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Dynamic strain based atomic force microscopy (AFM) modes often fail at the interfaces where the most interesting physics occurs because of their incapability of tracking contact resonance accurately under rough topography. To overcome this difficulty, we develop a high-throughput sequential excitation AFM that captures contact dynamics of probe–sample interactions with high fidelity and efficiency, acquiring the spectrum of data on each pixel over a range of frequencies that are excited in a sequential manner. Using electrochemically active granular ceria as an example, we map both linear and quadratic electrochemical strain accurately across grain boundaries with high spatial resolution where the conventional approach fails. The enhanced electrochemical responses point to the accumulation of small polarons in the space charge region at the grain boundaries, thought to be responsible for the enhanced electronic conductivity in nanocrystalline ceria. The spectrum of data can be processed very efficiently by physics-informed principal component analysis (PCA), speeding data processing by several orders of magnitude. This approach can be applied to a variety of AFM modes for studying a wide range of materials and structures on the nanoscale. 

Dense thin films of the solid oxide fuel cell cathode material La 0.6 Sr 0.4 CoO 3-δ were studied by operando X-ray absorption spectroscopy under sinusoidal voltage perturbations. This approach showed good agreement with previous steady-state μ-XAS measurements, but with high effective p (O 2) resolution over several orders of magnitude. Co oxidation state varied strongest under a 0.5 Hz perturbation suggesting, in agreement with linear impedance, that oxygen exchange kinetics are most active at this timescale. Furthermore, the local structure around Co atoms response varied at different timescales; however, interpretation was limited with only preliminary analysis. Altogether, this approach was shown as a successful step towards developing a technique sensitive to local chemical state that can also separate processes by timescale.