Abstract & Details
Description
Award ID: 2015155
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development, design, and optimization of new materials in the absence of gravity. The current approach to in-space manufacturing is primarily trial-and-error. The proposed technology will advance a systematic approach to in-space manufacturing, enabling the development of new materials with better properties and cost-competitive associated infrastructure. This Small Business Innovation Research (SBIR) Phase I project will advance the translation of material development in zero-G environments. Chemical formulations of known materials may be unstable under the effect of body forces, but the mechanisms through which these forces impact the phase diagram remain unknown. This project will integrate experimental, computational, and machine learning techniques to identify material formulations amenable to zero-G manufacturing. 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: Muralidharan Nair
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development, design, and optimization of new materials in the absence of gravity. The current approach to in-space manufacturing is primarily trial-and-error. The proposed technology will advance a systematic approach to in-space manufacturing, enabling the development of new materials with better properties and cost-competitive associated infrastructure. This Small Business Innovation Research (SBIR) Phase I project will advance the translation of material development in zero-G environments. Chemical formulations of known materials may be unstable under the effect of body forces, but the mechanisms through which these forces impact the phase diagram remain unknown. This project will integrate experimental, computational, and machine learning techniques to identify material formulations amenable to zero-G manufacturing. 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: Muralidharan Nair
| Status | Closed |
|---|---|
| Effective start/end date | 08/01/20 → 07/31/22 |
Lead and Sub-Awardee Organization(s)
Funding
- SBIR Phase I: $225,000.00
Active Fiscal Year
- FY2022
Start Fiscal Year
- FY2020
TIP Programs
- SBIR Phase I
Small Business
- Yes
Key Technology Areas
- Advanced Materials
- (confidence score: 100%)
- Robotics and Advanced Manufacturing
- (confidence score: 100%)
Technology Foci
- Advanced Manufacturing (excluding biomanufacturing and semiconductor manufacturing)
- (confidence score: 100%)
- Other next-generation materials
- (confidence score: 97%)
Congressional District at Award
- District n. 17 of California
Current Congressional District
- District n. 17 of California
United States
- California
Core Based Statistical Area (CBSA)
- San Jose-Sunnyvale-Santa Clara, CA
County
- County: Santa Clara, CA
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