Anatole visited MPIP in Mainz in February/March 2007.
His current affiliation is University of Toronto, Department of Materials Science and Engineering.
Published in the group
2015
Transferable atomic multipole machine learning models for small organic molecules
T. Bereau, D. Andrienko, A. O. von Lilienfeld
J. Chem. Theory Comput.,
11,
3225-3233,
2015,
[doi]
[abstract]
Accurate representation of the molecular electrostatic potential which is often expanded in distributed multipole moments is crucial for an efficient evaluation of intermolecular interactions. Here we introduce a machine learning model for multipole coefficients of atom types H C O N S F and Cl in any molecular conformation. The model is trained on quantum-chemical results for atoms in varying chemical environments drawn from thousands of organic molecules. Multipoles in systems with neutral cationic and anionic molecular charge states are treated with individual models. The modelsâÃÂàpredictive accuracy and applicability are illustrated by evaluating intermolecular interaction energies of nearly 1000 dimers and the cohesive energy of the benzene crystal.
2011
Toward quantitative structure-property relationships for charge transfer rates of polycyclic aromatic hydrocarbons
M. Misra, D. Andrienko, B. Baumeier, J.-L. Faulon, O. A. von Lilienfeld
J. Chem. Theory Comput.,
7,
2549-2555,
2011,
[doi]
[abstract]
Quantitative structure-property relationships (QSPRs) have been developed and assessed for predicting the reorganization energy of polycyclic aromatic hydrocarbons (PAHs). Preliminary QSPR models based on a combination of molecular signature and electronic eigenvalue difference descriptors have been trained using more than 200 PAHs. Monte Carlo cross-validation systematically improves the performance of the models through progressive reduction of the training set and selection of best performing training subsets. The final biased QSPR model yields correlation coefficients q2 and r2 of 0.7 and 0.8 respectively and an estimated error in predicting reorganization energy of ±0.014 eV.
2007
Tuning electronic eigenvalues of benzene via doping
V. Marcon, O. A. von Lilienfeld, D. Andrienko
J. Chem. Phys.,
127,
064305,
2007,
[doi]
2006
Coarse-grained interaction potentials for polyaromatic hydrocarbons
O. Anatole von Lilienfeld, Denis Andrienko
J. Chem. Phys.,
124,
054307,
2006,
[doi]
[abstract]
Using Kohn-Sham (KS) density-functional theory we have studied the interaction between various polyaromatic hydrocarbon molecules. The systems range from monocyclic benzene up to hexabenzocoronene (hbc). For several conventional exchange-correlation functionals total potential-energy curves of interaction of the pi-pi stacking hbc dimer are reported. It is found that all pure local density or generalized gradient approximated functionals yield qualitatively incorrect predictions regarding structure and interaction. Inclusion of a nonlocal atom-centered correction to the KS Hamiltonian enables quantitative predictions. The computed potential-energy surfaces of interaction yield parameters for a coarse-grained potential which can be employed to study discotic liquid-crystalline mesophases of derived polyaromatic macromolecules.