Author Description

Computational modeling of materials behavior by multiscale materials modeling (MMM) approaches is becoming a reliable tool to underpin scientific investigations and to complement traditional theoretical and experimental approaches of component assessment. At transitional (or microstructure) scales continuum approaches begin to break down and atomistic methods reach inherent limitations in time and length scale. Transitional theoretical frameworks and modeling techniques are developed to bridge the gap between the different length scales. Industrial success in high technology fields relies on the possibility to specifically engineer materials and products with improved performance. The success factor is the ability to make these material related developments timely at relatively low-costs. This demands not only the rapid development of new or improved processing techniques but also better understanding and control of material chemistry, processing, structure, performance, durability, and their relationships. This scenario usually involves multiple length (space) & time scales and multiple processing & performance stages, which are usually only accessible via multi-scale / multi-stage modeling or simulation. In high-payoff, high-risk technologies such as the design of large structures in the aerospace and nuclear industries, the effects of aging and environment on failure mechanisms cannot be left to conservative approaches. Increasing efforts are now focused on developing MMM approaches to develop new material systems (components and devices). Appropriate validation experiments are crucial to verify that the models predict the correct behavior at each length scale. Thus, one of the advantages of these MMM approaches is that, at each scale, physically meaningful parameters are predicted and used in models for subsequent scales, avoiding the use of empiricism and fitting parameters. Recent interest in nanotechnology is challenging the scientific community to design na