Computer vision for high-throughput materials synthesis: a tutorial for experimentalists
Computer vision enables the rapid identification of chemical phases, such as solid metal–organic framework (MOF) materials, from images of sample vials.
Authors
- Abhijoy Mandal (ORCID: https://orcid.org/0009-0003-5788-9496)
- Varinia Bernales (ORCID: https://orcid.org/0000-0002-8446-7956)
- Madeleine A. Gaidimas (ORCID: https://orcid.org/0000-0001-6111-8238)
- Kent O. Kirlikovali (ORCID: https://orcid.org/0000-0001-8329-1015)
- Kourosh Darvish (ORCID: https://orcid.org/0000-0003-4984-432X)
- G. C. Kim
- Alan Ramayee Aspuru-Guzik
- Akshay Talekar
- Pan Chen
- Shi Xuan Leong
- Omar K. Farha
Institutions
- Northwestern University (US)
- Nanyang Technological University (SG)
- University of Toronto (CA)
- Institute of Materials Science (VN)
- Vector Institute (CA)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-12-23
- DOI
- https://doi.org/10.1039/d5dd00384a
- Citations
- 1
- Primary Topic
- Metal-Organic Frameworks: Synthesis and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.54
Funders
- Northwestern University
- Underwriters Laboratories
- Ministry of Education - Singapore
- Nanyang Technological University
- University of Toronto
- Canada First Research Excellence Fund
- International Institute for Nanotechnology, Northwestern University
- Natural Sciences and Engineering Research Council of Canada
- Natural Resources Canada