Reactive alkali metals such as lithium and sodium are increasingly important to battery development. Their sensitivity to air, moisture, and electron beams makes them difficult to characterize without altering the structures researchers are trying to study.
Dr. Zhao Liu, Senior Market Development Manager at Thermo Fisher Scientific.
That challenge is particularly important when examining the solid electrolyte interphase (SEI), a thin layer that forms between the electrode and electrolyte and plays a significant role in battery performance and degradation. Damage introduced during sample preparation, transfer, or imaging can distort results and make it difficult to determine the material’s native structure.
To discuss the findings and the new characterization guidelines developed by a University of Chicago research team led by Professor Ying Shirley Meng, we spoke with Dr. Zhao Liu, senior market development manager at Thermo Fisher Scientific.
In this Q&A, Liu explains the challenges of imaging reactive battery materials, how correlative imaging can connect nanoscale behavior with cell-level performance, and why consistent characterization methods matter for reproducibility across research labs.
Here’s what he has to say…
Why are reactive alkali metal battery materials difficult to characterize using conventional imaging and analysis methods?
Electron microscopy is a primary technique in battery research due to its ability to resolve the nanoscale features that influence battery behavior. Researchers rely on it to direct a focused electron beam through or onto a sample to characterize structures at the atomic level. With reactive materials like lithium and sodium, however, the same beam can change the features it’s meant to measure. The sensitivity of the materials makes it important to ensure the beams are under careful control to deliver trustworthy results.
Alkali metals are extremely reactive on two fronts: to the environment, meaning air and moisture, and to the electron or ion beam used during characterization within the electron microscope. The sensitivity makes it challenging to preserve the material’s native state during characterization. Scientists look to measure materials in their native state because any damage introduced during handling or imaging replaces the true material with an artifact, and conclusions drawn from that artifact cannot be trusted to guide real battery development.
Beyond the material’s sensitivity, different teams are characterizing the materials in different ways, making it difficult to study, compare results, and land on new industry findings.
The electric vehicle (EV) industry relies on these materials because lithium-metal anodes are one of the leading paths to the energy densities that extend vehicle range beyond what graphite-based cells can deliver. Additionally, sodium chemistries are emerging as a lower-cost option for entry-level EVs. However, neither can be reliably engineered if we cannot characterize them accurately and in a standardized way.
An inert gas sample transfer holder helps protect sensitive samples during transfer to an electron microscope for characterization. (Image: UChicago Pritzker School of Molecular Engineering / John Zich)
What problem were the new correlative imaging and analysis guidelines designed to solve for battery researchers?
The correlative imaging and analysis guidelines provide a repeatable and reliable workflow that enables native state nanoscale characterization of alkali metals and solid electrolyte interphase (SEI), which is a thin layer of organic and inorganic composite that forms at the connection between the electrode and electrolyte within a battery.
The guidelines span the full chain of custody: sample storage, preparation, transfer, imaging, and analysis, because damage can occur at any of those steps. For EV battery programs, this guideline matters because failure analysis of cycled cells is only as good as the sample handling behind it.
Even if a careful technique is used, reactive alkali metal samples are sensitive to brief air or moisture exposure during transfer. This can alter lithium’s structure as quickly as 15 seconds. Additionally, exposure from the electron beam during imaging can change compounds into entirely new materials. Researchers risk unknowingly imaging and interpreting artifacts of their own measurement process versus the material’s true, native structure, which highlights why standardized, damage-minimized workflows are needed to transfer, store, and image these materials.
To build these new guidelines, the research team at the University of Chicago, led by Professor Ying Shirley Meng, Energy Storage Research Alliance (ESRA) Director and professor in molecular engineering at the Pritzker School of Molecular Engineering, prepared multiple identical samples of the most significant lithium and sodium-based inorganic compounds used in battery work, changing only the transfer and imaging conditions. This made it possible to isolate exactly where damage originated and overturned a longstanding assumption in the field, which is that pure lithium metal does not require cryogenic temperatures to withstand the electron beam during transmission electron microscopy (TEM) imaging.
With the inert gas transfer method, it’s now possible to secure high-resolution images of pure lithium metal at room temperature.
It’s the beam-sensitive SEI that forms on electrochemically deposited lithium that demands cryo-protection rather than the metal itself. This distinction changes how labs design their experiments.
