activity
20152021
most citedMachine learning for many-body physics: efficient solution of dynamical mean-field theory

29 citations · 86 across the 6 of their papers we have counts for

collaborators

12 papers

physics.chem-ph2021

Elucidating atmospheric brown carbon -- Supplanting chemical intuition with exhaustive enumeration and machine learning

Enrico Tapavicza, Guido Falk von Rudorff, David O. De Haan +4

To unravel the structures of C12H12O7 isomers, identified as light-absorbing photooxidation products of syringol in atmospheric chamber experiments, we apply a graph-based molecule…

physics.chem-ph20203 cited

Dictionary of 140k GDB and ZINC derived AMONs

Bing Huang, O. Anatole von Lilienfeld

We present all {\bf A}mons for {\bf G}DB and {\bf Z}inc data-bases using no more than 7 non-hydrogen atoms (AGZ7)---a calculated organic chemistry building-block dictionary based o…

physics.chem-ph202022 cited

Large yet bounded: Spin gap ranges in carbenes

Max Schwilk, Diana N. Tahchieva, O. Anatole von Lilienfeld

Despite its relevance for chemistry, the electronic structure of free carbenes throughout chemical space has not yet been studied in a systematic manner. We explore a large and sys…

physics.chem-ph202012 cited

Quantum-chemistry-aided identification, synthesis and experimental validation of model systems for conformationally controlled reaction studies: Separation of the conformers of 2,3-dibromobuta-1,3-diene in the gas phase

Ardita Kilaj, Hong Gao, Diana Tahchieva +6

The Diels-Alder cycloaddition, in which a diene reacts with a dienophile to form a cyclic compound, counts among the most important tools in organic synthesis. Achieving a precise…

physics.chem-ph2019

Atoms in molecules from alchemical perturbation density functional theory

Guido Falk von Rudorff, O. Anatole von Lilienfeld

Based on thermodynamic integration we introduce atoms in molecules (AIM) using the orbital-free framework of alchemical perturbation density functional theory (APDFT). Within APDFT…

physics.chem-ph2018

Alchemical normal modes unify chemical space

Stijn Fias, K. Y. Samuel Chang, O. Anatole von Lilienfeld

In silico design of new molecules and materials with desirable quantum properties by high-throughput screening is a major challenge due to the high dimensionality of chemical space…