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Книги з теми "Electronic Structure Calculations - Computational Methods"

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Автор: Grafiati
Опубліковано: 7 вересня 2023

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1

Royal Society of Chemistry. Faraday Division., ed. Molecular electronic structure calculations: Methods and applications. London: Royal Society of Chemistry, 1985.

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2

1950-, Wilson S., ed. Methods in computational chemistry. New York: Plenum, 1992.

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3

1950-, Wilson S., ed. Methods in computational chemistry. New York: Plenum, 1988.

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4

1950-, Wilson S., ed. Methods in computational chemistry. New York: Plenum, 1992.

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5

1950-, Wilson S., ed. Methods in computational chemistry. New York: Plenum Press, 1987.

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6

Alkauskas, Audrius. Advanced calculations for defects in materials: Electronic structure methods. Weinheim: Wiley-VCH, 2011.

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7

AEleen, Frisch, and Gaussian Inc, eds. Exploring chemistry with electronic structure methods. 2nd ed. Pittsburgh, PA: Gaussian, Inc., 1996.

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8

Computational methods for large systems: Electronic structure approaches for biotechnology and nanotechnology. Hoboken, N.J: Wiley, 2011.

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9

1938-, Kumar Vijay, Andersen O. K, Mookerjee Abhijit 1946-, and Working Group on "Disordered Alloys" (1992 : ICTP, Trieste, Italy), eds. Lectures on Methods of electronic structure calculations: Proceedings of the Miniworkshop on "Methods of Electronic Structure Calculations" and Working Group on "Disordered Alloys" : ICTP, Trieste, Italy, 10 August-4 September 1992. Singapore: World Scientific, 1994.

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10

Olle, Eriksson, Andersson Per, Delin Anna, Grechnyev Oleksiy, Alouani Mebarek, and SpringerLink (Online service), eds. Full-Potential Electronic Structure Method: Energy and Force Calculations with Density Functional and Dynamical Mean Field Theory. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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11

Kohanoff, Jorge. Electronic Structure Calculations for Solids and Molecules: Theory and Computational Methods. Cambridge University Press, 2010.

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12

Electronic Structure Calculations for Solids and Molecules: Theory and Computational Methods. Cambridge University Press, 2006.

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13

Lectures on Methods of Electronic Structure Calculations. World Scientific Pub Co Inc, 1995.

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14

Wilson, S. Methods in Computational Chemistry. Springer, 1987.

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15

Computational methods in condensed matter: Electronic structure. New York: American Institute of Physics, 1992.

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16

Anderson, O. K., and V. Kumar. Lectures on Methods of Electronic Structure Calculations: Proceedings of the Miniworkshop on "Methods of Electronic Structure Calculations" and Work. World Scientific Pub Co Inc, 1995.

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17

Wilson, S. Methods in Computational Chemistry. Springer, 1992.

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18

Wilson, S. Methods in Computational Chemistry. Springer, 1989.

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19

Methods in Computational Chemistry. Springer, 1993.

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20

Alkauskas, Audrius, Jörg Neugebauer, Peter Deák, Alfredo Pasquarello, and Chris G. Van de Walle. Advanced Calculations for Defects in Materials: Electronic Structure Methods. Wiley & Sons, Incorporated, John, 2011.

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21

Springborg, Michael. Methods of Electronic-Structure Calculations: From Molecules to Solids. Wiley, 2000.

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22

Alkauskas, Audrius, Jörg Neugebauer, Peter Deák, Alfredo Pasquarello, and Chris G. Van de Walle. Advanced Calculations for Defects in Materials: Electronic Structure Methods. Wiley & Sons, Incorporated, John, 2011.

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23

Alkauskas, Audrius, Jörg Neugebauer, Peter Deák, Alfredo Pasquarello, and Chris G. Van de Walle. Advanced Calculations for Defects in Materials: Electronic Structure Methods. Wiley & Sons, Incorporated, John, 2011.

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24

Springborg, Michael. Methods of Electronic-Structure Calculations: From Molecules to Solids. Wiley, 2000.

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25

Alkauskas, Audrius, Jörg Neugebauer, Peter Deák, Alfredo Pasquarello, and Chris G. Van de Walle. Advanced Calculations for Defects in Materials: Electronic Structure Methods. Wiley & Sons, Limited, John, 2011.

