Atomic force microscopy (AFM) has become a valuable tool in battery research, offering nanoscale resolution for investigating electrode surfaces, solid-electrolyte interphases (SEI), and material degradation. However, its application in this field is not without significant challenges and limitations. While AFM provides unique insights into topography, mechanical properties, and electrical characteristics, researchers must contend with artifacts, speed constraints, tip wear, and sample preparation complexities that can compromise data reliability. Furthermore, AFM is often complemented by other techniques that overcome some of its inherent drawbacks, though each method has its own trade-offs.

One of the most persistent challenges in AFM for battery research is the introduction of artifacts. These distortions arise from multiple sources, including tip-sample interactions, feedback loop errors, and environmental noise. In contact mode, excessive force can deform soft materials like polymer binders or SEI layers, leading to misleading height profiles. Tapping mode reduces this risk but may still produce artifacts due to adhesion forces or improper oscillation damping. Electrochemical AFM, used to study battery materials under operating conditions, faces additional complications from electrical interference and electrolyte interactions. For example, parasitic currents can distort both topography and current measurements, while meniscus forces in liquid environments may cause false adhesion readings. These artifacts necessitate careful calibration and validation, often requiring cross-verification with other techniques.

Scan speed is another critical limitation. AFM imaging is inherently slow compared to electron microscopy or optical profilometry, with typical scan times ranging from minutes to hours for a single high-resolution image. This becomes problematic when studying dynamic processes such as SEI formation, dendrite growth, or phase transitions during cycling. While high-speed AFM variants exist, they often sacrifice resolution or are limited to small scan areas. The slow acquisition rate also hinders statistical analysis, as obtaining a representative dataset across multiple sample locations is time-consuming. In contrast, techniques like scanning electron microscopy (SEM) can rapidly survey large areas, though they lack AFM’s ability to measure mechanical properties or operate in liquid environments.

Tip wear is an unavoidable issue that degrades data quality over time. Battery materials, particularly hard cathode particles like lithium nickel manganese cobalt oxide (NMC) or lithium iron phosphate (LFP), accelerate tip blunting. A worn tip produces broader features, reducing lateral resolution and distorting roughness measurements. Conductive AFM probes, essential for mapping local conductivity or electrochemical activity, are especially prone to wear due to their fragile coatings. Repeated scans in corrosive electrolytes further exacerbate this problem, leading to inconsistent results. Researchers must frequently replace tips, increasing costs and interrupting experiments. Some studies report tip lifetimes as short as a few hours when imaging abrasive battery materials, emphasizing the need for robust probe designs or alternative characterization methods where possible.

Sample preparation presents additional hurdles. AFM requires relatively flat surfaces to avoid tip crashes or false topography readings, yet battery electrodes are inherently rough due to particle agglomerates and porous structures. Mechanical polishing can smooth surfaces but risks altering material properties or introducing contaminants. Cross-sectional analysis of electrode stacks is even more challenging, as delamination or smearing during cutting can obscure true interfacial morphology. In situ studies, where AFM monitors electrochemical processes in real time, demand specialized cells that accommodate the probe while maintaining proper electrochemical conditions. These constraints limit the applicability of AFM for certain battery research questions, particularly those involving thick or irregularly shaped samples.

When compared to complementary techniques, AFM’s strengths and weaknesses become clearer. SEM provides higher throughput and superior depth of field but cannot measure mechanical properties or operate easily in liquid. Transmission electron microscopy (TEM) offers atomic resolution but requires ultrathin samples and high vacuum conditions, making it unsuitable for in situ studies of bulk electrodes. X-ray diffraction (XRD) excels at crystallographic analysis but lacks spatial resolution for heterogeneous materials. Scanning electrochemical microscopy (SECM) probes local reactivity but does not provide topographical data. Thus, AFM occupies a niche where nanoscale surface properties and mechanical behavior are paramount, though its limitations often necessitate a multimodal approach.

Despite these challenges, AFM remains indispensable for certain battery research applications. Its ability to map modulus variations, detect dendrite formation, or quantify SEI evolution provides insights that other techniques cannot match. However, researchers must carefully design experiments to mitigate artifacts, account for tip wear, and validate findings with complementary methods. Future advancements in probe technology, faster scanning modes, and improved environmental control may alleviate some current limitations, but for now, AFM’s role in battery research is both powerful and constrained.

In summary, while AFM offers unparalleled capabilities in nanoscale characterization of battery materials, its practical use is hampered by artifacts, slow imaging speeds, tip degradation, and stringent sample requirements. These limitations underscore the importance of combining AFM with other analytical techniques to obtain a comprehensive understanding of battery systems. As battery technologies evolve toward more complex materials and architectures, overcoming these challenges will be critical for leveraging AFM’s full potential in advancing energy storage research.