Physics Ph.D. Student Develops AI Tools to Tackle an Industry ‘Bottleneck’
The University of Toledo published a profile on 26 August 2026 of Alex Bordovalos, a physics doctoral student building artificial intelligence tools to automate the slowest step in spectroscopic ellipsometry — turning raw polarisation spectra into thickness and optical constants. His advisor, Dr. Nik Podraza, calls it “a major bottleneck in industry and research”. This breakdown separates the university announcement from the peer-reviewed evidence behind it: what the technique actually measures and why its inverse problem needs a human, what Bordovalos and five co-authors published in the Journal of Applied Physics in September 2025, how two series of neural networks split the structural model from the parameter values, the 81-point maps and three amorphous silicon samples used to validate it, the half a million simulations behind the doctoral tool, and the simulation-to-reality gap that still has to be closed on real cadmium telluride cells at Toledo’s Wright Center. It closes with the procurement questions any buyer of automated measurement software should be asking.