Inverse extraction of material properties by apertureless scanning near-field optical microscopy using phenomenological model

Abstract

Apertureless scanning near-field optical microscopy (a-SNOM) enables the surface properties of optically scattering materials to be measured with ultrahigh resolution. However, the detection signal is inevitably contaminated by background signal. The literature contains various configurations capable of directly obtaining a background-free detection signal of a-SNOM, but these methods generally require the use of a complex experimental setup and strict calibration. Accordingly, the present study provides a robust phenomenological model with a genetic algorithm (GA) for inversely extracting material properties without using a background-free signal from a complex experimental setup. Finally, the properties of SiC crystal in different structures are successfully and inversely extracted by only using the first and second orders of modulation signals as multiple objective functions in the curve-fitting GA.