References of "Tkatchenko, Alexandre 50009596"
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See detailInterpolating Nonadiabatic Molecular Dynamics Hamiltonian with Artificial Neural Networks
Bipeng Wang; Weibin Chu; Tkatchenko, Alexandre UL et al

in Journal of Physical Chemistry Letters (2022)

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See detailCorrelated Wave Functions for Electron–Positron Interactions in Atoms and Molecules
Charry Martinez, Jorge Alfonso UL; Barborini, Matteo UL; Tkatchenko, Alexandre UL

in Journal of Chemical Theory and Computation (2022), 18(4), 22672280

The positron, as the antiparticle of the electron, can form metastable states with atoms and molecules before its annihilation with an electron. Such metastable matter–positron complexes are stabilized by ... [more ▼]

The positron, as the antiparticle of the electron, can form metastable states with atoms and molecules before its annihilation with an electron. Such metastable matter–positron complexes are stabilized by a variety of mechanisms, which can have both covalent and noncovalent character. Specifically, electron–positron binding often involves strong many-body correlation effects, posing a substantial challenge for quantum-chemical methods based on atomic orbitals. Here we propose an accurate, efficient, and transferable variational ansatz based on a combination of electron–positron geminal orbitals and a Jastrow factor that explicitly includes the electron–positron correlations in the field of the nuclei, which are optimized at the level of variational Monte Carlo (VMC). We apply this approach in combination with diffusion Monte Carlo (DMC) to calculate binding energies for a positron e+ and a positronium Ps (the pseudoatomic electron–positron pair), bound to a set of atomic systems (H–, Li+, Li, Li–, Be+, Be, B–, C–, O– and F–). For PsB, PsC, PsO, and PsF, our VMC and DMC total energies are lower than that from previous calculations; hence, we redefine the state of the art for these systems. To assess our approach for molecules, we study the potential-energy surfaces (PES) of two hydrogen anions H– mediated by a positron (e+H22–), for which we calculate accurate spectroscopic properties by using a dense interpolation of the PES. We demonstrate the reliability and transferability of our correlated wave functions for electron–positron interactions with respect to state-of-the-art calculations reported in the literature. [less ▲]

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See detailAnisotropic Interlayer Force Field for Transition Metal Dichalcogenides: The Case of Molybdenum Disulfide
Wengen, Ouyang; Reut, Sofer; Xiang, Gao et al

in Journal of Chemical Theory and Computation (2021)

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See detailSoftware for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package
Evgeny Epifanovsky; Andrew T. B Gilbert; Xintian Feng et al

in Journal of Chemical Physics (2021)

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See detailMachine Learning Force Fields: Recent Advances and Remaining Challenges
Poltavskyi, Igor UL; Tkatchenko, Alexandre UL

in Journal of Physical Chemistry Letters (2021)

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See detailInteractions between large molecules pose a puzzle for reference quantum mechanical methods
Yasmine S. Al-Hamdani; Péter R. Nagy; Andrea Zen et al

in Nature Communications (2021)

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See detailMethyl-Induced Polarization Destabilizes the Noncovalent Interactions of N-Methylated Lysines
Sanim Rahman; Vered Wineman-Fisher; Peter Nagy et al

in Chemistry: A European Journal (2021)

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See detailMolecular basis for higher affinity of SARS-CoV-2 spike RBD for human ACE2 receptor
Julián M. Delgado; Nalvi Duro; David M. Rogers et al

in Wiley (2021)

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See detailMachine Learning Force Fields
Oliver T. Unke; Stefan Chmiela; Huziel E. Sauceda et al

in Chemical Reviews (2021)

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See detailPredictive QM/MM Modeling of Modulations in Protein–Protein Binding by Lysine Methylation
Sanim Rahman; Vered Wineman-Fisher; Yasmine Al-Hamdani et al

in Journal of Molecular Biology (2021)

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See detailQM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
Hoja, Johannes UL; Medrano Sandonas, Leonardo UL; Ernst, Brian G. et al

in Scientific Data (2021), 8(43),

We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for ≈4.2 million equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O ... [more ▼]

We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for ≈4.2 million equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O, S, Cl) atoms. To span this fundamentally important region of chemical compound space (CCS), QM7-X includes an exhaustive sampling of (meta-)stable equilibrium structures—comprised of constitutional/structural isomers and stereoisomers, e.g., enantiomers and diastereomers (including cis-/trans- and conformational isomers)—as well as 100 non-equilibrium structural variations thereof to reach a total of ≈4.2 million molecular structures. Computed at the tightly converged quantum-mechanical PBE0+MBD level of theory, QM7-X contains global (molecular) and local (atom-in-a-molecule) properties ranging from ground state quantities (such as atomization energies and dipole moments) to response quantities (such as polarizability tensors and dispersion coefficients). By providing a systematic, extensive, and tightly-converged dataset of quantum-mechanically computed physicochemical properties, we expect that QM7-X will play a critical role in the development of next-generation machine-learning based models for exploring greater swaths of CCS and performing in silico design of molecules with targeted properties. [less ▲]

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See detailDynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature
Huziel E. Sauceda; Vassilev Galindo, Valentin UL; Stefan Chmiela et al

in Nature Communications (2021)

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