NSF Convergence Accelerator Track L: Innovative chemical microsensor development for in situ, real-time monitoring of priority water pollutants to protect water quality

清洁的水对人类生命和大自然的健康和福祉至关重要。然而，人类活动对水质有着深远的影响，往往导致人类和生态系统健康的下降，粮食生产的减少，以及美国和全球贫困的加剧。越来越高的水污染物水平，其中大部分没有得到充分监测，正在造成一种“看不见的水危机”，对低收入社区、部落国家和有色人种社区造成了不成比例的影响。该项目旨在开发一种紧凑的、可定制的化学传感系统，该系统集成了新的微传感器、数据管理和分析技术，以准确量化和显示威胁淡水和管理水系统的人类和生态系统健康的高优先级污染物。这种工程、环境化学、人工智能和水资源管理方面的专业知识和新兴技术的合作，增强了这些实时、具有成本效益的水监测技术的创新。它们的数据输出最终将提高作出及时、知情决定和推动确保社会和地球健康的渐进行动的能力。与不同利益相关者（水倡导非营利组织、资源管理者、部落和州政府团体以及环境工程师）的合作将确保这些微传感器和数据的可访问性和用户友好性，从而使高风险和服务不足的人群受益。该项目将通过先进的微加工技术，利用基于微机电系统的技术，开发小型化的便携式化学传感器，该传感器具有极高的灵敏度（十亿分之一的水平）和对淡水和管理水环境中多种目标污染物（特别是营养物和金属）的特异性。传感器模块和传感器阵列的远程部署将通过利用嵌入式系统设计和超低功耗系统来延长部署的使用寿命，并实现实时数据传输的无线通信。大数据技术将用于确保从这些传感器阵列获得的数据易于访问，准确，组织良好，并可由具有广泛专业知识和需求的最终用户解释，空间人工智能方法将促进水质预测和预测。这种创新的化学传感和数据分析平台将为广泛的应用提供敏感、选择性、实时、可靠和具有成本效益的水质监测。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。

Clean water is essential for the health and wellbeing of human life and of nature. Human activities, however, have far-reaching impacts on water quality, often leading to a decline in human and ecosystem health, reduction in food production, and escalation of poverty throughout the United States and globally. The increasingly high levels of water pollutants, most of which are not adequately monitored, are creating an “invisible water crisis” that disproportionately impacts low-income communities, tribal nations, and communities of color. This project aims to develop a compact, customizable chemical sensing system integrated with new microsensors and data management and analytic technologies to accurately quantify, and make visible, high-priority pollutants that threaten human and ecosystem health of freshwater and managed water systems. This collaboration of expertise and emerging technologies in engineering, environmental chemistry, artificial intelligence, and water resource management enhances the innovation of these real-time, cost-effective water-monitoring technologies. Their data outputs will ultimately improve capabilities for making timely, informed decisions and spurring progressive actions that ensure societal and planetary health. Engagement with diverse stakeholders (water advocacy non-profits, resource managers, tribal and state government groups, and environmental engineers) will ensure that these microsensors and data are accessible and user-friendly to benefit high-risk and underserved populations. Using microelectromechanical systems-based technologies through advanced microfabrication techniques, this project will develop miniaturized, portable chemical sensors with exceptional sensitivity (sub parts-per-billion level) and specificity of multiple target pollutants (specifically, nutrients and metals) in freshwater and managed water environments. Remote deployment of sensor modules and sensor arrays will be enabled by leveraging embedded systems design and ultra-low-power systems advances to extend the lifetime of deployments and enable wireless communications for real-time data transfer. Big Data technologies will be used to ensure that the data obtained from these sensor arrays are readily accessible, accurate, well-organized, and interpretable by end-users with wide-ranging expertise and needs, and spatial artificial intelligence methods will facilitate water quality prediction and forecasting. This innovative chemical sensing and data analytics platform will provide sensitive, selective, real-time, reliable, and cost-effective water quality monitoring for broad applications.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.