）在电子设备和微生物之间创建有效的接口以实现自我支持系统。这些进展有望为未来的超低功耗信息处理奠定基础，这从根本上与最终的计算效率和存储容量有关。该SemiSynBio-II项目（NSF 20-518）资助支持生物信号处理的研究，如感官检测、神经计算和记忆巩固，由数学和物理科学理事会（MPS）材料研究部（DMR）资助。生物科学局（BIO）的分子和细胞生物科学部（MCB），计算机和信息科学与工程局（CISE）的计算和通信基础部（CCF），以及工程局（ENG）的电气、通信和网络系统部（ECCS）。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Recent progress in bio-voltage memristors working with ultralow voltage of biological amplitude

生物振幅超低电压生物电压忆阻器的最新进展

• DOI: 10.1039/d2nr06773k
• 发表时间: 2023
• 期刊: Nanoscale
• 影响因子: 6.7
• 作者: Fu, Tianda;Fu, Shuai;Yao, Jun
• 通讯作者: Yao, Jun

Generic Air‐Gen Effect in Nanoporous Materials for Sustainable Energy Harvesting from Air Humidity

纳米多孔材料中的通用空气-发电机效应，用于从空气湿度中可持续收集能量

• DOI: 10.1002/adma.202300748
• 发表时间: 2023
• 期刊: Advanced Materials
• 影响因子: 29.4
• 作者: Liu, Xiaomeng;Gao, Hongyan;Sun, Lu;Yao, Jun
• 通讯作者: Yao, Jun