The Atomic Blueprint: How a New Algorithm Opened the Door to Sustainable Technologies in Materials

Garnet’s atomic structure is analogous to the crater on the potential energy surface, which features rugged mountains, hills, and valleys. Finding the lowest lying vertex computationally is challenging, however it is possible to employ advanced algorithms and quantum computers to do it by anchoring a mesh on this surface. After a few adjustments, the optimum garnet structure is revealed. Gratitude: Liverpool University

Researchers at the University of Liverpool have created a mathematical formula that could mark a turning point in the search for new materials to address the challenge of net zero and a sustainable future.

A breakthrough in the attempt to create the novel materials required to tackle the challenge of net zero and a sustainable future may have been signaled by recent research from the University of Liverpool.

The Liverpool team published its findings in Nature, demonstrating that a mathematical program can reliably predict the structure of any substance given only knowledge of its constituent atoms.

The algorithm, which was developed by a group of researchers from the University of Liverpool’s Departments of Chemistry and Computer Science, takes a batch approach to evaluating potential structures rather than looking at each one individually to speed up the process of zeroing in on the best option.

This development allows us to determine which materials are fabricatable and, in many circumstances, to foretell their qualities. Quantum computers, which have the potential to answer many problems quicker than classical computers, were used to show the new method, which can speed up the calculations even further.

That “everything is made of something” is a truism that underpins our entire way of existence. From batteries and solar absorbers for clean power to low-energy computers and the catalysts that will manufacture the clean polymers and chemicals for our sustainable future, new materials are needed to tackle the challenge of net zero.

Because there are an infinite number of possible atomic combinations and, by extension, structures that can form, this search is time-consuming and labor-intensive. The prediction of a structure about which nothing is known is a formidable scientific problem, because materials with transformative qualities are likely to have structures that are different from those that are known today.

Professor Matt Rosseinsky of 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.”

To quote from the paper: “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.”

Department of Computer Science professor Paul Spirakis at the University of stated, “We managed to provide a general algorithm for crystal structure prediction that can be applied to a diversity of structures.” We were able to use powerful optimization techniques in a discrete space to probe the unknown atomic positions in a continuous space by coupling local minimization with integer programming.

In the pleasant experience of uncovering new and valuable things, we hope to investigate and employ additional algorithmic approaches. The key to this breakthrough was the collaboration between chemists and computer scientists.