There are a couple journals dedicated to computational materials science. Two active fields are phase field models and molecular dynamics. Phase field models a

There are a couple journals dedicated to computational materials science. Two active fields are phase field models and molecular dynamics. Phase field models are mesoscale continuum (PDE) models based on the Cahn-Hilliard and Allen-Cahn equations, and are useful for things like predicting crystal grain growth and reorganization under strain, as well as fracture and many other uses. In phase-field modeling, the interesting physics is a consequence of the free energy functional, which is phenomenological and different for each material, so software should make it as easy as possible to turn specification of the free energy into an accurate and efficient massively parallel simulation. One such approach is outlined in this paper [1] from some colleagues. The resulting discrete systems are stiff and have positivity properties that must be preserved, so scalable implicit solvers (like multigrid) as well as methods for variational inequalities are necessary. In molecular dynamics, there are many parallel scalability and expressivity challenges. Fast algorithms for long-range interactions (such as the fast multipole method) lead to less regular computational, but huge asymptotic (O(n) versus O(n^2)). Since better algorithms become more important as our hardware allows us to keep scaling up the problem sizes, Fast methods need to be applied in more places. There is also a lot of activity in multiscale modeling and numerical homogenization, where explicit microscale models (often kinetic) are used to provide missing components of meso/macro-scale continuum models. [1] http://dx.doi.org/10.1016/j.commatsci.2011.07.028 http://dx.doi.org/10.1016/j.commatsci.2011.07.028