Amit Kumar and Arslan Akbar used machine learning to find Cr3+ phosphors that emit in the second near-infrared window, beyond 1000 nm, where light travels deeper through tissue. Models trained on 208 reported Cr3+ spectra screened 4,062 oxide and fluoride hosts and led to LiInW2O8 and NaScW2O8, with broadband emission centered at 1085 and 1100 nm.
The U.S. Department of Energy’s ARPA-E awarded $2.88 million through its MAGNITO program to GAMBIT (Guided AI for Magnetic Boride/Carbide Intermetallic Technologies), a UH-led team that will use machine learning to discover new permanent magnets. Brgoch leads the project with Joshua Bocarsly at UH, alongside Rice University, Colorado State University, Newfound Materials, and Carrier Global.
Brgoch was named a Senior Member of the National Academy of Inventors (NAI), which recognizes academic inventors whose work has produced patents and technologies with real-world impact.
Brgoch starts as an associate editor at Chemistry of Materials, handling papers on integrating computation, AI, and experiment.
Brgoch was named a Fellow Member of the Royal Society of Chemistry (FRSC).
