Titlebook: Computational Materials Science; From Ab Initio to Mo Kaoru Ohno,Keivan Esfarjani,Yoshiyuki Kawazoe Textbook 2018Latest edition Springer-Ve

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Boban Arsenijevi?,Berit Gehrke,Rafael Marínsembling. The macroscopic behaviors of such systems are rather different from the microscopic laws in the world of atoms and molecules. For example, in the usual cases of macroscopic systems, the motion of the atoms and molecules can be regarded simply as heat. That is, the average kinetic energy of

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Quantum Monte Carlo (QMC) Methods,Since Metropolis’s work, the Monte Carlo method has been applied not only to various statistical problems of classical systems, but also to many quantum mechanical systems. In this chapter, we briefly describe the extension of the Monte Carlo method to quantum mechanical systems.

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https://doi.org/10.1007/978-3-662-56542-1Ab-initio Methods; Coarse Graining; Computational Materials Science; Empirical Methods; First Principles

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978-3-662-58587-0Springer-Verlag GmbH Germany, part of Springer Nature 2018

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Empirical Methods and Coarse-Graining, much accuracy and reliability. In principle, it is possible to construct realistic classical potentials based on ab initio calculations. A possible methodology here is to determine classical potentials by, for example, fitting them to contour maps of the total energy, which may be obtained with an

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Boban Arsenijevi?,Berit Gehrke,Rafael Marínmory alloys, liquid flows, surface tension of liquids, swelling of polymers by water absorption, etc. Sometimes such cooperative motions are frozen as the temperature decreases. In this case, the states which have been realized at higher temperatures become unstable.