Data Driven Sustainable Synthesis and Processing

AI-assisted synthesis is transforming experimental chemistry by accelerating workflows, reducing waste, and enhancing efficiency. Experts highlighted how AI optimizes high-throughput experiments and the skills future chemists will need in the era of data-driven sustainable chemistry.

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The data driven and AI-assisted synthesis is the future not only to make our experimental work faster but also to follow a more sustainable pathway by minimizing the by-products and waste while obtaining high-quality products in a cost efficient manner. The speakers gave insightful talks which explained how an AI-assisted laboratory can be planned for high throughput experiments and also the related challenges. AI driven molecular chemistry is found to be ahead in this development compared to supramolecular chemistry and more heterogeneous systems. Among others the panel discussions summarized the competences of future chemists interested in Data driven sustainable chemistry and also highlighted the need to expand the space of structured data availability through high through put experimental platforms

We would like to thank the speakers Mimi Hii, Pascal Miéville, Samuel Genheden, Kjell Jorner and Juho Rousu which not only presented excellent slides but also gave inspiring answers during the panel discussions with Belén Martín-Matute!

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See speakers' presentations below

Pivoting synthetic chemistry towards a data data-led subject (3615 Kb)

Paradigm shift in synthesis planning: how to exploit artificial intelligence (1407 Kb)

Deep representation Learning for Small Molecules (1327 Kb)

Digital tools for reaction prediction and optimization (5188 Kb)

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Last updated: September 27, 2024

Source: SUCCeSS

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