6 papers · 1 filter
Towards a universal model for spin-orbit coupled Wannier Hamiltonians
Alexander C. Tyner
While machine learning interatomic potentials (MLiPs) have matured to revolutionize material science, deep learning models for electronic structure are just beginning to emerge and…
Generation of magnetic metal-organic frameworks
Alexander C. Tyner, Avinash Pathapati, Alexander V. Balatsky
The potential to utilize metal-organic frameworks as a replacement for rare earth materials as well as in technological applications has prompted increased interested in this mater…
Fine tuning generative adversarial networks with universal force fields: application to two-dimensional topological insulators
Alexander C. Tyner
Despite rapid growth in use cases for generative artificial intelligence, its ability to design purpose built crystalline materials remains in a nascent phase. At the moment invers…
Machine learning guided discovery of stable, spin-resolved topological insulators
Alexander C. Tyner
Identification of a non-trivial index in a spinful two dimensional insulator indicates the presence of an odd, quantized (pseudo)spin-resolved Chern number, $C_{s}…
BerryEasy: A GPU enabled python package for diagnosis of nth-order and spin-resolved topology in the presence of fields and effects
Alexander C. Tyner
Multiple software packages currently exist for the computation of bulk topological invariants in both idealized tight-binding models and realistic Wannier tight-binding models deri…
Screening the organic materials database for superconducting metal-organic frameworks
Alexander C. Tyner, Alexander V. Balatsky
The increasing financial and environmental cost of many inorganic materials has motivated study into organic and "green" alternatives. However, most organic compounds contain a lar…