Adaptive discrete mapping of dynamic nanomechanical property of soft materials on atomic force microscope

In this paper, an adaptive discrete nanomechanical mapping (A-DNM) technique is proposed for mapping time-varying nanomechanical properties of soft samples using atomic force microscope (AFM). Mapping time-varying nanomechanical properties is needed to investigate samples such as live cells undergoing dynamic evolutions. However, the existing methods based on continuous scanning are either too slow to capture time-elapsing variations of the sample over the entire sampled area, or only capable of mapping a small sample area. Contrarily, we propose to extend a discrete nanomechanical mapping scheme where only a set of chosen discrete locations (points of interests, POIs) are measured, thereby, dramatically increasing the number of measurements acquired at these POIs during the dynamic evolution of the sample occurring in minutes or faster. Specifically, through the proposed A-DNM approach, two challenges are addressed: First, the effect of time-varying sample topography during the nanomechanical evolution is accounted for by updating the estimation of the sample height at each POI during the mapping and compensating for it in the cantilever transition and engagement process. Secondly, an adaptive planning of the mapping sequence is proposed to adjust the distribution of the measurements between the POIs to accomodate the sample dynamic evolution. A POI-dynamics index is introduced to estimate the relative speeds of the nanomechanical evolutions at the POIs based on the measured data, and then online assign more measurements to those POIs of faster nanomechanical evolutions. The proposed approach is demonstrated through an experiment of mapping nanomechanical evolution of a poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) polymer undergoing crystallization process.