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Browsing by Author "Varga, Zoltan"

Now showing 1 - 3 of 3
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    Electronic structure data for ³A´ and ³A´´ N₂O
    (2020-10-28) Lin, Wei; Varga, Zoltan; Song, Guoliang; Paukku, Yuliya; Truhlar, Donald G; truhlar@umn.edu; Truhlar, Donald G; University of Minnesota Department of Chemistry
    This dataset constitutes the electronic structure data that was fitted to obtain global reactive potential energy surfaces (PESs) for Born-Oppenheimer collisions of oxygen atoms with nitrogen molecules. In particular it contains data for the lowest-energy ³Α´ and ³A´´ PESs for the high-energy reaction N₂(X ¹Σ) + O(³P) → NO(X ²Π) + N(⁴S); these potential energy surfaces can serve to generate forces for dynamics calculations. The data was obtained by multireference configuration interaction (MRCI) calculations that were improved by a dynamically scaled external correlation (DSEC) term. The MRCI calculations are based on wave functions obtained from state-averaged complete active space self-consistent-field calculations for 2280 geometries for the three lowest ³A´´ states and for 2298 geometries for the three lowest ³A´ states. The lowest-energy ³A´ and ³A´´ state at each of these geometries was then improved by applying the DSEC method to all MRCI points.
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    Electronic structure data of singlet N₄
    (2020-04-24) Varga, Zoltan; Paukku, Yuliya; Truhlar, Donald G; truhlar@umn.edu; Truhlar, Donald G; Truhlar Group, Department of Chemistry. UMN
    Calculated electronic structure energies by CASPT2/maug-cc-pVTZ and CCSD(T)/maug-cc-pVTZ for 21406 geometry points of the singlet N₄ system. These points can be used to fit the global potential energy surface of the ground state of singlet N₄.
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    PIPFit 2022
    (2022-02-14) Yang, Ke R; Varga, Zoltan; Parker, Kelsey A; Shu, Yinan; Truhlar, Donald G; truhlar@umn.edu; Truhlar, Donald G; Truhlar Research Group, Department of Chemistry, University of Minnesota
    The PIPFit 2022 program can be used to develop analytic representations of potential energy surfaces for three-body and four-body systems. A weighted least-squares fit is performed with permutationally invariant polynomials (PIPs) whose variables are Morse-like bond functions, Gaussians, mixed exponential–Gaussians (MEGs), or hyperbolic secant variables. Three kinds of fit can be performed with the program: