Algorithmic innovation enables sustainable technology from atoms to materials
The qualities of crystalline materials are determined by their structures, which enable critical technologies. Thus, crystal structure prediction can be essential in developing new functional materials. Researchers created effective methods for identifying structural minima on the potential energy surface. The University of Liverpool presents a mathematical method that can predict the structure of any material based on its atoms.
The algorithm, developed by an interdisciplinary team of researchers from the Departments of Chemistry and Computer Science at the University of Liverpool, systematically evaluates entire sets of possible structures at once, rather than considering them one at a time, to speed up the identification of the correct solution.
This discovery enables the identification of materials that can be manufactured and, in many circumstances, the prediction of their properties. The new method was shown on quantum computers, which have the potential to solve many problems faster than classical computers, allowing calculations to be even faster.
New materials are required to fulfill the net zero challenge, such as batteries, solar absorbers for clean power, low-energy computing, and catalysts for clean polymers and chemicals for our sustainable future.
This search is slow and complex due to the countless ways atoms may be joined to form materials, and predicting a structure about which nothing is known is a huge scientific problem.
Professor Matt Rosseinsky, from the University’s Department of Chemistry and Materials Innovation Factory, said: “Having certainty in the prediction of crystal structures now offers the opportunity to identify from the whole of the space of chemistry exactly which materials can be synthesized and the structures that they will adopt, giving us for the first time the ability to define the platform for future technologies.”
He added, “With this new tool, we will be able to define how to use those chemical elements that are widely available and begin to create materials to replace those based on scarce or toxic elements, as well as to find materials that outperform those we rely on today, meeting the future challenges of a sustainable society.”
According to Professor Paul Spirakis of the University’s Department of Computer Science, the general technique for crystal structure prediction may be applied to a variety of structures. The new study aims to investigate and apply more algorithmic ideas to discover new and valuable materials, collaborating with chemists and computer scientists.
The potential energy surface crater, with its jagged mountains, hills, and valleys, correlates to the atomistic structure of the garnet crystal. The lowest-lying vertex may be located using sophisticated algorithms and quantum computers. After a small adjustment, the garnet structure is revealed, which has an optimality guarantee.
The Royal Society and Leverhulme Trust provided funding for the study.
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