Massive Monte Carlo simulations-guided interpretable learning of two-dimensional Curie temperature
Arnab Kabiraj, Tripti Jain, Santanu Mahapatra
Abstract
Data-driven models for Curie temperature prediction with exceptional accuracy d A Curie temperature dataset for a quarter million 2D materials d Models are interpreted using permutation feature importance and Shapley values d Pure ab initio, automated approach for Curie and Ne el temperature prediction
Topics & Concepts
Heisenberg modelMonte Carlo methodCurie temperatureAnisotropyStatistical physicsHamiltonian (control theory)IsotropyInterpretabilityMagnetismCondensed matter physicsFerromagnetismPhysicsArtificial intelligenceMathematicsComputer scienceStatisticsQuantum mechanicsMathematical optimizationMachine Learning in Materials ScienceQuantum many-body systemsAdvanced Condensed Matter Physics