From the 1 of 18 linked papers with an AI index.
14 papers · 1 filter
Machine-learned exchange-correlation functionals for molecules, solids, and reactive surfaces
Mohamed S. Abdallah, Zhuotao Jin, Boris Kozinsky +1
The application of density functional theory to heterogeneous catalysis is hindered by the shortcomings of conventional density functional approximations. We combine machine learni…
DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion
Zhuotao Jin, Xiaoyun Wang, Nicholas Brawand +5
The search for new crystalline materials spans an enormous compositional and structural space. Generating candidates in this space requires jointly modeling discrete crystallograph…
Predicting Interface Structure using the Minima Hopping Method with a Machine Learning Interatomic Potential
Chang-Ti Chou, Menghang Wang, Chao Yang +4
Predicting atomic-scale interfacial structures remains a central challenge in materials science due to their structural complexity and the difficulty of direct comparison between c…
Quantum theory of nonlinear phononics
Francesco Libbi, Boris Kozinsky
The recent capability to use THz pulses to control the nuclear quantum degrees of freedom in crystals has opened promising avenues for the advanced manipulation of material propert…
Exploring Charge Density Waves in two-dimensional NbSe2 with Machine Learning
Norma Rivano, Francesco Libbi, Chuin Wei Tan +8
Niobium diselenide (NbSe) has garnered significant attention due to the coexistence of superconductivity and charge density waves (CDWs) down to the monolayer limit. However, r…
Equivalence of charged and neutral density functional formulations for correcting the many-body self-interaction of polarons
Stefano Falletta, Jennifer Coulter, Joel B. Varley +4
The electron self-interaction problem in density functional theory affects the accurate modeling of polarons, particularly their localization and formation energy. Charged and neut…