249 citations · 538 across the 9 of their papers we have counts for
9 papers
Design Space of Self--Consistent Electrostatic Machine Learning Interatomic Potentials
William J. Baldwin, Ilyes Batatia, Martin Vondrák +2
Machine learning interatomic potentials (MLIPs) have become widely used tools in atomistic simulations. For much of the history of this field, the most commonly employed architectu…
Spectral tuning of hyperbolic shear polaritons in monoclinic gallium oxide via isotopic substitution
Giulia Carini, Mohit Pradhan, Elena Gelzinyte +26
Hyperbolic phonon polaritons - hybridized modes arising from the ultrastrong coupling of infrared light to strongly anisotropic lattice vibrations in uniaxial or biaxial polar crys…
Efficient Composite Infrared Spectroscopy: Combining the Doubly-Harmonic Approximation with Machine Learning Potentials
Philipp Pracht, Yuthika Pillai, Venkat Kapil +5
Vibrational spectroscopy is a cornerstone technique for molecular characterization and offers an ideal target for the computational investigation of molecular materials. Building o…
A foundation model for atomistic materials chemistry
Ilyes Batatia, Philipp Benner, Yuan Chiang +85
Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much…
Operando Characterization and Molecular Simulations Reveal the Growth Kinetics of Graphene on Liquid Copper during Chemical Vapor Deposition
Valentina Rein, Hao Gao, Hendrik H. Heenen +10
In recent years, liquid metal catalysts have emerged as a compelling choice for the controllable, large-scale, and high-quality synthesis of two-dimensional materials. At present,…
Finding the Right Bricks for Molecular Lego: A Data Mining Approach to Organic Semiconductor Design
Christian Kunkel, Christoph Schober, Johannes T. Margraf +2
Improving charge carrier mobilities in organic semiconductors is a challenging task that has hitherto primarily been tackled by empirical structural tuning of promising core compou…
Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules
Johannes Gasteiger, Shankari Giri, Johannes T. Margraf +1
Many important tasks in chemistry revolve around molecules during reactions. This requires predictions far from the equilibrium, while most recent work in machine learning for mole…
Atomic structures and orbital energies of 61,489 crystal-forming organic molecules
Annika Stuke, Christian Kunkel, Dorothea Golze +5
Data science and machine learning in materials science require large datasets of technologically relevant molecules or materials. Currently, publicly available molecular datasets w…
Hylleraas-configuration-interaction analysis of the low-lying states in the three-electron Li atom and Be+ ion
Maria Belen Ruiz, Johannes T. Margraf, Alexei M. Frolov
The total energies of twenty eight bound S-, P-, D-, F-, G-, H-, and I-states in the three-electron systems Li atom and Be+ ion, respectively, are determined with the use of the Co…