Atomistic Simulation Methods in Solid Mechanics

Many exciting problems in mechanics are multiscale in nature. For example, the failure of materials involves breaking of chemical bonds at the atomic scale and crack spreading at larger scales. Mechanics of the cell as a material is defined by the cytoskeleton networks and membrane, as built up from proteins and lipids at the molecular level. To solve these problems, one must be equipped with techniques that are able to address the multiphysics nature at different space and time scales and successfully bridging them. Recently, rapid progresses in micro-, nanomechanics and mechanics of biological materials urges the development of theoretical models and numerical techniques within this scenario. The goal of this book is to bring a pedestrian introduction and in-depth discussion on the key ideas and challenges. In this book, we aim to present the developing field of atomistic simulation methods and their applications in solid mechanics, in a self-contained way. The first part (the algorithm) will cover basics in quantum, classical and statistical mechanics knowledge, also basic concepts and physics of solid mechanics. With this background, the algorithm of molecular dynamics and relative methods such as Monte-Carlo methods are introduced as well. The second part of the book focuses on a number of hot topics in the current mechanics community, from failure of materials, nanomechanics, to mechanics of biological materials. In the third part, extended discussion on novel methods for solving multiscale solid mechanics problems are introduced. Some of them are fresh and still under development at the time the manuscript is prepared and are believed by the authors to be the future direction in this field.The book addresses theoretical issues, and detailed numeric algorithms as well. The readers are assumed to have basic knowledge in engineering mechanics and college physics. Some experience with physical chemistry or solid-state physics will be helpful. Illustrative examples and problems are prepared after many chapters for self-study purposes.