Pure lithium can be inspected at room temperature, so engineers evaluating lithium-metal cells for EVs can reserve cryogenic sample preparation and transfer for the samples that genuinely need it.
How does correlative imaging help connect atomic-scale material behavior with cell-level battery performance?
Correlative imaging enables a comprehensive understanding of battery microstructure at multiple length scales, which is needed to understand the structure-performance relationship of a battery.
EV engineers work with cell-level metrics to determine vehicle range, charging behavior, and warranty exposure. Each of these cell-level metrics, from capacity retention to fast-charge tolerance, has a root cause at the nanoscale, including how the SEI evolves, how lithium plates and strips, or how an interphase fractures under mechanical and thermal stress.
No single technique covers the entire range, but by correlating observations across scales, from atomic-resolution TEM through the electrode and cell level, we can trace a performance outcome back to a specific structural origin. This only works if every image in the chain can be validated, so if the nanoscale data is corrupted by transfer contamination or beam damage, the correlation points to the wrong mechanism, and the whole chain of inference breaks.
What are the main sources of error or inconsistency when analyzing reactive battery materials, and how can standardized workflows reduce them?
The main sources of error are contamination from inappropriate sample transfer and artifacts generated during imaging. On the transfer side, we compared common transfer methods to one another. Cryo-transfer thermally preserves the sample, but frozen water inevitably condenses during the transfer between the glovebox, holder, and the microscope.
Think of this like beads of moisture forming on a cold glass in summer, and that water attacks lithium and sodium. Glovebag transfer with a cooling holder still adds unavoidable air exposure when inserting a sample. By standardizing the workflows, we can reduce any errors in sample transfer because researchers will be able to validate results across labs.
Why is atomic-resolution imaging important for understanding degradation, and how could better characterization accelerate alkali-metal battery development?
In a battery, one of the most critical layers is the SEI because its properties determine the battery’s electrochemical cycling performance. This shapes the important commercial outcomes, including how far a vehicle can travel on a charge, how long the battery will last, how fast it can safely charge, and how it behaves under stress. Accurately understanding this layer is vital to advancing battery technology as a whole.
If scientists cannot work on accurate information related to the structure and properties within battery materials at the nanoscale, then characterization will not provide accurate guidance for development.
Teams end up engineering electrolytes and interfaces against a picture of the SEI that was partly an imaging artifact. With damage-minimized, reproducible characterization, researchers can see the SEI as it exists within the cell and identify which structural features correlate with stable cycling. This allows them to deliberately design toward these structural features, tightening the design-test-learn loop for alkali-metal chemistries and shortening the path from lab results to a cell that can be validated.
A transmission electron microscope sample grid prepared with lithium fluoride powder for nanoscale characterization. (Image: UChicago Pritzker School of Molecular Engineering / John Zich)
What practical challenges do laboratories face when handling and imaging air or moisture-sensitive battery materials?
Since there’s been no standard framework, different laboratories have used different ways to handle and image the same battery materials, which can lead to different results. When that happens, the learning cannot be fully applied across the field, or worse, it can steer development in the wrong direction entirely. In an industry where cell programs run on multi-year automotive timelines, a misstep at the characterization stage is costly to unwind.
The practical constraints compound the problem across the EV research pipeline. Removing a sample from the protective environment of a glovebox, even briefly, risks contaminating it. Many smaller labs do not have advanced electron microscopy equipment in-house, so they prepare samples and ship them elsewhere for characterization, which multiplies the opportunities for exposure along the way. When combined with the differences in equipment, holders, and operator preferences for beam conditions, the field ends up with widely differing results that are difficult to compare and, in some cases, difficult to trust when making engineering decisions.
What would broader adoption of standardized imaging workflows mean for reproducibility across battery research labs?
If standardized workflows are adopted across the industry, the learning generated in different labs can be shared and built on. Today, a result from one lab often cannot be reproduced or even meaningfully compared in another, because the transfer method, beam dose, and reporting conventions all differ. A common framework means that results would be directly comparable across labs.
That matters more as the field moves toward next-generation chemistries such as sodium-ion, which are becoming more prominent in cost-sensitive EV segments. Establishing shared workflows and disclosure standards now, before those chemistries mature, means the foundational data underpinning their development will be consistent and reliable from the start, which is ultimately the goal of the research conducted by the team at the University of Chicago.
Filed Under: Batteries, Featured Contributions, Q&As