A signal that seems to reveal lithium ions racing through a battery may, in fact, be nothing more than a topographical illusion. Researchers at the Korea Advanced Institute of Science and Technology (KAIST) have traced one of the most stubborn sources of error in nanoscale battery analysis to a surprisingly mundane cause: uneven surfaces. In doing so, they have exposed a systematic flaw that may run through years of published data on where and how ions move inside energy-storage materials, and they have offered a remarkably practical remedy—polish the sample flat before you measure it.
The study, led by Professor Seungbum Hong of KAIST’s Department of Materials Science and Engineering in collaboration with the research groups of Professor Jong Min Yuk from the same department and Professor Nam-Soon Choi from the Department of Chemical and Biomolecular Engineering, was published in the journal Small Methods. First author Dongyan Chen, a PhD student in materials science and engineering, quantified how surface topography alone can generate false signals in Electrochemical Strain Microscopy, a technique widely used to probe ion transport at the nanometer scale. The team also demonstrated that a sample-preparation method borrowed from electron microscopy—cooling cross-section polishing with an argon ion beam—can suppress the artifact almost entirely.
Electrochemical Strain Microscopy, or ESM, grows out of Atomic Force Microscopy, the workhorse of nanoscale surface characterization. In an AFM-based instrument, an exquisitely sharp tip mounted on a flexible cantilever is rastered across a material’s surface while a feedback loop keeps the force between tip and sample constant. ESM adds an electrical twist: an alternating voltage applied through the tip drives electrochemical processes—such as the insertion and extraction of lithium or sodium ions—in the tiny volume of material beneath it. Because moving ions cause the material to expand and contract ever so slightly, the resulting surface displacement, detected through the cantilever, serves as an indirect fingerprint of ion mobility. Researchers use these fingerprints to map, point by point, where ions move freely and where they get stuck, information that is central to designing batteries that charge quickly and last long.
The trouble begins when the surface being scanned is rough. The KAIST team showed, both theoretically and experimentally, that when the tip travels over height variations—hills, valleys, grain-boundary grooves—the feedback loop that is supposed to maintain constant contact cannot respond instantaneously. There is an inherent delay in the feedback circuitry, and during that delay the degree of contact between tip and sample changes. Those changes alter the contact stiffness, the mechanical rigidity of the tip–sample junction, and variations in contact stiffness produce cantilever responses that look strikingly similar to the strain signals generated by genuine ion motion. In the band-excitation variant of the technique known as DART-ESM, where dual AC resonance tracking is used to follow local contact resonances, the effect is particularly insidious because the resonance shifts caused by changing stiffness overlap with the resonance shifts caused by electrochemical strain.
To isolate the phenomenon, the researchers engineered an elegant control experiment. They fabricated fine trenches on the surface of an ionically inactive single-crystal silicon wafer—a system in which, by construction, no electrochemistry and no ion movement could occur, while the surface remained deliberately uneven. When they scanned this inert, corrugated surface with DART-ESM, they still obtained strong signals. The measurements quantitatively demonstrated that height variations alone, interacting with the finite feedback-loop delay, were enough to generate signals mimicking ion transport. In other words, the microscope can be made to “see” ion movement where none exists, simply because the tip rides up and down over bumps like a car bouncing along a bumpy road.
The next question was whether this laboratory curiosity mattered for real battery materials. It did. When the team examined a graphite anode—a mainstay of commercial lithium-ion batteries—and the sodium solid electrolyte Na₂Zn₂TeO₆, an increasingly relevant material for sodium-ion chemistry, the ESM signals again tracked surface topography rather than any intrinsic electrochemical property. This confirmed that the artifact is not confined to one material class or one crystal structure. It is a general phenomenon that anyone performing nanoscale electrical or electrochemical characterization on rough battery surfaces must confront, from silicon anodes to sulfide electrolytes to oxide cathodes.
