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

Abstract

Imaging mechanisms in contact Kelvin Probe Force Microscopy (cKPFM) are explored via information theory-based methods. Gaussian Processes are used to achieve super-resolution in the cKPFM signal, effectively extrapolating across the spatial and parameter space. Tensor matrix factorization is applied to reduce the multidimensional signal to the tensor convolution of the scalar functions that show clear trending behavior with the imaging parameters. These methods establish a workflow for the analysis of the multidimensional data sets, that can then be related to the relevant physical mechanisms. We also provide an interactive Google Colab notebook (http://bit.ly/39kMtuR) that goes through all the analysis discussed in the paper.

Update with accepted version

References in corpus (9)

• Dual-Frequency Resonance-Tracking Atomic Force Microscopy
• The Band Excitation Method in Scanning Probe Microscopy for Rapid Mapping of Energy Dissipation on the Nanoscale
• Ferroelectric domains in methylammonium lead iodide perovskite thin-films
• Local probing of ionic diffusion by electrochemical strain microscopy: spatial resolution and signal formation mechanisms
• Thermodynamics of Electromechanically-Coupled Mixed Ionic-Electronic Conductors: Deformation potential, Vegard strains and Flexoelectric effect
• Equilibrium and Stability of Polarization in Ultrathin Ferroelectric Films with Ionic Surface Compensation
• Electromechanical Probing of Ionic Currents in Energy Storage Materials
• Landau-Ginzburg-Devonshire theory for electromechanical hysteresis loop formation in piezoresponse force microscopy of thin films
• To switch or not to switch -- a machine learning approach for ferroelectricity

Cited by in corpus (1)

• Sub-10 nm Probing of Ferroelectricity in Heterogeneous Materials by Machine Learning Enabled Contact Kelvin Probe Force Microscopy