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可用于感测爆炸性挥发性有机化合物的新型传感器，该传感器将使用受昆虫启发的纳米颗粒传感器技术以及人工智能（AI）。用于非侵入性化学传感的下一代电子鼻技术，应用于生物医学、安全、环境监测、气候变化技术以及风味和食品行业。该融合项目提供了以下机会：(i) 确定两者之间的整合途径。化学、物理、生物和数据科学，以创建可转化技术；(ii) 为学术界、工业界、国家实验室、非营利组织和其他利益相关者之间加强合作铺平道路；(iii) 为下一代电子技术的发展奠定基础；具有大型传感器阵列并结合受生物学启发的设计和计算原理的鼻子；以及（iv）培训下一代科学家和企业家，该研究将基于在气味识别中观察到的生物传感原理合成高度可靠和可重复的传感元件。为了解决化学传感领域的关键挑战，拟议的研究将促进两个关键概念的融合：（i）合成具有多种功能的大型纳米结构化学传感器阵列的可扩展方法，以及（ii） ）结合了我们在过去 15 年中在昆虫嗅觉系统中发现的关键传感和人工智能原理。短期目标是制造和展示一个概念验证的便携式人工智能系统。将为一组目标化合物建立可用于数据收集和验证的性能指标，例如剂量反应曲线、检测限、分类性能和接收者操作特征曲线。会产生适当浓度范围（几 ppb – 几十 ppm）的各种爆炸性蒸气。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。