The lack of large-scale energy storage bottlenecks many sources of renewable energy, such as sunlight-reliant solar power and unpredictable wind power. Researchers from Lawrence Livermore National Laboratory (LLNL) are working on changing that, leveraging an allocation on Argonne National Laboratory’s Theta supercomputer to better understand the dynamics of ion transport that are at the core of batteries and other energy storage systems.
In essence, the issue is that simulations of energy-storing materials are too perfect: or rather, the materials they simulate are too perfect. The imperfections found in real-world materials are key for ion transport, but are not typically well-captured by simulations of those materials.
“We want to understand these boundary regions, so we threw lots of high-performance computing power at it,” explained Brandon Wood, deputy director of LLNL’s Laboratory for Energy Applications for the Future. The HPC power in question: Argonne’s Theta system, via an allocation from the Department of Energy’s INCITE program. Theta is an HPE system that delivers 6.92 Linpack petaflops, and it ranked 70th on the most recent Top500 list.
The researchers are using Theta to run ensemble simulations of a wide range of material imperfections. Wood said that Theta made it possible to look beyond individual problem formations and toward a “range of combinations to see the whole picture.” These atomistic simulations incorporated the minute dynamics of ion mobility, and the results of those ultra-precise simulations were then fed into a larger model to understand the interactions between different types of interfaces.
This multiscale approach, the researchers explained, was crucial to meaningful results. Using HPC to study the controlling variables, the researchers discovered that there were strong interdependencies between changes in atomic structure and the arrangements of interfaces, and that both variables—and the operating temperature of the material—had effects on ion transport.
“We need to understand how all of these different factors talk to each other, and there’s an additional layer of complexity because the relationship itself depends on operating conditions such as temperature or pressure,” Wood said. “This relationship between operating conditions, materials properties at the atomic scale, and materials properties at the mesoscale is the crux of what we’re trying to get at.”
The researcher team is interested in applying their learnings to improvements in solid-state batteries and hydrogen storage technologies.
“It’s giving guidance in not only ideally what I would want but also hints of how to make it,” Wood said. “If you change your chemical composition in a certain way and alter the processing temperature in another way, it will manifest as improved performance or an improved tradeoff between the different factors relevant in these materials.”
To learn more about this research, read the reporting in ASCR Discovery here.