snompy: a package for modelling scattering-type scanning near-field optical microscopy

TL;DR

snompy is an open-source Python library that simplifies the modeling of scattering-type scanning near-field optical microscopy (s-SNOM), enabling better quantitative analysis of nanoscale material properties through simulation and data recovery.

Contribution

This work introduces snompy, a Python package implementing key s-SNOM models, making quantitative near-field optical microscopy modeling more accessible and standardized.

Findings

Demonstrated simulation of nano-FTIR spectra.

Showed how to recover permittivity from experimental data.

Discussed modeling challenges like finite size effects.

Abstract

Scattering-type scanning near-field optical microscopy (s-SNOM) is a powerful technique for extreme subwavelength imaging and spectroscopy, with around 20 nm spatial resolution. But quantitative relationships between experiment and material properties requires modelling, which can be computationally and conceptually challenging. In this work, we present snompy an open-source Python library which contains implementations of two of the most common s-SNOM models, the finite dipole model (FDM) and the point dipole model (PDM). We show a series of typical uses for this package with demonstrations including simulating nano-Fourier transform infrared (FTIR) spectra and recovering permittivity from experimental s-SNOM data. We also discuss the challenges faced with this sort of modelling, such as competing descriptions of the models in literature, and finite size effects. We hope that snompy will make quantitative s-SNOM modelling more accessible to the wider research community, which will further empower the use of s-SNOM for investigating nanoscale material properties.