# Collaborative Research: CDS&E: Motif-Based Deep Learning for Discovery and Chemical Insights into Disordered Phases

**Budget Signal Score:** 55/100

| Field | Value |
|---|---|
| Institution | Rensselaer Polytechnic Institute |
| Location | TROY, NY |
| Project | Collaborative Research: CDS&E: Motif-Based Deep Learning for Discovery and Chemical Insights into Disordered Phases |
| Award amount | $300,880 |
| Obligated so far | $300,880 |
| Awarded | 2026-08-03 |
| Period | 2026-08-15 to 2029-07-31 |
| Program | CONDENSED MATTER & MAT THEORY |
| Directorate / division | MPS / MRS |
| Award ID | 2602544 |

## Why this score
- Award of $300K or more.
- Equipment- and compute-heavy field.

Source: U.S. National Science Foundation Awards API (https://www.nsf.gov/awardsearch/showAward?AWD_ID=2602544). Last refreshed: 2026-11-04T18:13:44.963Z.
Award data comes from the NSF Awards API and may be amended by NSF. Institution-level only; investigator contact details are not included. Informational only.