Nature-inspired crystal structure predictor

phys.org | 11/12/2018 | Staff
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Scientists from Russia have reported a way to improve crystal structure prediction algorithms, making the discovery of new compounds multiple times faster. The results of the study were published in Computer Physics Communications.

Given the ever-increasing need for new technologies, chemists seek higher-performance materials with better strength, weight, stability and other properties. The search for new materials is a challenging task, and if performed experimentally, takes a lot of time and money, as it often requires trying a huge number of compounds at different conditions. Computers can assist with this, but they require good algorithms.

Artem - R - Oganov - Professor - Skoltech

In 2005, Artem R. Oganov, now professor of Skoltech and Moscow Institute of Physics and Technology (MIPT), developed the evolutionary crystal structure prediction algorithm USPEX, perhaps the most successful algorithm in the field, now used by several thousand scientists worldwide. USPEX only needs to know which atoms the crystal is made of. Then it generates a small number of random structures whose stability is assessed based on the energy of interaction between the atoms. Next, an evolutionary mechanism accounts for natural selection, crossover and mutations of the structures and their descendants, resulting in particularly stable compounds.

In their recent study, scientists from Skoltech, MIPT and Samara State Technical University, led by Artem R. Oganov, improved USPEX's first step, which generates initial structures. Showing that purely random generation is...
(Excerpt) Read more at: phys.org
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