SOURCE-LINKED INTELLIGENCE
Development of Data-assisted Photo-Organocatalytic Transformations
hods. This proposal aims to develop new data-assisted protocols for reaction discovery and photocatalyst design. During the outgoing phase at the University of Utah, under Prof. Sigman's supervision, machine learning algorithms will be used to correlate photocatalysts' structures with their functions. Classification tools will explore reactivity cliffs, and dimensionality reduction techniques will map the chemical space to visualize reactivity patterns with fewer experiments. In the subsequent return phase at the University of Padova, under Prof. Dell'Amico's supervision, these photochemical methodologies will be adapted for flow processes to produce synthetically relevant compounds on a multi-gram scale. The data science knowledge acquired will guide this transition, enabling a more efficient implementation. Data science, computer-assisted reaction development, machine learning, predictive algorithms
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 396991.08
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T04:21:15.460Z. This is not the publication date.