Machine learning assisted multifrequency AFM: Force model prediction

• DOI: 10.1063/5.0176688
• Publication Date: 2023-12-05T15:18:59Z
• Authors: Lamiaa Elsherbiny; Sergio Santos; Karim Gadelrab; Tuza Olukan; Josep Font; Victor Barcons; Matteo Chiesa
• Keywords: Formalism (music)

Multifrequency atomic force microscopy (AFM) enhances resolving power, provides extra contrast channels, and is equipped with a formalism to quantify material properties pixel by pixel. On the other hand, multifrequency AFM lacks ability extract examine profile validate given model while scanning. We propose exploiting data-driven algorithms, i.e., machine learning packages, predict optimum from observables of This approach allows distinguishing between different phenomena selecting suitable directly observables. generate predictive models using simulation data. Finally, can be employed analytically recover inputting right model.