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BIGDML: Towards Exact Machine Learning Force Fields for Materials
Huziel E. Sauceda, Luis E. Gálvez-González, Stefan Chmiela +3
Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and applicable to molecules, materials, and interfaces thereof. Currently, MLFFs often…
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects
Oliver T. Unke, Stefan Chmiela, Michael Gastegger +3
Machine-learned force fields (ML-FFs) combine the accuracy of ab initio methods with the efficiency of conventional force fields. However, current ML-FFs typically ignore electroni…
On the forbidden graphene's ZO (out-of-plane optic) phononic band-analog vibrational modes in fullerenes
Jesús N. Pedroza-Montero, Ignacio L. Garzón, Huziel E. Sauceda
The study of nanostructures' vibrational properties is at the core of nanoscience research, they are known to represent a fingerprint of the system as well as to hint the underlyin…