Determining surface properties with bimodal and multimodal AFM

TL;DR

This paper develops a theoretical framework for using bimodal and multimodal AFM to better characterize surface properties, verified through noisy simulations mimicking real room-temperature conditions.

Contribution

It introduces a theoretical basis for extracting surface parameters from multimodal AFM data, enhancing surface characterization techniques.

Findings

The theory accurately approximates tip-surface interaction parameters.

Simulations confirm robustness under realistic noise conditions.

Multimodal AFM provides richer surface information.

Abstract

Conventional dynamic atomic force microscopy (AFM) can be extended to bimodal and multimodal AFM in which the cantilever is simultaneously excited at two ore more resonance frequencies. Such excitation schemes result in one additional amplitude and phase images for each driven resonance, and potentially convey more information about the surface under investigation. Here we present a theoretical basis for using this information to approximate the parameters of a tip-surface interaction model. The theory is verified by simulations with added noise corresponding to room-temperature measurements.