skip to main content


Title: Imaging via complete cantilever dynamic detection: General dynamic mode imaging and spectroscopy in scanning probe microscopy

We develop and implement a multifrequency spectroscopy and spectroscopic imaging mode, referred to as general dynamic mode (GDM), that captures the complete spatially- and stimulus dependent information on nonlinear cantilever dynamics in scanning probe microscopy (SPM). GDM acquires the cantilever response including harmonics and mode mixing products across the entire broadband cantilever spectrum as a function of excitation frequency. GDM spectra substitute the classical measurements in SPM, e.g. amplitude and phase in lock-in detection. Here, GDM is used to investigate the response of a purely capacitively driven cantilever. We use information theory techniques to mine the data and verify the findings with governing equations and classical lock-in based approaches. We explore the dependence of the cantilever dynamics on the tip–sample distance, AC and DC driving bias. This approach can be applied to investigate the dynamic behavior of other systems within and beyond dynamic SPM. In conclusion, GDM is expected to be useful for separating the contribution of different physical phenomena in the cantilever response and understanding the role of cantilever dynamics in dynamic AFM techniques.
ORCiD logo [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Additional Journal Information:
Journal Volume: 27; Journal Issue: 41; Journal ID: ISSN 0957-4484
IOP Publishing
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; scanning probe microscopy (SPM); kelving probe force microscopy (KPFM); electrostatic force microscopy (EFM); principal component analysis (PCA); big data; high performance computing (HPC)
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1323554