The 2013 International Workshop on Multiscale Modeling and Simulation in Materials Science

The 2013 International Workshop on Multiscale Modeling and Simulation in Materials Science will be held April 21 - April 23, 2013, in the Institute of Natural Sciences (Room 601, Pao Yue-Kong Library, North Entrance), Shanghai Jiao Tong University, Shanghai, China. Abstract The last two decades has seen remarkable developments in multi-scale modeling and simulation for materials science. By now, it has become a vibrant and stimulating discipline, with a significant impact on materials science, mechanics and mathematics. Materials science provides a rich source of problems in various fields of mathematics and mechanics, these problems often have a multi-scale character. For example, multi-scale issues can be raised by purely continuum model such as phase field models and dislocation dynamics. Mathematical techniques such as homogenization and relaxation can be used to transfer information from micro-scale (atomic and/or electronic) structure to macro-scale (continuum) property of materials. Furthermore, analysis of multi-scale computational methods, e.g., atomistic/continuum coupling methods, requires the development of new mathematical and numerical tools. Substantial progress has been made for static problems under the framework of calculus of variation and nonlinear PDEs, while dynamic/evolution problems remain to be a major challenge. The field of materials science has been and continues to be revolutionized by the availability of experiments and theoretical advances in multi-scale methods based on advanced mathematical methods. For example, the ability to design materials with intricate features on an almost atomistic level calls for a solid theoretical foundation. Greater interdisciplinary participation of materials scientists, mechanical engineers and mathematicians are needed to address fundamental questions related to the development of computational materials simulations and design, to improve the efficiency and reliability and to enhance the predictive power of computation.