203 citations · 216 across the 18 of their papers we have counts for
21 papers
A latent-space extrapolation grade built into graph atomic cluster expansion foundation potentials
Yury Lysogorskiy, Anton Bochkarev, Ralf Drautz
Foundation machine-learning interatomic potentials cover broad configurational and chemical spaces, but their reliability can vary across the atomic environments encountered during…
A strategic roadmap for an atomistic machine-learning ecosystem
Jörg Behler, Michele Ceriotti, Cecilia Clementi +47
Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of matter is particularly widespre…
Reactive calcium carbonate precipitation from an atomic cluster expansion potential and enhanced sampling
Eslam Ibrahim, Yury Lysogorskiy, Ralf Drautz +1
Calcium carbonate formation from aqueous solution is central to biomineralization and to carbon sequestration through mineral carbonation. At near-neutral pH, the process is highly…
A hidden low-temperature transformation pathway in compositionally complex materials
Yujiao Li, Elaheh Akbarnejad, Quentin Bizot +9
Most compositionally complex materials (CCMs, frequently referred to as high entropy alloys) are metastable and their attractive properties often belong to kinetically trapped stat…
Computing binary alloy phase diagrams with explicit configurational and vibrational entropy
Sarath Menon, Marvin Poul, Tilmann Hickel +2
Phase stability in multicomponent solid solutions depends on configurational entropy beyond the ideal mixing limit, but capturing it together with vibrational entropy within the sa…
Aromatic Molecule Solvation in Liquid Water with Coupled Cluster Accuracy: The Balance of Pi-Interactions and Hydrophobicity
Nore Stolte, Harald Forbert, Yury Lysogorskiy +2
Aromatic organic solutes in water exhibit a delicate balance between hydrophobic solvation and directional O-H hydrogen bonds, yet widely used force fields and state-of-t…
A general-purpose atomic cluster expansion interatomic potential for niobium
Aleksei Egorov, Ralf Drautz, Thomas Hammerschmidt
Niobium, a body-centered cubic transition metal, poses a challenge for interatomic potentials, which struggle to capture its properties, such as phonons, high-pressure behavior, en…
Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks
Anton Bochkarev, Yury Lysogorskiy, Ralf Drautz
We present an algorithm for evaluating contracted Clebsch--Gordan tensor products in -equivariant machine learning potentials at fixed Canonical P…
Hydride formation and phase separation in palladium nanoparticles from a transferable atomic cluster expansion potential
Minaam Qamar, Apinya Ngoipala, Matous Mrovec +2
The palladium-hydrogen system is a prototype for hydrogen-metal interactions and underpins technologies such as hydrogen storage, catalysis and purification. Yet its nanoscale beha…
Hydrogen uptake and hydride formation in AlCoCrFeNi high-entropy alloys: First-principles, universal-potential, and experimental study
Fritz Körmann, Yuji Ikeda, Konstantin Glazyrin +9
Hydrogen uptake in complex multicomponent alloys, including high-entropy alloys (HEAs), governs both hydrogen storage capacity and resistance to hydrogen-induced degradation. We co…
Exploring the extremes: atomic basis for multi-elemental materials science under complex thermodynamic conditions
Anton Bochkarev, Yury Lysogorskiy, Aparna Subramanyam +2
Modern materials science has historically been founded on combining restricted subsets of the periodic table, favoring high-purity, few-element systems. However, the demands of an…
Water Phase Diagram from a General-Purpose Atomic Cluster Expansion Potential
Eslam Ibrahim, Yury Lysogorskiy, Ralf Drautz +1
Water's phase diagram remains one of the most intricate and challenging benchmarks in molecular modeling. In this study, we compute the phase diagram of water using an Atomic Clust…
Conservative adaptive-precision interatomic potentials
David Immel, Ralf Drautz, Godehard Sutmann
Adaptive precision molecular dynamics simulations have developed along energy- and force-coupling approaches, which allow for a continuous transition between different particle des…
AI-Driven Expansion and Application of the Alexandria Database
Théo Cavignac, Jonathan Schmidt, Pierre-Paul De Breuck +9
We present a novel multi-stage workflow for computational materials discovery that achieves a 99% success rate in identifying compounds within 100 meV/atom of thermodynamic stabili…
Graph atomic cluster expansion for foundational machine learning interatomic potentials
Yury Lysogorskiy, Anton Bochkarev, Ralf Drautz
Foundational machine learning interatomic potentials that can accurately and efficiently model a vast range of materials are critical for accelerating atomistic discovery. We intro…
Data-efficient machine-learning of complex Fe-Mo intermetallics using domain knowledge of chemistry and crystallography
Mariano Forti, Alesya Malakhova, Yury Lysogorskiy +5
Atomistic simulations of multi-component systems require accurate descriptions of interatomic interactions to resolve details in the energy of competing phases. A particularly chal…
Efficient local atomic cluster expansion for BaTiO close to equilibrium
Anna Grünebohm, Matous Mrovec, Maxim N. Popov +4
Barium titanate (BTO) is a representative perovskite oxide that undergoes three first-order ferroelectric phase transitions related to exceptional functional properties. In this wo…
Nanoindentation simulations for copper and tungsten with adaptive-precision potentials
David Immel, Matous Mrovec, Ralf Drautz +1
We perform nanoindentation simulations for both the prototypical face-centered cubic metal copper and the body-centered cubic metal tungsten with a new adaptive-precision descripti…
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs, Dane Morgan, Siamak Attarian +27
The rapid development and large body of literature on machine learning interatomic potentials (MLIPs) can make it difficult to know how to proceed for researchers who are not exper…
Charge-constrained Atomic Cluster Expansion
Matteo Rinaldi, Anton Bochkarev, Yury Lysogorskiy +1
The atomic cluster expansion (ACE) efficiently parameterizes complex energy surfaces of pure elements and alloys. Due to the local nature of the many-body basis, ACE is inherently…
Adaptive-precision potentials for large-scale atomistic simulations
David Immel, Ralf Drautz, Godehard Sutmann
Large-scale atomistic simulations rely on interatomic potentials providing an efficient representation of atomic energies and forces. Modern machine-learning (ML) potentials provid…