9
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Challenges in large scale quantum mechanical calculations : Challenges in large scale quantum mechanical calculations

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references179

          • Record: found
          • Abstract: not found
          • Article: not found

          Self-consistent-charge density-functional tight-binding method for simulations of complex materials properties

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            QM/MM methods for biomolecular systems.

            Combined quantum-mechanics/molecular-mechanics (QM/MM) approaches have become the method of choice for modeling reactions in biomolecular systems. Quantum-mechanical (QM) methods are required for describing chemical reactions and other electronic processes, such as charge transfer or electronic excitation. However, QM methods are restricted to systems of up to a few hundred atoms. However, the size and conformational complexity of biopolymers calls for methods capable of treating up to several 100,000 atoms and allowing for simulations over time scales of tens of nanoseconds. This is achieved by highly efficient, force-field-based molecular mechanics (MM) methods. Thus to model large biomolecules the logical approach is to combine the two techniques and to use a QM method for the chemically active region (e.g., substrates and co-factors in an enzymatic reaction) and an MM treatment for the surroundings (e.g., protein and solvent). The resulting schemes are commonly referred to as combined or hybrid QM/MM methods. They enable the modeling of reactive biomolecular systems at a reasonable computational effort while providing the necessary accuracy.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              The SIESTA method for ab initio order-N materials simulation

              We have developed and implemented a self-consistent density functional method using standard norm-conserving pseudopotentials and a flexible, numerical LCAO basis set, which includes multiple-zeta and polarization orbitals. Exchange and correlation are treated with the local spin density or generalized gradient approximations. The basis functions and the electron density are projected on a real-space grid, in order to calculate the Hartree and exchange-correlation potentials and matrix elements, with a number of operations that scales linearly with the size of the system. We use a modified energy functional, whose minimization produces orthogonal wavefunctions and the same energy and density as the Kohn-Sham energy functional, without the need of an explicit orthogonalization. Additionally, using localized Wannier-like electron wavefunctions allows the computation time and memory, required to minimize the energy, to also scale linearly with the size of the system. Forces and stresses are also calculated efficiently and accurately, thus allowing structural relaxation and molecular dynamics simulations.
                Bookmark

                Author and article information

                Journal
                Wiley Interdisciplinary Reviews: Computational Molecular Science
                WIREs Comput Mol Sci
                Wiley
                17590876
                January 2017
                January 2017
                November 07 2016
                : 7
                : 1
                : e1290
                Affiliations
                [1 ]Argonne Leadership Computing Facility; Argonne National Laboratory; Lemon IL USA
                [2 ]Department of Computer Applications in Science and Engineering; Barcelona Supercomputing Center (BSC-CNS); Barcelona Spain
                [3 ]University Grenoble Alpes; INAC-MEM; Grenoble France
                [4 ]CEA, INAC-MEM; Grenoble France
                [5 ]Laboratoire de Biologie Structurale et Radiologie, Service de Bioénergétique, Biologie Structurale et Mécanisme; Institut de Biologie et de Technologie de Saclay, CEA Saclay; Gif-sur-Yvette Cedex France
                Article
                10.1002/wcms.1290
                658b86d8-4583-4249-9edd-25cee9d5b42b
                © 2016

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://onlinelibrary.wiley.com/termsAndConditions#am

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                History

                Comments

                Comment on this article