Department of Chemistry · University of Houston
Solid-state synthesis, crystallography, and spectroscopy, guided by computation and machine learning.
Using machine learning to find efficient, thermally stable phosphors for white LEDs and near-infrared light sources.
Read more: Data-Driven Development of Phosphors for LED Lighting
Engineering trap states so persistent phosphors keep glowing at high temperature and in harsh environments.
Combining machine learning and synthesis to find hard, oxidation-resistant materials made from earth-abundant elements.
Using machine learning, computation, and synthesis to find new permanent magnets that rely less on rare-earth and other critical elements.
Read more: AI-Driven Discovery of Permanent Magnetic Materials
Exploring the crystal chemistry of compounds in which gold and platinum carry a negative charge.
The Brgoch group rebuilt two public tools for materials design. MatLearn.org uses machine learning to predict the formation energies of binary and ternary compositions and plots the resulting phase diagrams. The Scarcity Calculator, originally developed with the Sparks group at the University of Utah, reports the crustal abundance, scarcity, and market concentration of any compound, and now maps where each element is produced worldwide.
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.
A. Kumar, A. Akbar, J. Brgoch*
J. Am. Chem. Soc. 2026, 148 (40), 43499–43508|doi:10.1021/jacs.6c13733
A. Kumar, J. Brgoch*
Annu. Rev. Mater. Res. 2026, 56, 67–85|doi:10.1146/annurev-matsci-072924-104401
M. Shymanovich, A. G. Squires*, J. Brgoch, D. O. Scanlon*
Chem. Mater. 2026, 38, 7179–7187|doi:10.1021/acs.chemmater.6c00669
N. Lee, M. Sójka, A. La, S. Sharma, S. R. Kavanagh, D. Ahn, D. O. Scanlon*, J. Brgoch*
ACS Appl. Mater. Interfaces 2026, 18, 32921–32930|doi:10.1021/acsami.6c07772
U. Chinaegbomkpa, E. Oyeka, X. Huai, R. Kumar, M. Liang, B. Lee, J. Brgoch, H. Sanabria, T. Tran*
J. Am. Chem. Soc. 2026, 148, 16905–16915|doi:10.1021/jacs.6c00793
Prospective graduate students, postdoctoral researchers, and University of Houston undergraduates should contact Dr. Brgoch directly.