The implications are most acute at grain boundaries—the interfaces where the microscopic crystalline grains within a material meet, much like the seams between adjacent tiles. Grain boundaries are scientifically fascinating because they can act either as fast conduits for ions or as barriers that impede them, and resolving which role they play is critical for engineering better solid electrolytes and electrodes. Yet the KAIST team found that before surface smoothing, strong ESM signals appeared precisely at grain boundaries, seemingly flagging them as highways for ion transport. After the samples were polished flat, those enhanced signals vanished. That result raises an uncomfortable possibility: some published reports of “enhanced ion transport at grain boundaries” may instead have documented nothing more than height contrast at surface grooves, with the signal generated mechanically by the feedback delay rather than electrochemically by mobile ions.
The remedy the researchers propose is as straightforward as it is effective: make the surface as smooth and flat as possible before measuring. They achieved this with a cooling cross-section polisher, or CCP, a device that fires a beam of argon ions at the sample to shave away material with nanometer-level precision. Argon is chemically inert under most conditions, which means the beam sculpts the surface without chemically altering the delicate battery material beneath—no oxidation, no contamination, no change to the very properties the researchers want to measure. The cryogenic cooling stage protects thermally sensitive samples, such as polymer-containing electrolytes, from beam-induced heating. After CCP treatment, surface roughness dropped substantially, and with it the topography-induced artifacts, allowing genuine electrochemical strain signals to stand out cleanly.
The significance of the work extends well beyond a single instrument or technique. Solid-state batteries, which replace flammable liquid electrolytes with ceramics or polymers, and sodium-ion batteries, which substitute abundant sodium for increasingly contested lithium, are the two most prominent candidates for next-generation energy storage. Both depend critically on understanding ionic transport through heterogeneous microstructures full of grains, boundaries, and phase interfaces—exactly the environments where topographic artifacts are most likely to masquerade as science. By establishing a rigorous protocol that separates real ion transport from mechanical crosstalk, the KAIST team has given researchers in these fields a tool for producing trustworthy maps of ionic conductivity at the nanoscale.
There is also a data-quality dimension that reaches into the era of artificial intelligence. Machine-learning models for predicting battery performance and screening new materials are only as good as the training data they consume, and those data increasingly come from nanoscale characterization experiments. If a meaningful fraction of archived ESM measurements is contaminated by topographic artifacts, models trained on them will learn phantom correlations between surface features and ionic behavior. The accumulation of artifact-free, reproducible nanoscale datasets—of the kind this polishing protocol makes possible—could therefore feed directly into higher-quality AI-driven materials discovery, accelerating the search for electrolytes and electrodes that enable faster charging and longer lifetimes.
Professor Hong emphasized the broader lesson for the microscopy community. “This research clearly demonstrates how variations in surface height affect the results of nanoscale battery-material analysis,” he said. “We expect our findings to enable more accurate tracking of ion movement within batteries and contribute to understanding the operating mechanisms of next-generation battery materials and designing improved materials.” The phrasing is deliberately cautious where it matters: the team is not claiming that all ESM data are wrong, but that height crosstalk is a quantifiable, predictable, and removable confound—and that measurements made without controlling for it should be interpreted with care.
The study’s quantitative character is what sets it apart from earlier anecdotal warnings. By measuring the trace–retrace discrepancy—the mismatch between signals recorded as the tip scans in opposite directions over the same feature—the team connected the magnitude of the artifact to specific instrument parameters, including the feedback-loop delay and local contact stiffness. Because these parameters are known and controllable, researchers can now estimate how much of a given ESM signal might be topographic in origin, and design experiments that either suppress the artifact or explicitly model it out. That transforms the problem from a vague caveat into a solvable engineering challenge.
The work was supported by National Research Foundation of Korea grants funded by the Korean government’s Ministry of Science and ICT. For a field racing to deliver solid-state packs and fast-charging sodium cells, the message from Daejeon is refreshingly concrete: before you trust a nanoscale map of where ions flow, make sure the road itself is not producing the motion. A flat surface, an inert argon beam, and an honest accounting of feedback delay may be all that separates a genuine discovery in ion transport from a very convincing mirage.
