Rapid broadband discrete nanomechanical mapping of soft samples on atomic force microscope

Jingren Wang, Xuemei Li, Xuemei Li, Qingze Zou, Chanmin Su, Nicole S. Lin

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


In this paper, an approach to achieve rapid broadband discrete nanomechanical mapping of soft samples using an atomic force microscope is developed. Nanomechanical mapping (NM) is needed to investigate, for example, dynamic evolution of the nanomechanical distribution of the sample - provided that the mapping is fast enough. The throughput of conventional NM methods, however, is inherently limited by the continuous scanning involved where the probe visits each sampling location continuously. Thus, we propose to significantly reduce the number of measurements through discrete mapping where only discrete sampling locations of interests are visited and measured. An online-searching learning-based technique is utilized to achieve rapid probe engagement and withdrawal with the interaction force minimized at each sampling location. Then, a control-based nanoindentation measurement technique is used to quickly acquire the nanomechanical property at each location, over frequencies that can be chosen arbitrarily in a broad range. Finally, a decomposition-based learning approach is explored to achieve rapid probe transitions between the sampling locations. The proposed technique is demonstrated through experiments using a Polydimethylsiloxane (PDMS) sample and a PDMS-epoxy sample as examples.

Original languageEnglish (US)
Article number335705
Issue number33
StatePublished - Aug 14 2020

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Chemistry(all)
  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering
  • Electrical and Electronic Engineering


  • atomic force microscope
  • fibonacci searching
  • learning-based online optimization
  • nanomechanical mapping
  • soft materials


Dive into the research topics of 'Rapid broadband discrete nanomechanical mapping of soft samples on atomic force microscope'. Together they form a unique fingerprint.

Cite this