Design and discovery of materials guided by theory and computation

Computational materials science and engineering has emerged as an interdisciplinary subfield spanning materials science and engineering, condensed matter physics, chemistry, mechanics and engineering in general. Modern materials research often requires a close integration of computation and experiments in order to fundamentally understand the materials structures and properties and their relation to synthesis and processing. A number of computational methods and tools at different spatio-temporal scales are now well established, ranging from electronic structure calculations based on density functional theory, 1, 2 atomic molecular dynamics 3, 4 and Monte Carlo techniques, 5 phase-field method 6 – 9 to continuum macroscopic approaches. Over the last few years, computational materials activities have been steadily moving from technique development and purely computational studies of materials towards discovering and designing new materials guided by computation, machine learning and data mining or by a closely tied combination of computational predictions and experimental validation. This movement is being further accelerated by the recent initiatives by various government agencies in the United States, Europe, China and other countries to pursue the materials genome initiative, 10 integrated computational materials engineering 11 – 13 as well as the ‘Big Data’ initiative.