Sandia test method paves the way for better, longer-lasting solid-state batteries

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Using a microscopic method of measuring electrical potential, a team of scientists from Sandia National Laboratories could have discovered how to identify flow limiting processes in solid-state batteries. The results are detailed in an article by American Chemical Society Energy Letters.

The performances of electrochemical systems in the solid state are intimately linked to the distributions of potential and lithium across the electrolyte-electrode junctions which give rise to the interface impedance. Here, we combine two operand methods, Kelvin Probe Force Microscopy (KPFM) and Neutron Depth Profiling (NDP), to identify the limiting interface in the functioning of Si-LiPON-LiCoO.2 solid state batteries by mapping the contact potential difference (CPD) and the corresponding Li distributions.

The contributions of ions, electrons and interfaces are deconvolved by correlating the CPD profiles with the Li concentration profiles and by comparisons with first-principles modeling. We find that the greatest drop in potential and change in Li concentration occurs at the anode-electrolyte interface, with a smaller drop at the cathode-electrolyte interface and a shallow gradient in the bulk electrolyte. . Correlation of these results with electrochemical impedance spectroscopy after battery cycling at low and high speeds confirms a long-held conjecture linking large drops in potential to a rate-limiting interfacial process.

—More full et al.

This illustration shows how a team from Sandia National Laboratories used Kelvin probe force microscopy to pinpoint areas where electron flow becomes blocked, potentially leading to the design of more durable and efficient batteries. (Illustration courtesy of S. Kelley / National Institute of Standards and Technology.)


Solid-state batteries use solid electrolytes instead of electrochemical gels and liquids, and typically power small electronic devices. Most researchers suspected that there was a loss of voltage or electrical potential at the battery interfaces, but not which interface was responsible for most of the impedance in the battery. The team started working five years ago to get some clarity.

There were two main motivations for this. The first was fundamental: we want to have good battery models that we can use to develop better materials. The second thing was to figure out how we can design the interfaces to make them less annoying. In our case, it really has to do with the speed at which lithium ions can move through the Si anode used in the study.

—Alec Talin, co-corresponding author

The team found that much of the battery’s electrical potential was lost at the boundary between the electrolyte and the anode terminal (negative).

To validate the data by measuring where lithium ions were in different states during charge, the team worked with researchers at the National Institute of Standards and Technology Center for Neutron Research using a technique called neutron depth profiling which can measure where lithium ions are at a particular time.

We will use this technique to study other batteries as well as other solid-state electrical systems, such as electrochemical random access memory invented at Sandia. This will allow us to develop devices that work the way we would like them to work.

—Alec Talin

The work was done in conjunction with NIST, Naval Research Labs, University of Maryland College Park, and Brown University. It was sponsored by Sandia’s Laboratory Directed Research and Development Lithium Battery Grand Challenge and the Nanostructures for Electrical Energy Storage Energy Frontiers Research Center as well as the Platforms Core Program, both led by the University of Maryland and sponsored by the DOE Office of Basic Energy Sciences. .

Resources

  • Elliot J. Fuller, Evgheni Strelcov, Jamie L. Weaver, Michael W. Swift, Joshua D. Sugar, Andrei Kolmakov, Nikolai Zhitenev, Jabez J. McClelland, Yue Qi, Joseph A. Dura and A. Alec Talin (2021) ” Spatially-resolved potential distributions and Li-Ion distributions reveal regions limiting performance in solid-state batteries ” ACS Energy Letters 6 (11), 3944-3951 doi: 10.1021 / acsenergylett.1c01960

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