Complete Neural Electronic Initialization Accelerates Materials DFT
Materials
Presents the first complete machine learning method for accelerating plane-wave DFT in materials under the PAW formalism, formalizing seven criteria that a Complete Neural Electronic Initializer must satisfy and addressing two missing structure-dependent components: augmentation occupancies and spin initialization.
See LICENSE file Density Functional TheoryMachine LearningMaterials Science