Books: 'Ab initio calculations'

1

Stein, Christopher J. Highly Accurate Spectroscopic Parameters from Ab Initio Calculations. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-14830-0.

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2

Searles, Debra J., and Ellak I. von Nagy-Felsobuki. Ab Initio Variational Calculations of Molecular Vibrational-Rotational Spectra. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-05561-8.

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3

Searles, D. Ab initio variational calculations of molecular vibrational-rotational spectra. Berlin: Springer-Verlag, 1993.

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4

Searles, D. Ab initio variational calculations of molecular vibrational-rotational spectra. Berlin: Springer-Verlag, 1994.

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5

Born, R. Ab initio calculations of conformational effects on ¹³C NMR spectra of amorphous polymers. Berlin: Springer, 1997.

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6

Born, R., and H. W. Spiess. Ab Initio Calculations of Conformational Effects on 13C NMR Spectra of Amorphous Polymers. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60644-1.

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7

Poirier, Raymond. Handbook of Gaussian basis sets: A compendium for Ab-initio molecular orbital calculations. Amsterdam: Elsevier, 1985.

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8

Roy, Kari, and Csizmadia I. G, eds. Handbook of Gaussian basis sets: A compendium for ab-initio molecular orbital calculations. Amsterdam: Elsevier, 1985.

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9

Simpson, Charles Q. Ab initio calculations on the structure and conformation of group V bent methallocenethiolates. Ithaca, N.Y: Cornell Theory Center, Cornell University, 1991.

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10

United States. National Aeronautics and Space Administration., ed. Accurate ab initio calculations which demonstrate a 3 Pi u ground state for Al₂. [Washington, DC: National Aeronautics and Space Administration, 1986.

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11

United States. National Aeronautics and Space Administration., ed. Accurate ab initio calculations which demonstrate a 3 Pi u ground state for Al₋b2₋s. [Washington, DC: National Aeronautics and Space Administration, 1986.

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12

Maezono, Ryo. Ab initio Calculation Tutorial. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0919-3.

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13

Dykstra, Clifford E. AB initio calculation of the structures and properties of molecules. Amsterdam: Elsevier, 1988.

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14

Pisani, Cesare, ed. Quantum-Mechanical Ab-initio Calculation of the Properties of Crystalline Materials. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-61478-1.

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15

C, Pisani, ed. Quantum-mechanical ab-initio calculation of the properties of crystalline materials. Berlin: Springer-Verlag, 1996.

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16

Kim, Gapsue. Ab initio calculation of the excited states of some diatomic molecular ions. [s.l.]: typescript, 1997.

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17

Cook, D. B. Ab Initio Valence Calculations in Chemistry. Elsevier Science & Technology Books, 2013.

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18

Cook, David B., and D. B. Cook. AB Initio Valence Calculations in Chemistry. Wiley & Sons, Incorporated, John, 2013.

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19

Velinova, Maria. Ab Initio Calculations: Methods and Applications. Arcler Education Inc, 2017.

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20

Urban, Miroslav, and Petr Carsky. Ab Initio Calculations: Methods and Applications in Chemistry. Springer, 2012.

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21

Mulliken, Robert. Diatomic Molecules: Results of Ab Initio Calculations. Elsevier Science & Technology Books, 2012.

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22

Mulliken, Robert S. Polyatomic Molecules: Results of Ab Initio Calculations. Elsevier Science & Technology Books, 2012.

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23

Searles, Debra J., and Ellak I. v. Nagy-Felsobuki. Ab Initio Variational Calculations of Molecular Vibrational-Rotational Spectra. Springer London, Limited, 2013.

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24

Spiess, H. W., R. Born, and J. Seelig. Ab Initio Calculations of Conformational Effects on 13C NMR Spectra of Amorphous Polymers. Springer London, Limited, 2012.

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25

Ab Initio Calculations of Conformational Effects on 13C NMR Spectra of Amorphous Polymers. Springer, 2012.

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26

Spiess, H. W., R. Born, and J. Seelig. Ab Initio Calculations of Conformational Effects on 13 C NMR Spectra of Amorphous Polymers. Springer Berlin / Heidelberg, 2011.

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27

Sapse, Anne-Marie, ed. Molecular Orbital Calculations for Biological Systems. Oxford University Press, 1998. http://dx.doi.org/10.1093/oso/9780195098730.001.0001.

