2.1k citations · 6k across the 29 of their papers we have counts for
3 papers · 1 filter
Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery
Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev +3
The screening of novel materials is an important topic in the field of materials science. Although traditional computational modeling, especially first-principles approaches, is a…
Machine Learned Hückel Theory: Interfacing Physics and Deep Neural Networks
Tetiana Zubatyuk, Ben Nebgen, Nicholas Lubbers +7
The Hückel Hamiltonian is an incredibly simple tight-binding model famed for its ability to capture qualitative physics phenomena arising from electron interactions in molecules an…
MolecularRNN: Generating realistic molecular graphs with optimized properties
Mariya Popova, Mykhailo Shvets, Junier Oliva +1
Designing new molecules with a set of predefined properties is a core problem in modern drug discovery and development. There is a growing need for de-novo design methods that woul…