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26

Dyall, Kenneth G., and Knut Faegri. Introduction to Relativistic Quantum Chemistry. Oxford University Press, 2007. http://dx.doi.org/10.1093/oso/9780195140866.001.0001.

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Анотація:
This book provides an introduction to the essentials of relativistic effects in quantum chemistry, and a reference work that collects all the major developments in this field. It is designed for the graduate student and the computational chemist with a good background in nonrelativistic theory. In addition to explaining the necessary theory in detail, at a level that the non-expert and the student should readily be able to follow, the book discusses the implementation of the theory and practicalities of its use in calculations. After a brief introduction to classical relativity and electromagnetism, the Dirac equation is presented, and its symmetry, atomic solutions, and interpretation are explored. Four-component molecular methods are then developed: self-consistent field theory and the use of basis sets, double-group and time-reversal symmetry, correlation methods, molecular properties, and an overview of relativistic density functional theory. The emphases in this section are on the basics of relativistic theory and how relativistic theory differs from nonrelativistic theory. Approximate methods are treated next, starting with spin separation in the Dirac equation, and proceeding to the Foldy-Wouthuysen, Douglas-Kroll, and related transformations, Breit-Pauli and direct perturbation theory, regular approximations, matrix approximations, and pseudopotential and model potential methods. For each of these approximations, one-electron operators and many-electron methods are developed, spin-free and spin-orbit operators are presented, and the calculation of electric and magnetic properties is discussed. The treatment of spin-orbit effects with correlation rounds off the presentation of approximate methods. The book concludes with a discussion of the qualitative changes in the picture of structure and bonding that arise from the inclusion of relativity.
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27

Katsnelson, A. A., and V. S. Stepanyuk. Computational Methods in Condensed Matter: Electronic Structure (Aip Translation Series). AIP Press, 1992.

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28

Khoromskaia, Venera, and Boris Khoromskij. Tensor Numerical Methods in Electronic Structure Calculations: Basic Algorithms and Applications. De Gruyter, Inc., 2018.

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29

Reimers, Jeffrey R. Computational Methods for Large Systems: Electronic Structure Approaches for Biotechnology and Nanotechnology. Wiley & Sons, Incorporated, John, 2011.

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30

Reimers, Jeffrey R. Computational Methods for Large Systems: Electronic Structure Approaches for Biotechnology and Nanotechnology. Wiley & Sons, Incorporated, John, 2012.

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31

Reimers, Jeffrey R. Computational Methods for Large Systems: Electronic Structure Approaches for Biotechnology and Nanotechnology. Wiley & Sons, Incorporated, John, 2011.

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32

Recent Advances in Density Functional Methods Part III (Recent Advances in Computational Chemistry). World Scientific Publishing Company, 2002.

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33

Exploring Chemistry With Electronic Structure Methods: A Guide to Using Gaussian. Gaussian, Incorporated, 1993.

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34

Computational Chemistry Methodology in Structural Biology and Materials Sciences. Taylor & Francis Group, 2017.

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35

Ranjan, Prabhat, Anand Pandey, and Tanmoy Chakraborty. Computational Chemistry Methodology in Structural Biology and Materials Sciences. Apple Academic Press, Incorporated, 2017.

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36

Zaheer Ul-Haq and Angela K. Wilson, eds. Frontiers in Computational Chemistry: Volume 6. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150368481220601.

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Анотація:
Frontiers in Computational Chemistry presents contemporary research on molecular modeling techniques used in drug discovery and the drug development process: computer aided molecular design, drug discovery and development, lead generation, lead optimization, database management, computer and molecular graphics, and the development of new computational methods or efficient algorithms for the simulation of chemical phenomena including analyses of biological activity. The sixth volume of this series features these six different perspectives on the application of computational chemistry in rational drug design: 1. Computer-aided molecular design in computational chemistry 2. The role of ensemble conformational sampling using molecular docking & dynamics in drug discovery 3. Molecular dynamics applied to discover antiviral agents 4. Pharmacophore modeling approach in drug discovery against the tropical infectious disease malaria 5. Advances in computational network pharmacology for Traditional Chinese Medicine (TCM) research 6. Progress in electronic-structure based computational methods: from small molecules to large molecular systems of biological significance
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37

Andriotis, A. N., R. M. Sheetz, E. Richter, and M. Menon. Structural, electronic, magnetic, and transport properties of carbon-fullerene-based polymers. Edited by A. V. Narlikar and Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533053.013.21.

