Kelvin Probe Force Microscopy (KPFM) is a scanned probe microscopy technique that allows local electric properties to be measured with nanoscale resolution. This technique, when applied to perovskite and other organic solar cells, is useful for determining local material properties correlated with overall device performance and degradation. There are currently two methods for interpreting KPFM data. The traditional KPFM equation incorrectly assumes that sample-tip charges respond instantaneously to changes in applied tip-sample voltage. In contrast, the impedance model describes the sample in terms of resistors and capacitors, giving much more information about the sample. However, the equations for the impedance model depend heavily on the tip parameters and can be difficult to estimate. This greatly limits the KPFM experiments researchers can perform and the information they can extract about their sample. The focus of this work was to use computational capacitance models to obtain the parameters necessary for the impedance model. The publicly available Capsol model was utilized, but this model was numerically unstable when applied to perovskite samples. Ultimately, a new Python simulation was written which correctly handles perovskite and other semiconductor samples. Comparing the results from this model with experimental results and an analytical answer, found by estimating the tip as a sphere and the sample as a dielectric slab, it was determined that the Python program could give reasonable values for capacitance, force, and frequency shift. These results allow for predictions about a variety of KPFM experiments, such as Local Dielectric Broadband Spectroscopy. A publicly available website was developed to allow researchers to input their tip and sample parameters and obtain these necessary values. This site will allow a broader community of scientists to use advanced KPFM techniques and assess their results.

Using computational models of capacitance to interpret KPFM data and improve solar cell materials

ACS Spring 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.