Abstract & Details
Description
Award ID: 2141084
The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to design gas sensing applications for farming and industrial operations. The National Academy of Engineering has identified Managing the Nutrients as a Grand Challenge. The proposed project will develop a field-deployable and portable gas sensing system for reliable and affordable assessment of farm health and safety, improving the real-time monitoring of environmental impacts. The gas sensor has commercial applications in industries such as steel, cement, and chemical manufacturing. The project will also train a new generation of workforce trained towards environmental hazard monitoring and taking research to practice. The proposed project will advance a novel fiber-optic, field-deployable, wireless, multiplexed gas sensing system for monitoring field/farm and industrial emissions. This project will develop a first-of-a-kind optical sensing system capable of detecting field-released potent greenhouse gases CH4 and CO2, and farm-emitted health hazards NH3 and H2S, which are produced in agriculture/animal-farming operation as well as in industrial setting. Unlike the existing sensing methodologies (e.g., gas chromatography-mass spectroscopy, infrared spectroscopy, electrochemical sensors, commercial artificial noses, and existing state-of-the-art optical gas detection technologies), the proposed sensing system is low-cost and provides the ppm-level limit-of-detection required of the target gases. The intellectual merit includes: (1) an integrated and reusable gas sensing system with higher selectivity through a 2-tiered approach of target specific functionalization together with coupled design-diversity and data-analytics for cross-sensitivity reduction and sensitivity/specificity improvement, and (2) Data analytics for dynamic runtime calibration together with time-division multiplexing to support continuous monitoring. 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.
NSF Program Director: Mara E. Schindelholz
The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to design gas sensing applications for farming and industrial operations. The National Academy of Engineering has identified Managing the Nutrients as a Grand Challenge. The proposed project will develop a field-deployable and portable gas sensing system for reliable and affordable assessment of farm health and safety, improving the real-time monitoring of environmental impacts. The gas sensor has commercial applications in industries such as steel, cement, and chemical manufacturing. The project will also train a new generation of workforce trained towards environmental hazard monitoring and taking research to practice. The proposed project will advance a novel fiber-optic, field-deployable, wireless, multiplexed gas sensing system for monitoring field/farm and industrial emissions. This project will develop a first-of-a-kind optical sensing system capable of detecting field-released potent greenhouse gases CH4 and CO2, and farm-emitted health hazards NH3 and H2S, which are produced in agriculture/animal-farming operation as well as in industrial setting. Unlike the existing sensing methodologies (e.g., gas chromatography-mass spectroscopy, infrared spectroscopy, electrochemical sensors, commercial artificial noses, and existing state-of-the-art optical gas detection technologies), the proposed sensing system is low-cost and provides the ppm-level limit-of-detection required of the target gases. The intellectual merit includes: (1) an integrated and reusable gas sensing system with higher selectivity through a 2-tiered approach of target specific functionalization together with coupled design-diversity and data-analytics for cross-sensitivity reduction and sensitivity/specificity improvement, and (2) Data analytics for dynamic runtime calibration together with time-division multiplexing to support continuous monitoring. 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.
NSF Program Director: Mara E. Schindelholz
| Status | Closed |
|---|---|
| Effective start/end date | 03/15/22 → 02/28/26 |
Lead and Sub-Awardee Organization(s)
Funding
- Other Programs (Technology): $250,000.00
Active Fiscal Year
- FY2024
- FY2023
- FY2022
- FY2026
- FY2025
Start Fiscal Year
- FY2022
TIP Programs
- Other Programs (Technology)
Key Technology Areas
- Emergent Technologies
Congressional District at Award
- District n. 04 of Iowa
Current Congressional District
- District n. 04 of Iowa
United States
- Iowa
Core Based Statistical Area (CBSA)
- Ames, IA
County
- County: Story, IA
EPSCoR Jurisdiction
- Yes
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine