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| U.S.-RoI-NI R&D Partnership: Ultrasensitive Nitrogen Sensor using Imprinted Polymer Assisted-Bacteria for Real-Time Monitoring of Water Quality | |
| 项目编号 | 2130661 |
| Rick Relyea | |
| 项目主持机构 | Rensselaer Polytechnic Institute |
| 开始日期 | 2021-10-01 |
| 结束日期 | 09/30/2024 |
| 英文摘要 | An award is made to Rensselaer Polytechnic Institute to integrate four research groups from the three nations (the United States, Republic of Ireland and Northern Ireland, UK) to collaboratively design, build, validate, and field test a sensor system for the real-time detection of the three most commonly monitored forms of nitrogen: nitrate, nitrite, and ammonia/ammonium. Across the globe, freshwater and marine ecosystems are threatened by the effects of multiple environmental stressors including pollutants, invasive species, climate change, acidification, and excess nutrients. Excess nutrients are of particular importance since they are a driver of harmful algal blooms and “dead zones,” which are increasingly occurring around the world and can tip ecosystems toward significant and potentially catastrophic ecological events. While scientists strive to monitor, understand, and model the effects of excess nutrients, the current major challenge is to frequently monitor nitrogen [N] and phosphorus [P]) dynamics using real-time sensors at a reasonable cost. Having high-frequency, real-time nutrient data would allow basic and applied researchers around the world to integrate nutrient data with other data from existing sensor networks and remote sensing to address the global challenge of harmful algal blooms and dead zones. The research will also integration exciting K-12 outreach efforts among the four research groups. Using team experts from different disciplines, the groups will work together to create educational modules that spiral knowledge from basic to advanced information to educate and engage broadly. These groups will create week-long summer programs that integrate in-person and virtual educational experiences for high school students and college undergraduates to learn about the importance of analytical chemistry, engineering, and limnology to produce new generations of aquatic sensors. Students will visit and participate in the research of state-of-the-art facilities at Queen’s University, Dublin City University, and Rensselaer, as well as the sensor network that has been deployed by RPI on Lake George, NY (in collaboration with IBM Research and The Lake George Association). Most nutrient monitoring today by researchers depends on collecting water samples infrequently and bringing them back to the lab for benchtop testing. Newer technologies for measuring nutrients in aquatic ecosystems are single-use or require the frequent replacement of reagents. Moreover, the few nutrient sensors that are field-deployable with real-time data—such as phosphorus sensors—have a high cost ($30k) that strongly limits the number of nutrient sensors that can be deployed. Aquatic researchers need real-time, high-frequency, low-cost nutrient sensors with low detection limits that can be embedded in existing sensor networks that monitor suites of other water variables. This research team proposes to build a single sensor that uses 1) polymers to separate and concentrate each form of nitrogen, 2) bacteria to convert each form of nitrogen into a single form (i.e., nitrite), 3) advanced 3D printed microfluidics to ensure routes toward the active sensor in a complete analyzer platform for field deployment, and 4) a more sensitive detection system using novel ultrasensitive detectors. Monitoring the real-time dynamics of aquatic nutrients in complex natural environments has the potential to bring transformative new insights into how these nutrients impact aquatic ecosystems, with a focus on the global issue of harmful algal blooms. Such insights are crucial for improving capabilities to understand, predict, and mitigate these impacts. 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. |
| 资助机构 | US-NSF |
| 项目经费 | $275,182.00 |
| 项目类型 | Continuing Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/212159 |
| 推荐引用方式 GB/T 7714 | Rick Relyea.U.S.-RoI-NI R&D Partnership: Ultrasensitive Nitrogen Sensor using Imprinted Polymer Assisted-Bacteria for Real-Time Monitoring of Water Quality.2021. |
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