Dr. Denis Usvyat entwickelt hochgenaue quantenchemische Rechenmethoden zur Berechnung von Elektronenstrukturen in Festkörpern und Defekten. Sein aktueller Fokus liegt auf der Aperiodic Defect Model (ADM), einem neuen Ansatz, der Fehlstellen in Kristallen präziser simuliert als bisherige Superzellen-Methoden — ohne unphysikalische Artefakte und mit deutlich reduzierten Rechenkosten. Parallel arbeitet er an kostengünstigen Coupled-Cluster-Varianten (Tensor-Decomposed Distinguishable Cluster) und an der Validierung dieser Methoden gegen experimentelle Benchmarks. Für die Industrie relevant: präzisere Vorhersagen von Materialeigenschaften (Defekte, Stabilität, elektronische Eigenschaften) für Halbleiter, Batterien und andere Funktionsmaterialien; gleichzeitig trägt er zur FAIRmat-Dateninfrastruktur bei, um Forschungsdaten standardisiert verfügbar zu machen.
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Dr. Denis Usvyat
HU-FIS-Profil ↗Förderer: DFG Sachbeihilfe Zeitraum: 07/2017 - 10/2021 Projektleitung: Dr. Denis Usvyat
Förderer: DFG sonstige Programme Zeitraum: 10/2021 - 09/2026 Projektleitung: Prof. Dr. Dr. h.c. Claudia Draxl
Förderer: DFG sonstige Programme Zeitraum: 10/2021 - 12/2028 Projektleitung: Prof. Dr. Dr. h.c. Claudia Draxl
Science · DOI
Computation of lattice energies to an accuracy sufficient to distinguish polymorphs is a fundamental bottleneck in crystal structure prediction. For the lattice energy of the prototypical benzene crystal, we combined the quantum chemical advances of the last decade to attain sub-kilojoule per mole accuracy, an order-of-magnitude improvement in certainty over prior calculations that necessitates revision of the experimental extrapolation to 0 kelvin. Our computations reveal the nature of binding by improving on previously inaccessible or inaccurate multibody and many-electron contributions and provide revised estimates of the effects of temperature, vibrations, and relaxation. Our demonstration raises prospects for definitive first-principles resolution of competing polymorphs in molecular crystal structure prediction.
Journal of Computational Chemistry · DOI
A computational technique for solving the MP2 equations for periodic systems using a local-correlation approach and implemented in the CRYSCOR code is presented. The Hartree-Fock solution provided by the CRYSTAL program is used as a reference. The motivations for the implementation of the new code are discussed, and the techniques adopted are briefly recalled. With respect to the original formulation (Pisani et al., J Chem Phys 2005, 122, 094113), many new features have been introduced in CRYSCOR to improve its efficiency and robustness. In particular, an adaptation of the density fitting scheme to translationally periodic systems is described, based on Fourier transformation techniques. Three examples of application are provided, concerning the CO(2) crystal, proton transfer in ice XI, and the adsorption of methane on MgO (001). The results obtained with the periodic LMP2 method for these systems appear more reliable than the ones obtained using density functional theory.
Physical Review B · DOI
When solving the M\o{}ller-Plesset second order perturbation theory (MP2) equations for periodic systems using a local-correlation approach [J. Chem. Phys. 122 (2005) 094113], the computational bottleneck is represented by the evaluation of the two-electron Coulomb interaction integrals between product distributions, each involving a Wannier function and a projected atomic orbital. While for distant product distributions a multipolar approximation performs very efficiently, the four index transformation for close-by distributions, which by far constitutes the bottleneck of correlated electronic structure calculations of crystals, can be avoided through the use of density fitting techniques. An adaptation of that scheme to translationally periodic systems is described, based on Fourier transformation techniques. The formulas and algorithms adopted allow the point symmetry of the crystal to be exploited. Problems related to the possible divergency of lattice sums of integrals involving fitting functions are identified and eliminated through the use of Poisson transformed fitting functions and of dipole-corrected product distributions. The iterative scheme for solving the linear local MP2 (LMP2) equations is revisited. Prescreening in the evaluation of the residual matrix is introduced, which significantly lowers the scaling of the LMP2 equations.