NSF Convergence Accelerator track L: Translating insect olfaction principles into practical and robust chemical sensing platforms

NSF 融合加速器轨道 L：将昆虫嗅觉原理转化为实用且强大的化学传感平台

• 批准号: 2344284
• 负责人: Baranidharan Raman
• 金额: $ 65万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2344284&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; track; Translating

This project seeks to develop a novel sensor that can be used for sensing explosive volatile organic compounds. The sensor will use insect-inspired, nanoparticle-based sensor technology along with artificial intelligence (AI). This work will be the initial step towards a the next-generation e-nose technology for non-invasive chemical sensing, with application to biomedicine, security, environmental monitoring, climate change technologies, and the flavor and food industry. This convergence project is providing opportunities to (i) identify avenues of integration between chemical, physical, biological, and data sciences to create a translatable technology; (ii) pave the way for increased partnerships between academia, industry, national labs, nonprofit organization, and other stakeholders; (iii) lay the seeds for the development of the next-generation electronic noses with large sensor arrays and incorporation of biologically inspired design and computing principles; and (iv) train the next generation of scientists and entrepreneurs. This research will synthesize highly reliable and reproducible sensing elements based on biological sensing principles of robust odor recognition observed in an insect-olfactory system. To address the key challenges in the field of chemical sensing, the proposed research will facilitate the convergence of two key concepts: (i) a scalable approach for synthesizing a large nanostructured chemical sensor array with diverse functionality, and (ii) incorporation of key sensing and AI principles that we have identified in the insect olfactory system over the past 15 years. The short-term goal is to fabricate and demonstrate a proof-of-concept, portable AI-enabled e-nose device that can be used for data collection and validation. Performance metrics such as dose-response curves, limit of detection, classification performance, and receiver operating characteristic curves will be established for a panel of targeted compounds. A library of known signatures for various explosive vapors at appropriate concentration ranges (few ppb – tens of ppm) will be generated.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.

该项目旨在开发一种新型传感器，该传感器可用于感应爆炸性挥发性有机化合物。该传感器将使用昆虫启发的基于纳米颗粒的传感器技术以及人工智能（AI）。这项工作将是迈向非侵入化学感官的下一代电子鼻技术的第一步，并应用生物医学，安全性，环境监测，气候变化技术以及风味和食品行业。这个融合项目为（i）确定化学，物理，生物学和数据科学之间的整合途径以创建可翻译技术； （ii）为增加学术界，工业，国家实验室，非营利组织和其他利益相关者之间的合作伙伴关系铺平道路； （iii）将种子铺设，以开发具有大型传感器阵列以及生物启发的设计和计算原理的基础设施的下一代电子鼻子； （iv）培训下一代科学家和企业家。这项研究将基于在绝缘 - 富尔科系统中观察到的强大气味识别的生物敏感性原理，合成高度可靠和可重复的传感器元素。为了应对化学传感器领域的关键挑战，拟议的研究将促进两个关键概念的收敛：（i）一种可扩展的方法，用于合成具有不同功能的大型纳米结构化学传感器阵列，（ii）我们在过去15年中鉴定出了密钥敏感性和AI原理。短期目标是制造和演示可用于数据收集和验证的概念验证验证的EI-NOSE设备。诸如剂量反应曲线，检测限，分类性能和接收器操作特征曲线之类的性能指标将用于一组目标化合物。将生成适当浓度范围的各种爆炸蒸气的已知签名图书馆（很少PPB - ppm）。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛的影响审查标准来评估来获得珍贵的支持。