University of Hyderabad, India

A chemist applauds an algorithm able to predict crystal structures from chemical composition alone.

I work in crystal engineering, a field that involves designing and constructing crystals with desired physical, chemical or pharmaceutical properties from small organic molecules. It is an experimental science based on pattern recognition and retrosynthetic strategies, in which the structure is considered as the sum of smaller, simpler parts.

Improvements to computational crystal-structure prediction could make design protocols more reliable. But this is such a difficult problem that only a handful of groups in the field work on it. In this context, I found a recent paper presenting a seemingly reliable method to be thought-provoking (A. R. Oganov and C. W. Glass J. Chem. Phys. 124, 244704; 2006).

Typically, crystal-structure prediction involves computer generation of putative crystal structures using a force field, which represents the interactions between atoms in neighbouring molecules. The correct structure is presumed to be that which minimizes the crystal’s energy.

The procedure is problematic because the force fields may not be well tailored to the molecules being studied, and because the experimental structure may not be the lowest-energy arrangement. It is also impossible to explore all conceivable structures, which are mind-boggling in number.

Oganov and Glass use an evolutionary algorithm to localize the search to the most promising structures. Their approach is attractive in that it requires no system-specific knowledge — the input is just the molecule’s chemical composition, not even its structure — and their ability to predict the unusual tetragonal structure of urea is impressive.

Is this the long-awaited breakthrough in crystal engineering? Perhaps not, but surely it’s an important step forward.