Since the dipole-dipole interaction between the induced sample dipole and the image tip dipole varies with ~ 1/z4 dependence where z is the tip-sample spacing, PiFM is expected to provide extreme surface sensitivity. We use PS(polystyrene)-b-PTMSS[poly(4-trimethylsilylstyrene)] block copolymer (BCP) with horizontal lamellae to demonstrate the surface sensitivity. The pitch L0 of the BCP is ~22 nm as shown in cartoon figure below. The topography and phase images of the BCP sample are shown next to the cartoon in the top row. While the topography confirms the presence of the “island” features, neither topography nor phase images can shed any light on the nature of the molecules associated with the structures. In fact, it will be difficult to find an analytical technique that combines the surface chemical sensitivity and the nanoscale spatial resolution that are required to shed light on the chemical nature of the molecules associated with this type of structures.
The bottom row shows the PiFM images acquired at 1493 cm-1 and 1599 cm-1 to identify PS molecules (colored in red) and PTMSS molecules (colored in blue) respectively. The bottom right image overlays the chemical map information on the 3D topography rendering to clearly confirm the chemical 3D structure of the sample; one can see PS molecules cover regions surrounding the island features (identifiable by taller features in topography) while PTMSS molecules cover the taller island features. Thus PiFM is capable of identifying which molecules cover the different regions even though the layer that we are measuring is only 5.5 nm thick.
Figure below shows PiFM spectra associated with two different bi-layer samples, one with PS on top of PTMSS and another with PTMSS on top of PS. One can see that even in the case of PTMSS on top of PS, the two PS vibrational bands are clearly seen in the spectrum albeit greatly reduced from that of PS on top of PTMSS. The rapid reduction in the PiFM signal is due to the dipole-dipole nature of PiFM, which results in its extremely surface sensitivity.
Download the PDF version of this application blog to get a more thorough picture of this interesting sample and its variant. We thank Michael Maher and Prof. Grant Wilson of Univ. of Texas at Austin for the samples.