000			02570nam a22002057a 4500
999			_c1054 _d1054
005			20210224121422.0
008			210224b ||||| |||| 00| 0 eng d
020			_a9781439836163
082			_a620.110 _bJUN
100			_aJune Gunn Lee
245			_aComputational materials science : _ban introduction _cLee June Gunn
260			_aBoca Raton, FL : _bTaylor & Francis, _c2011.
300			_axxi, 280 pages : _billustrations ; _c25 cm
505			_tChapter 1: Introduction -- _tChapter 2: Molecular dynamics -- _tChapter 3: MD exercises with xmd and lammps -- _tChapter 4: First-principles methods -- _tChapter 5: Density functional theory -- _tChapter 6: Treating solids -- _tChapter 7: DFT exercises with VASP --
520			_a"Preface No longer underestimated, computational science has emerged as a powerful partner to experimental and theoretical studies. Accelerated by the ever-growing power of computers and new computational methods, it is one of the fastest growing fields in science these days. Its predictive power in atomic and subatomic scales benefits all disciplines of science, and materials science is definitely one of them. Note that, for example, materials under extreme conditions such as high temperature or pressure, high radiation, on a very small scale, can be rather easily examined via the keyboard in computational materials science. Computational science has been a familiar subject in physics and chemistry, but in the materials field it was considered of secondary importance. It is now in the mainstream, and we have to catch up with the knowledge accumulated in the subject, which strongly involves physics and mathematics. Here, we are forced to deal with an obvious question: how much catch-up will be enough to cover the major topics and to perform computational works as materials researchers? Dealing with the entire field might be most desirable, but many certainly prefer to cover only the essential and necessary parts and would rather be involved in actual computational works. That is what this book is all about. As listed in the Further Readings sections in several chapters, a number of excellent and successful books are already available in this field. However, they are largely physics- or chemistry-oriented, full of theories, algorisms, and equations. It is quite difficult, if not impossible, for materials students to follow all those topics in detail
650			_aMaterials -- Mathematical models.
650			_a Materials -- Data processing.
650			_aMATHEMATICS -- Applied.
942			_2ddc _cBK