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Molecular Orbital Calculations for Biological Systems is a hands-on guide to computational quantum chemistry and its applications in organic chemistry, biochemistry, and molecular biology. With improvements in software, molecular modeling techniques are now becoming widely available; they are increasingly used to complement experimental results, saving significant amounts of lab time. Common applications include pharmaceutical research and development; for example, ab initio and semi-empirical methods are playing important roles in peptide investigations and in drug design. The opening chapters provide an introduction for the non-quantum chemist to the basic quantum chemistry methods, ab initio, semi-empirical, and density functionals, as well as to one of the main families of computer programs, the Gaussian series. The second part then describes current research which applies quantum chemistry methods to such biological systems as amino acids, peptides, and anti-cancer drugs. Throughout the authors seek to encourage biochemists to discover aspects of their own research which might benefit from computational work. They also show that the methods are accessible to researchers from a wide range of mathematical backgrounds. Combining concise introductions with practical advice, this volume will be an invaluable tool for research on biological systems.

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28

Evarestov, R. A. Theoretical Modeling of Inorganic Nanostructures: Symmetry and Ab-Initio Calculations of Nanolayers, Nanotubes and Nanowires. Springer, 2015.

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29

Evarestov, R. A. Theoretical Modeling of Inorganic Nanostructures: Symmetry and ab-initio Calculations of Nanolayers, Nanotubes and Nanowires. Springer, 2015.

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30

Evarestov, R. A. Theoretical Modeling of Inorganic Nanostructures: Symmetry and Ab-Initio Calculations of Nanolayers, Nanotubes and Nanowires. Springer Berlin / Heidelberg, 2016.

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31

Evarestov, R. A. Theoretical Modeling of Inorganic Nanostructures: Symmetry and ab initio Calculations of Nanolayers, Nanotubes and Nanowires. Springer, 2020.

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32

Stein, Christopher. Highly Accurate Spectroscopic Parameters from Ab Initio Calculations: The Interstellar Molecules l-C3H+ and C4. Springer Spektrum, 2016.

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33

Stein, Christopher J. Highly Accurate Spectroscopic Parameters from Ab Initio Calculations: The Interstellar Molecules l-C3H+ and C4. Spektrum Akademischer Verlag GmbH, 2016.

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34

Evarestov, R. A. Theoretical Modeling of Inorganic Nanostructures: Symmetry and Ab Initio Calculations of Nanolayers, Nanotubes and Nanowires. Springer International Publishing AG, 2021.

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35

Devreese, J. T. Ab Initio Calculation of Phonon Spectra. Springer, 2011.

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36

AB Initio Calculation of Phonon Spectra. Springer, 2012.

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37

Janssen, Ted, Gervais Chapuis, and Marc de Boissieu. Origin and stability. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198824442.003.0006.

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The origin of the stability of aperiodic systems is very difficult to answer. Often the terms ‘competitive forces’ or ‘frustration’ have been proposed as the origin of stability. The role of Fermi surfaces and Brillouin zone boundary have also been invoked. This chapter deals with the numerous attempts which have been proposed for a better understanding. First, the Landau theory of phase transition, which has often been applied to understand the stability of incommensurate and composite systems, is presented here. Various semi-microscopic models are also proposed, in particular the Frenkel–Kontorova and Frank–Van der Merwe models, as well as spin models. Phase diagrams have been calculated with some success with the ANNI and DIFFOUR models. For quasicrystals, only the simplest general features are found in model systems. For a better understanding, more complex calculations are required, using, for example, ab initio methods. The chapter also discusses electronic instabilities, charge-density systems, Hume–Rothery compounds, and the growth of quasicrystals.

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38

Quantum-Mechanical Ab-initio Calculation of the Properties of Crystalline Materials. Springer, 2011.

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39

Pisani, Cesare. Quantum-Mechanical Ab-Initio Calculation of the Properties of Crystalline Materials. Springer London, Limited, 2012.

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40

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

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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

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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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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42

Allen, Michael P., and Dominic J. Tildesley. Quantum simulations. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0013.

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This chapter covers the introduction of quantum mechanics into computer simulation methods. The chapter begins by explaining how electronic degrees of freedom may be handled in an ab initio fashion and how the resulting forces are included in the classical dynamics of the nuclei. The technique for combining the ab initio molecular dynamics of a small region, with classical dynamics or molecular mechanics applied to the surrounding environment, is explained. There is a section on handling quantum degrees of freedom, such as low-mass nuclei, by discretized path integral methods, complete with practical code examples. The problem of calculating quantum time correlation functions is addressed. Ground-state quantum Monte Carlo methods are explained, and the chapter concludes with a forward look to the future development of such techniques particularly to systems that include excited electronic states.

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Books on the topic 'Ab initio calculations'

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