The atomistic structure of the crystalline material garnet corresponds to the crater on a potential energy surface full of rough mountains, hills and valleys. Finding it computationally is very hard, but by fixing a mesh on this surface, advanced algorithms and quantum computers can be used to find the lowest lying vertex. A subsequent tweak reveals the garnet structure. Image: University of Liverpool.New research at the University of Liverpool in the UK could signal a step-change in the quest to design the new materials that are needed to meet the challenge of net zero and a sustainable future.
The Liverpool researchers have developed a mathematical algorithm that can predict the crystal structure of any material just based on knowledge of the atoms that make it up. They report this algorithm in a paper in Nature.
Developed by an interdisciplinary team of researchers from the University of Liverpool’s departments of chemistry and computer science, the algorithm systematically evaluates entire sets of possible structures at once, rather than considering them one at a time, to accelerate identification of the correct solution.
This breakthrough makes it possible to identify those materials that can be made and, in many cases, to predict their properties. The researchers demonstrated the algorithm on quantum computers that have the potential to solve many problems faster than classical computers and can therefore speed up the calculations even further.
New materials are needed to meet the challenge of net zero – from batteries and solar absorbers for clean power to low-energy computing to the catalysts that will make the clean polymers and chemicals for our sustainable future.
Up to now, this search has been slow and difficult because there are so many ways that atoms can be combined to make materials, and so many crystal structures that they could adopt. In addition, materials with transformative properties are likely to have structures that are different to those that are known today, and predicting a structure that nothing is known about is a tremendous scientific challenge.
“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,” said Matt Rosseinsky from the university’s Department of Chemistry and Materials Innovation Factory.
“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.”
“We managed to provide a general algorithm for crystal structure prediction that can be applied to a diversity of structures,” said Paul Spirakis from the university’s Department of Computer Science. “Coupling local minimization to integer programming allowed us to explore the unknown atomic positions in the continuous space using strong optimization methods in a discrete space.
“Our aim is to explore and use more algorithmic ideas in the nice adventure of discovering new and useful materials. Joining efforts of chemists and computer scientists was the key to this success.”
This story is adapted from material from the University of Liverpool, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier. Link to original source.