Computer vision for high-throughput materials synthesis: a tutorial for experimentalists

2025/12/23 by Madeleine A. Gaidimas, Abhijoy Mandal, Pan Chen +8 · 1 voice
Chemistry · Materials Science · #Machine Learning in Materials Science #Metal-Organic Frameworks: Synthesis and Applications #X-ray Diffraction in Crystallography

paper · pdf · doi:10.1039/d5dd00384a

openalex created_date 2025/12/23 · openalex publication_date 2025/12/23 · openalex updated_date 2026/07/02

Abstract

Computer vision enables the rapid identification of chemical phases, such as solid metal–organic framework (MOF) materials, from images of sample vials.

Citations

• High-Throughput Synthesis of Zeolitic Imidazolate Frameworks and Application to CO 2 Capture
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• Metal–Organic Frameworks for Drug Delivery: A Design Perspective
• Explainability of deep vision-based autonomous driving systems: Review and challenges
• Self-driving laboratory for accelerated discovery of thin-film materials

Discussions

• 📢 #DigitalDiscovery's Editor in Chief Alán Aspuru-Guzik and his team are empowering experimentalists to integrate computer vision approaches within high-throughput materials research in their newest [bsky, 6 points, 0 comments]

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