# Imaging Ferroelectric Domains via Charge Gradient Microscopy Enhanced by Principal Component Analysis

## TL;DR

This paper demonstrates that charge gradient microscopy combined with principal component analysis enables direct, quantitative imaging of ferroelectric domains and surface charge dynamics, overcoming limitations of traditional scanning probe techniques.

## Contribution

The study introduces the use of PCA to enhance charge gradient microscopy data, allowing for direct, quantitative analysis of ferroelectric polarization and surface charges.

## Key findings

- CGM signal scales linearly with scan speed
- Surface charge and polarization estimates agree with literature
- PCA significantly improves noise reduction in SPM data

## Abstract

Local domain structures of ferroelectrics have been studied extensively using various modes of scanning probes at the nanoscale, including piezoresponse force microscopy (PFM) and Kelvin probe force microscopy (KPFM), though none of these techniques measure the polarization directly, and the fast formation kinetics of domains and screening charges cannot be captured by these quasi-static measurements. In this study, we used charge gradient microscopy (CGM) to image ferroelectric domains of lithium niobate based on current measured during fast scanning, and applied principal component analysis (PCA) to enhance the signal-to-noise ratio of noisy raw data. We found that the CGM signal increases linearly with the scan speed while decreases with the temperature under power-law, consistent with proposed imaging mechanisms of scraping and refilling of surface charges within domains, and polarization change across domain wall. We then, based on CGM mappings, estimated the spontaneous polarization and the density of surface charges with order of magnitude agreement with literature data. The study demonstrates that PCA is a powerful method in imaging analysis of scanning probe microscopy (SPM), with which quantitative analysis of noisy raw data becomes possible.

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Source: https://tomesphere.com/paper/1706.02345