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      Adsorption of 1-chloro-1,2,2,2-tetrafluoroethane on pristine, Al, Ga-doped boron nitride nanotubes: a study involving PBC-DFT, NBO analysis, and QTAIM

      1 , 2
      Canadian Journal of Chemistry
      Canadian Science Publishing

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          Abstract

          In the present investigation, the feasibility of detecting the 1-chloro-1,2,2,2-tetrafluoroethane gas molecule on the outer surface of pristine single-walled boron nitride nanotube, as well as its aluminium- and gallium-doped structures, was carefully evaluated. For achieving this goal, a periodic boundary condition density functional theory level of study using both HSE06 and B3LYP-D3 functionals together with a 6-311G(d) basis set has been used. Subsequently, the CAM-B3LYP, ωB97XD, and M06-2X functionals with a 6-311G(d) basis set were also employed to consider the single point energies. Natural bond orbital and quantum theory of atoms in molecules were implemented by using the HSE06/6-311G(d) method and the results were compatible with the electronic properties. In this regard, the total density of state, the Wiberg bond index, natural charge, natural electron configuration, donor–acceptor natural bond orbital interactions, and the second-order perturbation energies are performed to explore the nature of the intermolecular interactions. All of the energy calculations and population analyses show that by adsorbing of the gas molecule onto the surface of the considered nanostructures, the intermolecular interactions are of the type of strong chemical adsorption. Between the doped nanotubes, aluminium-doped nanotube has very high adsorption energy compared with gallium. Generally, it was revealed that the sensitivity of the adsorption will be increased when the gas molecule interacts with decorated nanotubes and decrease the HOMO–LUMO band gap; therefore, the change of electronic properties can be used to design suitable nanosensors.

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          Generalized Gradient Approximation Made Simple

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            A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu.

            The method of dispersion correction as an add-on to standard Kohn-Sham density functional theory (DFT-D) has been refined regarding higher accuracy, broader range of applicability, and less empiricism. The main new ingredients are atom-pairwise specific dispersion coefficients and cutoff radii that are both computed from first principles. The coefficients for new eighth-order dispersion terms are computed using established recursion relations. System (geometry) dependent information is used for the first time in a DFT-D type approach by employing the new concept of fractional coordination numbers (CN). They are used to interpolate between dispersion coefficients of atoms in different chemical environments. The method only requires adjustment of two global parameters for each density functional, is asymptotically exact for a gas of weakly interacting neutral atoms, and easily allows the computation of atomic forces. Three-body nonadditivity terms are considered. The method has been assessed on standard benchmark sets for inter- and intramolecular noncovalent interactions with a particular emphasis on a consistent description of light and heavy element systems. The mean absolute deviations for the S22 benchmark set of noncovalent interactions for 11 standard density functionals decrease by 15%-40% compared to the previous (already accurate) DFT-D version. Spectacular improvements are found for a tripeptide-folding model and all tested metallic systems. The rectification of the long-range behavior and the use of more accurate C(6) coefficients also lead to a much better description of large (infinite) systems as shown for graphene sheets and the adsorption of benzene on an Ag(111) surface. For graphene it is found that the inclusion of three-body terms substantially (by about 10%) weakens the interlayer binding. We propose the revised DFT-D method as a general tool for the computation of the dispersion energy in molecules and solids of any kind with DFT and related (low-cost) electronic structure methods for large systems.
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              Multiwfn: a multifunctional wavefunction analyzer.

              Multiwfn is a multifunctional program for wavefunction analysis. Its main functions are: (1) Calculating and visualizing real space function, such as electrostatic potential and electron localization function at point, in a line, in a plane or in a spatial scope. (2) Population analysis. (3) Bond order analysis. (4) Orbital composition analysis. (5) Plot density-of-states and spectrum. (6) Topology analysis for electron density. Some other useful utilities involved in quantum chemistry studies are also provided. The built-in graph module enables the results of wavefunction analysis to be plotted directly or exported to high-quality graphic file. The program interface is very user-friendly and suitable for both research and teaching purpose. The code of Multiwfn is substantially optimized and parallelized. Its efficiency is demonstrated to be significantly higher than related programs with the same functions. Five practical examples involving a wide variety of systems and analysis methods are given to illustrate the usefulness of Multiwfn. The program is free of charge and open-source. Its precompiled file and source codes are available from http://multiwfn.codeplex.com. Copyright © 2011 Wiley Periodicals, Inc.
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                Author and article information

                Journal
                Canadian Journal of Chemistry
                Can. J. Chem.
                Canadian Science Publishing
                0008-4042
                1480-3291
                January 2021
                January 2021
                : 99
                : 1
                : 51-62
                Affiliations
                [1 ]School of Chemistry, College of Science, University of Tehran, Tehran 14176, Iran.
                [2 ]Physics Education Department, Faculty of Education, Tishk International University, 44001, Erbil, Iraq.
                Article
                10.1139/cjc-2020-0309
                d5693624-e07e-4a11-a0ec-13f909ccb75f
                © 2021

                http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining

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