Deciphering Antioxidant Interactions via Data Mining and RDKit
Lucas B. Ayres, Justin T. Furgala, and Carlos D. Garcia
Scientific Reports (2025) – in press
Authors acknowledge the support from the Open Access Publishing Fund
This project assembles expertise in analytical chemistry, antioxidant chemistry, and artificial intelligence to promote the discovery of novel, high-performance antioxidant blends for rendered fat. Funding for this project was provided by a program funded by South Carolina Department of Agriculture ACRE Competitive Grant Program (Garcia, Whitehead, and Linton)
Papers published
Predicting the Formation of NADES Using a Transformer-Based Model
Lucas B. Ayres, Federico J. V. Gomez, Maria F. Silva, Jeb R. Linton, and Carlos D. Garcia
Scientific Reports 14 (2024) 2715
Predicting Antioxidant Synergism via Artificial Intelligence and Benchtop Data
Lucas B. Ayres, Tomás E. Benavidez, Armelle Varillas, Jeb R. Linton, Daniel C. Whitehead, and Carlos D. Garcia
J. of Agricultural and Food Chemistry 71 (2023) 15644–15655 (cover article)
