Multiparametric characterization of heterogeneous soft materials using contact point detection-based atomic force microscopy

Force-distance (FD) curve-based atomic force microscopy (AFM) has been widely applied for characterizing the surface morphology and mechanical properties of soft materials at nanometer resolution. In this paper, we demonstrate FD curve-based AFM using a newly developed algorithm to detect contact points (CPs) from each FD curve and to determine properties such as stiffness, adhesion, and deformation. The performance of our method is compared with that of the tapping and peak force tapping (PFT) modes by imaging the same area of a heterogeneous blend of soft and hard polymers by using the same tip. The morphology obtained with our CP detection-based method is comparable to that obtained using the tapping mode, but PFT shows strong deviation in height images obtained on soft polymer regions. We also acquire FD curves at a much higher sampling rate than PFT. A site-dependent decaying oscillation following snap-in is detected, and the frequency of the decaying oscillation appears to be related to the stiffness of the region, pointing to a new direction for characterizing viscoelastic properties of sample surfaces with a high spatial resolution.