AI and data-driven chemistry
Ideas that use artificial intelligence, machine learning, autonomous or self-driving labs, digital twins and shared data to speed up chemistry and materials research.
Who funds this idea
2 calls from 2 funders currently fund work on this idea. Most calls: European Commission (Horizon Europe) (1), NSF (1).1 call for this idea welcome industry or international partners
Open now (2)
Automated Scientific Discovery - Materials Science (RAISE pilot) (RIA)
Deadline: 02 Feb 2027 (103 days)
materialsestablished / PI
Computational and Data-Enabled Science and Engineering
Deadline: Rolling / no fixed deadline
chemistryestablished / PI
Recently funded work on this idea
28 awards from NSF and NIH in our sample of the last 24 months match this idea. Latest examples:
| Award (official page) | Institution | Amount | Start date |
|---|---|---|---|
| Collaborative Research: DMREF: NSF-DFG: AI-Driven Platform for 2D Materials Synthesis and Discovery | Pennsylvania State Univ University Park | $1,440,000 | 01 Oct 2026 |
| Collaborative Research: DMREF: NSF-DFG: AI-Driven Platform for 2D Materials Synthesis and Discovery | Kenyon College | $160,000 | 01 Oct 2026 |
| GOALI: Machine Learning Enabled Multiscale Modeling Platform and Virtual Sensing Digital Twin for Fatigue in Metals Additive Manufacturing (MAM) | Johns Hopkins University | $900,000 | 01 Sep 2026 |
| Probing Heterogeneous Bubble Nucleation Mechanisms via Time-Resolved Upconverting Nanoparticles Luminescence Thermometry | University of New Mexico | $450,000 | 01 Aug 2026 |