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Imaging mechanisms in contact Kelvin Probe Force Microscopy (cKPFM) areexplored via information theory-based methods. Gaussian Processes are used toachieve super-resolution in the cKPFM signal, effectively extrapolating acrossthe spatial and parameter space. Tensor matrix factorization is applied toreduce the multidimensional signal to the tensor convolution of the scalarfunctions that show clear trending behavior with the imaging parameters. Thesemethods establish a workflow for the analysis of the multidimensional datasets, that can then be related to the relevant physical mechanisms. We alsoprovide an interactive Google Colab notebook (http://bit.ly/39kMtuR) that goesthrough all the analysis discussed in the paper.

Super-resolution and signal separation in contact Kelvin probe force microscopy of electrochemically active ferroelectric materials