News Publication Date: 6-Sep-2026
Web References: Not provided
References: Chen, D., Hong, S., Yuk, J. M., & Choi, N.-S. Quantitative Analysis of Topographic Crosstalk in DART-ESM Arising from Feedback-Loop-Delay-Induced Contact Stiffness Variations in Battery Materials. Small Methods. https://doi.org/10.1002/smtd.70763
Keywords
Electrochemical Strain Microscopy, Atomic Force Microscopy, battery nanoscale analysis, ion transport, topographic artifacts, grain boundaries, solid-state batteries, sodium-ion batteries, contact stiffness, feedback-loop delay, argon ion polishing, KAIST
Subject of Research: Identification and reduction of topography-induced measurement artifacts in nanoscale battery analysis using Electrochemical Strain Microscopy (DART-ESM)
Subject of Research: Technology and Engineering
Article Title: Quantitative Analysis of Topographic Crosstalk in DART-ESM Arising from Feedback-Loop-Delay-Induced Contact Stiffness Variations in Battery Materials
Article References: Chen, D., Lee, J., Song, C., Han, S. H., Choi, Y., Gong, C., Saha, A., Choi, N.-S., Yuk, J. M., & Hong, S. (2026). Quantitative Analysis of Topographic Crosstalk in DART‐ESM Arising from Feedback‐Loop‐Delay‐Induced Contact Stiffness Variations in Battery Materials. Small Methods, 10(13), Article e70763. https://doi.org/10.1002/smtd.70763
Image Credits: AI Generated
DOI: 10.1002/smtd.70763
Keywords: argon ion beam polishing for battery sample preparation, battery nanoscale measurement errors, electrochemical strain microscopy artifact correction, impact of surface irregularities on energy storage material studies, improving reliability of nanoscale battery analysis techniques, influence of surface roughness on battery measurement accuracy, ion transport imaging in energy storage materials, polishing techniques for accurate battery analysis, sample preparation methods for nanoscale battery characterization, surface topography effects in electrochemical analysis, systematic flaws in battery nanoscale research, troubleshooting unreliable battery ion transport data
Cite Scienmag News
APA
MLA
Chicago
Faith Mcneil. (September 7, 2026). KAIST pinpoints artifacts behind unreliable battery nanoscale analysis measurements. Scienmag. https://scienmag.com/kaist-pinpoints-artifacts-behind-unreliable-battery-nanoscale-analysis-measurements/
Faith Mcneil. “KAIST pinpoints artifacts behind unreliable battery nanoscale analysis measurements.” Scienmag, 7 September 2026, https://scienmag.com/kaist-pinpoints-artifacts-behind-unreliable-battery-nanoscale-analysis-measurements/. Accessed 7 September 2026.
Faith Mcneil. “KAIST pinpoints artifacts behind unreliable battery nanoscale analysis measurements.” Scienmag. September 7, 2026. https://scienmag.com/kaist-pinpoints-artifacts-behind-unreliable-battery-nanoscale-analysis-measurements/
Copy citation
Download RIS
Tags: advancements in nanometrology for batteriesargon ion beam polishing for battery sample preparationbattery nanoscale analysis artifactsbattery nanoscale measurement errorschallenges in analyzing ion movement within batteriescorrecting artifacts in energy-storage material characterizationelectrochemical strain microscopy artifact correctionelectrochemical strain microscopy error sourcesimpact of surface irregularities on energy storage material studiesimpact of surface topography on battery measurement accuracyimproving reliability of nanoscale battery analysis techniquesinfluence of surface roughness on battery measurement accuracyinfluence of uneven surfaces on lithium ion imagingion transport imaging in energy storage materialsmethodological improvements in battery nanoscale imagingpolishing methods to improve measurement reliabilitypolishing techniques for accurate battery analysisreliability of nanoscale battery diagnosticssample preparation methods for nanoscale battery characterizationsample preparation techniques for nanoscale battery analysissurface topography effects in electrochemical analysissystematic flaws in battery nanoscale researchsystematic flaws in ion transport datatroubleshooting unreliable battery ion transport data
