Computational materials science :
Lee, June Gunn.
Computational materials science : an introduction / June Gunn Lee. - Boca Raton, FL : Taylor & Francis, 2011. - xxi, 280 p. : ill. ; 25 cm.
Includes bibliographical references and index.
1 Introduction1.1 Computational Materials Science1.2 Methods in Computational Materials Science1.3 ComputersReferencesChapter 2 Molecular Dynamics (MD)2.1 Introduction2.2 Potentials2.3 Solutions for Newton's Equations of Motion2.4 Initialization2.5 Integration and Equilibration2.6 Data ProductionHomeworkFurther ReadingReferencesChapter 3 MD Exercises with XMD and LAMMPS3.1 Potential Curve of Al3.2 Melting of Ni Cluster3.3 Sintering of Ni Nano-particles3.4 Speed Distribution of Ar Gas: A Computer Experiment3.5 SiC Deposition on Si(001)3.6 Yield mechanism of Au Nano-wire 3.7 Water Nano-droplet Wrapped by Graphene Nano-ribbon (GNR)3.8 Stress-strain Behavior of Si-CNT CompositeHomeworkReferencesChapter 4 First-Principles Methods4.1 Quantum Mechanics: The Beginning4.2 Schroedinger's Wave Equation4.3 Early First-principles CalculationsHomeworkFurther ReadingReferencesChapter 5 Density Functional Theory (DFT)5.1 Introduction5.2 Kohn-Sham (KS) Approach5.3 Kohn-Sham (KS) Equations5.4 Exchange-correlation (XC) Functionals5.5 Solving Kohn-Sham (KS) Equations5.6 DFT Extensions and LimitationsHomeworkFurther ReadingReferencesChapter 6 Treating Solids6.1 Pseudo-potential (PP) Approach6.2 Reducing the Calculation Size6.3 Bloch Theorem6.4 Plane-wave (PW) Expansions6.5 Some Practical Topics6.6 Practical Algorithms for DFT RunsHomeworkFurther ReadingReferencesChapter 7 DFT Exercises with VASP7.1 VASP (Vienna ab-initio Simulation Package)7.2 Pt-atom7.3 Pt-FCC7.4 Convergence Tests7.5 Pt-bulk7.6 Pt(111)-surface7.7 Nudged Elastic Band (Neb) Method7.8 Pt(111)-catalyst7.9 Band Structure of Silicon (Si)7.10 Band Structure of Silicon (Si)-HSE067.11 Phonon Calculation for Silicon (Si)7.12 W12C9-Co28-interface7.13 Li2MnO3 Battery System with GGA+U Method7.14 Using GUI for VASP Calculations
"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"--
9781439836163
Materials
Materials
Molecular dynamics
Physical & Theoretical Chemistry
Material Science--Mathematical models.--Data processing.--Mathematics.
620.110 / LEE
Computational materials science : an introduction / June Gunn Lee. - Boca Raton, FL : Taylor & Francis, 2011. - xxi, 280 p. : ill. ; 25 cm.
Includes bibliographical references and index.
1 Introduction1.1 Computational Materials Science1.2 Methods in Computational Materials Science1.3 ComputersReferencesChapter 2 Molecular Dynamics (MD)2.1 Introduction2.2 Potentials2.3 Solutions for Newton's Equations of Motion2.4 Initialization2.5 Integration and Equilibration2.6 Data ProductionHomeworkFurther ReadingReferencesChapter 3 MD Exercises with XMD and LAMMPS3.1 Potential Curve of Al3.2 Melting of Ni Cluster3.3 Sintering of Ni Nano-particles3.4 Speed Distribution of Ar Gas: A Computer Experiment3.5 SiC Deposition on Si(001)3.6 Yield mechanism of Au Nano-wire 3.7 Water Nano-droplet Wrapped by Graphene Nano-ribbon (GNR)3.8 Stress-strain Behavior of Si-CNT CompositeHomeworkReferencesChapter 4 First-Principles Methods4.1 Quantum Mechanics: The Beginning4.2 Schroedinger's Wave Equation4.3 Early First-principles CalculationsHomeworkFurther ReadingReferencesChapter 5 Density Functional Theory (DFT)5.1 Introduction5.2 Kohn-Sham (KS) Approach5.3 Kohn-Sham (KS) Equations5.4 Exchange-correlation (XC) Functionals5.5 Solving Kohn-Sham (KS) Equations5.6 DFT Extensions and LimitationsHomeworkFurther ReadingReferencesChapter 6 Treating Solids6.1 Pseudo-potential (PP) Approach6.2 Reducing the Calculation Size6.3 Bloch Theorem6.4 Plane-wave (PW) Expansions6.5 Some Practical Topics6.6 Practical Algorithms for DFT RunsHomeworkFurther ReadingReferencesChapter 7 DFT Exercises with VASP7.1 VASP (Vienna ab-initio Simulation Package)7.2 Pt-atom7.3 Pt-FCC7.4 Convergence Tests7.5 Pt-bulk7.6 Pt(111)-surface7.7 Nudged Elastic Band (Neb) Method7.8 Pt(111)-catalyst7.9 Band Structure of Silicon (Si)7.10 Band Structure of Silicon (Si)-HSE067.11 Phonon Calculation for Silicon (Si)7.12 W12C9-Co28-interface7.13 Li2MnO3 Battery System with GGA+U Method7.14 Using GUI for VASP Calculations
"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"--
9781439836163
Materials
Materials
Molecular dynamics
Physical & Theoretical Chemistry
Material Science--Mathematical models.--Data processing.--Mathematics.
620.110 / LEE