Adversarial active learning
Uncertainty-driven training of machine-learning potentials that capture material properties accurately, straight from first principles.
Hylleraas Centre · University of Oslo
Bore Research Group
AI insight into the quantum world of atoms
iℏ ∂t|ψ⟩ = Ĥ|ψ⟩ → real materials
The Bore Research Group, at the Department of Chemistry, University of Oslo, works at the intersection of artificial intelligence and quantum mechanics. We develop and apply machine-learning potentials for accelerated, reliable first-principles molecular dynamics — reaching exotic chemistry and physics beyond what traditional methods allow.
Ion-conductive frameworks
Understanding and enhancing ionic conductivity in nanoporous materials — a step toward better fuel-cell membranes.
Why ice is slippery
A first-principles account of the thin premelted layer that governs the friction of ice.
News
Recent work
Latest preprints and publications from the group.
2026 · Preprint
Why ice is so slippery
S. L. Bore, B. N. J. Persson, H. A. Sveinsson — under review · arXiv
2026 · Preprint
Energy dissipation at the atomic scale explains how fracture energy depends on crack velocity in silica glass
M. G. Guren, S. L. Bore, F. Renard, H. A. Sveinsson — under review · arXiv
2026 · J. Catal.
The organic residue and solvent in the Schlenk equilibrium for Grignard reagents in THF
M. Bortoli, S. L. Bore, O. Eisenstein, M. Cascella — J. Catal. 454, 116619 · DOI
2025 · npj Comput. Mater.
Learning atomic forces from uncertainty-calibrated adversarial attacks
H. M. Cezar, T. Bodenstein, H. A. Sveinsson, M. Ledum, S. Reine, S. L. Bore — npj Comput. Mater. 11, 200 · DOI
2025 · Nature Physics
Constraints on the location of the liquid–liquid critical point in water
F. Sciortino, Y. Zhai, S. L. Bore, F. Paesani — Nat. Phys. 21, 480 · DOI
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Open positions
We're always looking for master's and PhD students and postdocs — bring your own system, or join an existing project on ice, ions, or ML-potential methods.
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Automated ML-potential workflows for battery materials, fuel cells, CO2 capture, and industrial process optimization — from your desktop to the supercomputer.
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