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Homogeneous catalyst graph neural network: A human-interpretable graph neural network tool for ligand optimization in asymmetric catalysis (2025)
Journal Article
Aguilar-Bejarano, E., Özcan, E., Rit, R. K., Li, H., Lam, H. W., Moore, J. C., Woodward, S., & Figueredo, G. (2025). Homogeneous catalyst graph neural network: A human-interpretable graph neural network tool for ligand optimization in asymmetric catalysis. iScience, 28(3), Article 111881. https://doi.org/10.1016/j.isci.2025.111881

Optimization of metal-ligand asymmetric catalysts is usually done by empirical trials, where the ligand is arbitrarily modified, and the new catalyst is re-evaluated in the lab. This procedure is not efficient and alternative strategies are highly de... Read More about Homogeneous catalyst graph neural network: A human-interpretable graph neural network tool for ligand optimization in asymmetric catalysis.

Gold(I)‐Catalyzed Nucleophilic Propargylation of Azinium Ions via Hydroxydihydroazine Intermediates (2025)
Journal Article
Smithson, J., O'Brien, L., Jones, K. D., Argent, S. P., Wheelhouse, K. M., Woodward, S., Ermanis, K., & Lam, H. W. (2025). Gold(I)‐Catalyzed Nucleophilic Propargylation of Azinium Ions via Hydroxydihydroazine Intermediates. Chemistry - A European Journal, 31(9), Article e202404153. https://doi.org/10.1002/chem.202404153

The nucleophilic propargylation of azinium ions with a propargylboronate proceeds efficiently under gold(I) catalysis. A range of N-alkylated pyridinium, quinolinium, and pyrazinium ions undergo propargylation with good yields and high regioselectivi... Read More about Gold(I)‐Catalyzed Nucleophilic Propargylation of Azinium Ions via Hydroxydihydroazine Intermediates.