The Opportunity

New battery materials are constantly being invented, but there are still challenges in producing them at a large scale and at high quality.

Through the power of artificial intelligence (AI) and advanced simulation, scientists can dramatically accelerate translating these materials from benchtop to large-scale manufacturing and in the process provide a way to generate higher-performance materials at scale.

Argonne researchers are currently using AI to optimize nanomaterials produced from flame-spray pyrolysis (FSP) in a minimum number of trials.

Argonne scientists are simultaneously building a comprehensive simulation of FSP to reveal the physics and inform the AI model. An advanced suite of diagnostics available at the FSP facility will provide validation data for the simulations.

What Argonne Offers

Argonne offers a wealth of battery expertise that ranges from the most fundamental materials science and chemistry to applied scale-up processing. Argonne is home to the Joint Center for Energy Storage Research (JCESR) and the Argonne Collaborative Center for Energy Storage Science (ACCESS), which seek to pioneer new energy storage
technologies in partnership with other laboratories, academia, and industry.

Argonne’s suite of state-of-the-art user facilities and battery research facilities make the laboratory uniquely positioned to contribute to novel solutions for energy storage technology.

The Argonne Leadership Computing Facility (ALCF) has AI-specific hardware and high-speed intranet connecting to experimental apparatuses.

The Materials Engineering Research Facility (MERF) allows for process R&D and scale-up of new materials and validation of emerging manufacturing processes.

By leveraging the power of the ALCF, the MERF, and Argonne’s AI expertise, Argonne scientists and engineers can accelerate the time it takes to go from candidate battery material to large-scale manufacturing.

The Benefits

Argonne’s work in flame-spray pyrolysis offers a number of benefits, especially to industry:

• Shorter development timescales for new materials and new processes
• Lower cost
• Enhanced material performance within the same supply chain
• Practical demonstration of the use of AI and simulation in science and technology
• Enhanced general battery manufacturing capabilities