Abstract & Details
Description
Award ID: 2136833
This Small Business Innovation Research (SBIR) Phase II project will improve the environment with cleaner diesel engine exhaust. Diesel engine manufacturers currently cannot precisely control their exhaust after-treatment systems due to the lack of widely deployable sensors that can differentiate between oxides of nitrogen (NOx) and other species in the exhaust stream. This project advances a novel on-board sensor for detecting NOx in diesel exhaust streams with sensitivities and molecular specificity unmatched by existing technologies. It can result in 10% greater fuel efficiency while matching new stringent NOx emissions standards. Fleet-wide fuel economy improvements and NOx emissions reductions enabled by this technology will lead to reduced carbon emissions and healthier air with lower amounts of NOx-induced smog, ground-level ozone, and acid rain. The intellectual merit of this project advances a novel application of laser-absorption spectroscopy, which probes the unique spectral absorption fingerprint of NOx species to avoid cross-species interference. This sensor is projected to achieve tenfold lower detection thresholds than current widely deployed electrochemical sensors in the harsh high-temperature particulate-laden diesel exhaust environments, all while maintaining a form factor similar to those used in existing diesel aftertreatment systems. This Phase I research will leverage novel manufacturing techniques to fabricate and demonstrate the performance of a high-sensitivity laser-based NO sensor capable of surviving high-temperature, oxidizing, intensely vibrating, and particulate-laden flows characteristic of vehicle exhaust gases. 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: Benaiah Schrag
This Small Business Innovation Research (SBIR) Phase II project will improve the environment with cleaner diesel engine exhaust. Diesel engine manufacturers currently cannot precisely control their exhaust after-treatment systems due to the lack of widely deployable sensors that can differentiate between oxides of nitrogen (NOx) and other species in the exhaust stream. This project advances a novel on-board sensor for detecting NOx in diesel exhaust streams with sensitivities and molecular specificity unmatched by existing technologies. It can result in 10% greater fuel efficiency while matching new stringent NOx emissions standards. Fleet-wide fuel economy improvements and NOx emissions reductions enabled by this technology will lead to reduced carbon emissions and healthier air with lower amounts of NOx-induced smog, ground-level ozone, and acid rain. The intellectual merit of this project advances a novel application of laser-absorption spectroscopy, which probes the unique spectral absorption fingerprint of NOx species to avoid cross-species interference. This sensor is projected to achieve tenfold lower detection thresholds than current widely deployed electrochemical sensors in the harsh high-temperature particulate-laden diesel exhaust environments, all while maintaining a form factor similar to those used in existing diesel aftertreatment systems. This Phase I research will leverage novel manufacturing techniques to fabricate and demonstrate the performance of a high-sensitivity laser-based NO sensor capable of surviving high-temperature, oxidizing, intensely vibrating, and particulate-laden flows characteristic of vehicle exhaust gases. 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: Benaiah Schrag
| Status | Closed |
|---|---|
| Effective start/end date | 03/01/22 → 01/31/26 |
Funding
- SBIR Phase II: $1,000,000.00
Active Fiscal Year
- FY2024
- FY2023
- FY2022
- FY2026
- FY2025
Start Fiscal Year
- FY2022
TIP Programs
- SBIR Phase II
Small Business
- Yes
Key Technology Areas
- Disaster Prevention and Mitigation
- (confidence score: 80%)
Technology Foci
- Disaster Prevention and Mitigation (Broad)
- (confidence score: 100%)
Congressional District at Award
- District n. 39 of California
Current Congressional District
- District n. 39 of California
United States
- California
Core Based Statistical Area (CBSA)
- Riverside-San Bernardino-Ontario, CA
County
- County: Riverside, CA
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