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Abstract Dual light-excited ketone/transition-metal catalysis is a rapidly developing field of photochemistry. It allows for versatile functionalizations of C–H or C–X bonds enabled by triplet ketone acting as a hydrogen-atom-abstracting agent, a single-electron acceptor, or a photosensitizer. This review summarizes recent developments of synthetically useful transformations promoted by the synergy between triplet ketone and transition-metal catalysis. 1 Introduction 2 Triplet Ketone Catalysis via Hydrogen Atom Transfer 2.1 Triplet Ketones with Nickel Catalysis 2.2 Triplet Ketones with Copper Catalysis 2.3 Triplet Ketones with Other Transition-Metal Catalysis 3 Triplet Ketone Catalysis via Single-Electron Transfer 4 Triplet Ketone Catalysis via Energy Transfer 5 Conclusions
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This content will become publicly available on June 11, 2026
Enhancing predictive models for solubility in multicomponent solvent systems using semi-supervised graph neural networks
Using a MixSolDB, a curated solubility dataset for multicomponent solvent systems, a GNN-based framework with semi-supervised distillation from COSMO-RS data improved prediction accuracy and broadened applicability.
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- Award ID(s):
- 2304658
- PAR ID:
- 10618610
- Publisher / Repository:
- Royal Society of Chemistry
- Date Published:
- Journal Name:
- Digital Discovery
- Volume:
- 4
- Issue:
- 6
- ISSN:
- 2635-098X
- Page Range / eLocation ID:
- 1492 to 1504
- Subject(s) / Keyword(s):
- multicomponent solvent solubility machine learning graph neural network
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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