HBRL Research Group

We envision and engineer the future landscape of semiconductor fabrication. We are a research group at the intersection of artificial intelligence and semiconductor fabrication. At HBRLRG we believe the future of materials science is written at the atomic scale — and that getting there requires both rigorous theory and hands-on experimentation working in constant dialogue. Our work bridges AI-driven materials design with experimental realization. We develop and apply deep learning diffusion models, density functional theory with machine-learning force fields, and kinetic Monte Carlo simulations — then validate every prediction through atomic-scale synthesis including atomic layer deposition (ALD), atomic layer modulation (ALM), and area-selective deposition (ASD). Two programmes: a digital twin of semiconductor fabrication, built from both ends at once, and surfaces engineered for the conditions life meets. Rehearsing atomic-layer processes on a computer — uniting experiment and AI in a reinforcing loop that advances both semiconductors and the models that design them. Surface self-saturation reactions in sequential cycles — enabling atomic-scale conformality and uniformity for nanodevice fabrication. Bottom-up patterning that grows a film only where it is wanted — replacing costly lithography steps with surface chemistry. Sub-monolayer sequential precursor dosing prior to oxidation — enabling atomic-scale in-plane mixing and precise stoichiometry control beyond the conventional ALD supercycle. First-principles energetics — accelerated by machine-learning force fields — to decide what adsorbs, what reacts, and what stays stable. From single reactions to whole films — stochastic and machine-learned models that predict growth, composition, and selectivity cycle by cycle.