The novel collaborative AI tool is designed to accelerate materials discovery. Image: University of Liverpool.
The novel collaborative AI tool is designed to accelerate materials discovery. Image: University of Liverpool.

Researchers at the University of Liverpool in the UK have created a collaborative artificial intelligence (AI) tool that reduces the time and effort required to discover truly new materials.

As the researchers report in a paper in Nature Communications, this new tool has already led to the discovery of four new materials, including a new family of solid-state materials that conduct lithium. Such solid electrolytes will be key to the development of solid-state batteries that offer longer range and increased safety for electric vehicles. Further promising materials are also in development.

The tool brings together AI with human knowledge to prioritize those parts of unexplored chemical space where new functional materials are most likely to be found.

Discovering new functional materials is a high-risk, complex and often arduous journey, as an infinite space of possible materials is accessible by combining all of the elements in the periodic table, and it is not known where new materials exist. The new AI tool was developed by a team of researchers at the University of Liverpool’s Department of Chemistry and Materials Innovation Factory, led by Matt Rosseinsky, to address this challenge.

The tool examines the relationships between known materials at a scale unachievable by humans. These relationships are used to identify and numerically rank combinations of elements that are likely to form new materials. The rankings are then used by scientists to guide exploration of the large unknown chemical space in a targeted way, making experimental investigation far more efficient. These scientists make the final decisions, informed by the different perspective offered by the AI tool.

“To date, a common and powerful approach has been to design new materials by close analogy with existing ones, but this often leads to materials that are similar to ones we already have,” said Rosseinsky.

“We therefore need new tools that reduce the time and effort required to discover truly new materials, such as the one developed here that combines artificial intelligence and human intelligence to get the best of both.

“This collaborative approach combines the ability of computers to look at the relationships between several hundred thousand known materials, a scale unattainable for humans, and the expert knowledge and critical thinking of human researchers that leads to creative advances.

“This tool is an example of one of many collaborative artificial intelligence approaches likely to benefit scientists in the future.”

Society’s capacity to solve global challenges such as energy and sustainability is constrained by our capability to design and make materials with targeted functions. Examples include better solar absorbers for making better solar panels and superior battery materials for making longer-range electric cars, or replacing existing materials by using less toxic or scarce elements.

Such new materials can create societal benefit by driving new technologies to tackle global challenges, and they also reveal new scientific phenomena and understanding. All modern portable electronics rely on the materials in lithium-ion batteries, which were developed in the 1980s. This emphasises how just one material class can transform how we live – defining accelerated routes to new materials will open currently unimaginable technological possibilities for our future.

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.