Computational materials science is one of the fastest growing disciplines in the field today, probably because it offers researchers the opportunity to model so many possibilities in both a time and cost effective manner. For example the predictive opportunities inherent in the science of computational materials science has made it one of the most important disciplines especially within biomaterials science, such as developing computational prediction in gene function.

It's not only in the field of biomaterials that we have seen opportunities for computational materials science; in the field of aviation for example to test the properties of new materials, scientists are now able to model strength and other properties under various conditions, quite easily. Modeling at the atomic level in the laboratory before moving to larger scale semi tech plants for further testing has also become routine.

Along with this growing reliance on software comes a warning from scientists, which was recently reported in the journal Science; we might see inaccurate interpretation of data or even high profile failures as some scientists may not have a thorough understanding of what the software is really doing.

Particularly now when we are witness to so many industrial applications of research the consequences of not fully understanding the software in question could be very high.

As with most black box technologies the remedy will be to open the lid and make freely available the source code for scrutiny and a clearer understanding of what is actually happening underneath the lid.

Ultimately what will help this growing field of science is a closer collaboration between software engineers and scientists.