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Анотація:
This article discusses the structural, electronic, magnetic, and transport properties of carbon-fullerene-based polymers. In particular, it examines the defect-induced ferromagnetism of the C60-based polymers and its analog in the case of non-traditional inorganic materials. It first reviews the computational methods currently used in the literature, highlighting the pros and cons of each one of them. It then considers the defects associated with the ferromagnetism of the C60-based polymers, namely carbon vacancies, the 2 + 2 cycloaddition bonds and impurity atoms, and their effect on the electronic structure. It also evaluates the effect of codoping and goes on to describe the electronic, magnetic and transport properties of the rhombohedral C60-polymer. Finally, it looks at the origin of magnetic coupling among the magnetic moments in the rhombohedral C60-polymer and provides further evidence for the analogy between the magnetism of the rhombohedral C60-polymer and zinc oxide.
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38

Swendsen, Robert H. An Introduction to Statistical Mechanics and Thermodynamics. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198853237.001.0001.

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Анотація:
This is a textbook on statistical mechanics and thermodynamics. It begins with the molecular nature of matter and the fact that we want to describe systems containing many (1020) particles. The first part of the book derives the entropy of the classical ideal gas using only classical statistical mechanics and Boltzmann’s analysis of multiple systems. The properties of this entropy are then expressed as postulates of thermodynamics in the second part of the book. From these postulates, the structure of thermodynamics is developed. Special features are systematic methods for deriving thermodynamic identities using Jacobians, the use of Legendre transforms as a basis for thermodynamic potentials, the introduction of Massieu functions to investigate negative temperatures, and an analysis of the consequences of the Nernst postulate. The third part of the book introduces the canonical and grand canonical ensembles, which are shown to facilitate calculations for many models. An explanation of irreversible phenomena that is consistent with time-reversal invariance in a closed system is presented. The fourth part of the book is devoted to quantum statistical mechanics, including black-body radiation, the harmonic solid, Bose–Einstein and Fermi–Dirac statistics, and an introduction to band theory, including metals, insulators, and semiconductors. The final chapter gives a brief introduction to the theory of phase transitions. Throughout the book, there is a strong emphasis on computational methods to make abstract concepts more concrete.
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39

Fox, Raymond. The Use of Self. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780190616144.001.0001.

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Анотація:
This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; scaling laws from atomistic to continuum; and neural networks applications to chemical reaction dynamics. It is anticipated that this emerging field of NN in chemical reaction dynamics will play an increasingly important role in MD, MC, and quantum mechanical studies in the years to come.
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40

Raff, Lionel, Ranga Komanduri, Martin Hagan, and Satish Bukkapatnam. Neural Networks in Chemical Reaction Dynamics. Oxford University Press, 2012. http://dx.doi.org/10.1093/oso/9780199765652.001.0001.

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Анотація:
This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; scaling laws from atomistic to continuum; and neural networks applications to chemical reaction dynamics. It is anticipated that this emerging field of NN in chemical reaction dynamics will play an increasingly important role in MD, MC, and quantum mechanical studies in the years to come.
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41

Boero, Mauro, and Masaru Tateno. Quantum-theoretical approaches to proteins and nucleic acids. Edited by A. V. Narlikar and Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533046.013.17.

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Анотація:
This article describes quantum methods used to study proteins and nucleic acids: Hartree–Fock all-electron approaches, density-functional theory approaches, and hybrid quantum-mechanics/molecular-mechanics approaches. In addition to an analysis of the electronic structure, quantum-mechanical approaches for simulating proteins and nucleic acids can elucidate the cleavage and formation of chemical bonds in biochemical reactions. This presents a computational challenge, and a number of methods have been proposed to overcome this difficulty, including enhanced temperature methods such as high-temperature molecular dynamics, parallel tempering and replica exchange. Alternative methods not relying on the knowledge a priori of the final products make use of biasing potentials to push the initial system away from its local minimum and to enhance the sampling of the free-energy landscape. This article considers two of these biasing techniques, namely Blue Moon and metadynamics.
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