79 citations · 110 across the 7 of their papers we have counts for
8 papers
Transferable excited-state dynamics enable screening of fluorescent protein chromophores
Rhyan Barrett, Sophia Wesely, Julia Westermayr
Transferable excited-state dynamics offer a route to efficient screening of photophysical behavior across molecular systems, but conventional nonadiabatic simulations remain prohib…
Hierarchical generative modeling for the design of multi-component systems
Rhyan Barrett, Robin Curth, Julia Westermayr
The functionality of catalysts, enzymes, and supramolecular assemblies emerges not from individual molecules alone, but from the subtle interplay between multiple components arrang…
Statistics makes a difference: Machine learning adsorption dynamics of functionalized cyclooctine on Si(001) at DFT accuracy
Hendrik Weiske, Rhyan Barrett, Ralf Tonner-Zech +2
The interpretation of experiments on reactive semiconductor surfaces requires statistically significant sampling of molecular dynamics, but conventional ab initio methods are limit…
Incorporating Long-Range Interactions via the Multipole Expansion into Ground and Excited-State Molecular Simulations
Rhyan Barrett, Johannes C. B. Dietschreit, Julia Westermayr
Simulating long-range interactions remains a significant challenge for molecular machine learning potentials due to the need to accurately capture interactions over large spatial r…
Transferable Machine Learning Potential X-MACE for Excited States using Integrated DeepSets
Rhyan Barrett, Christoph Ortner, Julia Westermayr
Conical intersections serve as critical gateways in photochemical reactions, enabling rapid nonradiative transitions between potential energy surfaces that underpin fundamental pro…
Parameterizing Intersecting Surfaces via Invariants
Timon S. Gutleb, Rhyan Barrett, Julia Westermayr +1
We introduce and analyze numerical companion matrix methods for the reconstruction of hypersurfaces with crossings from smooth interpolants given unordered or, without loss of gene…
Reinforcement learning for traversing chemical structure space: Optimizing transition states and minimum energy paths of molecules
Rhyan Barrett, Julia Westermayr
In recent years, deep learning has made remarkable strides, surpassing human capabilities in tasks like strategy games, and it has found applications in complex domains, including…
High-throughput property-driven generative design of functional organic molecules
Julia Westermayr, Joe Gilkes, Rhyan Barrett +1
The design of molecules and materials with tailored properties is challenging, as candidate molecules must satisfy multiple competing requirements that are often difficult to measu…