Publications by authors named "D Usvyat"

To date, computational methods for modeling defects (vacancies, adsorbates, etc.) have relied on periodic supercells in which the defect is far enough from its repeated image that they can be assumed non-interacting. Yet, the relative proximity and periodic repetition of the defect's images may lead to spurious, unphysical artifacts, especially if the defect is charged and/or open-shell, causing a very slow convergence to the thermodynamic limit (TDL).

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We present a cost-reduced approach for the distinguishable cluster approximation to coupled cluster with singles, doubles, and iterative triples (DC-CCSDT) based on a tensor decomposition of the triples amplitudes. The triples amplitudes and residuals are processed in the singular-value-decomposition (SVD) basis. Truncation of the SVD basis according to the values of the singular values together with the density fitting (or Cholesky) factorization of the electron repulsion integrals reduces the scaling of the method to N6, and the DC approximation removes the most expensive terms of the SVD triples residuals and at the same time improves the accuracy of the method.

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In light of the recent discrepancies reported between fixed node diffusion Monte Carlo and local natural orbital coupled cluster with single, double, and perturbative triples [CCSD(T)] methodologies for non-covalent interactions in large molecular systems [Al-Hamdani et al., Nat. Commun.

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Article Synopsis
  • - The study focuses on improving simulations of energy storage materials, specifically examining the cathode material LiCoNiO in Lithium batteries, by using advanced quantum chemical calculations to analyze Lithium hopping barriers.
  • - Various computational methods, including Hartree-Fock and density functional theory, were employed to calculate the Lithium diffusion coefficient, revealing that results were consistent across different approaches, which is unusual.
  • - The findings suggest that although static correlation is significant, it tends to cancel out in energy differences, leading to a best estimate for the reaction barrier of approximately 0.85 eV.
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The hybrid QM:QM approach is extended to adsorption on transition metal surfaces. The random phase approximation (RPA) as the high-level method is applied to cluster models and, using the subtractive scheme, embedded in periodic models which are treated with density functional theory (DFT) that is the low-level method. The PBE functional, both without dispersion and augmented with the many-body dispersion (MBD), is employed.

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