Critical minerals: Harnessing AI to improve discovery and supply

A new initiative to use artificial intelligence (AI) in the discovery, development and delivery of critical minerals has been established by the US Department of Energy (DoE). The Critical Minerals and Materials to Unlock Supply (CM²US) initiative is being led by the 12 US DoE national laboratories with support from private sector partners. The initiative intends to accelerate breakthroughs across the entire critical minerals supply chain from mining to manufacturing.

The DoE says that the CM²US initiative is based on an AI-driven engine that serves as a strategic guide for the entire critical materials supply chain. The system generates a dynamic digital map of the process – from mining to market – pinpointing the most promising opportunities.

“By integrating advanced data platforms and machine learning with deep scientific expertise, the initiative enables smarter, faster decision-making and helps validate promising technologies early in development,” the DoE said.

'Within CM2US we can collect that data at unprecedented speed and consistency, running hundreds of experiments in days instead of years and enabling truly predictive, AI-guided discovery and process optimization,” said Ihor Hlova, a scientist at Ames Lab and its Critical Materials Innovation (CMI) Hub and co-lead for the project.

The DoE said the Ames National Laboratory and the CMI Hub’s leadership directly supports its mission to advance energy security and economic resilience by ensuring reliable access to the material needed for energy technologies, national defence systems and high-tech manufacturing. Tom Lograsso, Director CMI Hub said: “Accelerating the pathway from laboratory to market has always been part of the CMI’s mission. AI is essential for accelerating discovery.”

The CM²US project is part of the DoE’s Genesis Mission, an initiative established last year to use AI and advanced computing to revolutionise US science and innovation.

Ames National Laboratory and the CMI Hub, at Iowa State University are also leading efforts to reduce supply chain vulnerabilities through innovation in recovery, substitution, and efficient processing of critical minerals. Here, researchers are looking at unconventional sources of critical minerals such as mine tailings and wastewater and developing new biological approaches to recover these materials.

Rare earth elements and critical minerals have a key role to play in the energy transition and are vital for electronics, and finding new sources for these materials has intensified as concerns over access to conventional supplies have increased.

The Ames research team says that it will combine synthetic biology, machine learning, automated laboratory systems, and molecular modelling to create an advanced platform for capturing valuable minerals from unconventional sources.

Starting with cobalt, the team will adapt naturally occurring systems to help capture and store this critical mineral. Using the automated platform, AI will identify and design a range of peptides and then select which of these can bind to cobalt and other critical minerals. This process will quickly allow the researchers to precisely develop selective binding systems.

Peng Xu, assistant professor at Ames Laboratory and lead principal investigator for the project said: “Nature already has ways of capturing metal efficiently. Our approach takes this biological process to the next level by using specialised cellular components that act as intracellular metal depositories in certain bacteria.”

The researchers say that with a working system in place, it will be possible to leverage automation and AI to scale up the process for broader application. This could lead to a method that is less costly than traditional routes for extraction of critical minerals.

Describing the project as “a highly interdisciplinary effort,” Xu added “This is truly a project that requires theory, AI and experimentation across chemistry and biology.”

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