Generalizable Framework for Algorithmic Interpretation of Thin Film Morphologies in Scanning Probe Images.

We describe an open-source and widely adaptable Python library that recognizes morphological features and domains in images collected via scanning probe microscopy. π-Conjugated polymers (CPs) are ideal for evaluating the Materials Morphology Python (m2py) library because of their wide range of morphologies and feature sizes. Using thin films of nanostructured CPs, we demonstrate the functionality of a general m2py workflow. We apply numerical methods to enhance the signals collected by the scanning probe, followed by Principal Component Analysis (PCA) to reduce the dimensionality of the data. Then, a Gaussian Mixture Model segments every pixel in the image into phases, which have similar material-property signals. Finally, the phase-labeled pixels are grouped and labeled as morphological domains using either connected components labeling or persistence watershed segmentation. These tools are adaptable to any scanning probe measurement, so the labels that m2py generates will allow researchers to individually address and analyze the identified domains in the image. This level of control, allows one to describe the morphology of the system using quantitative and statistical descriptors such as the size, distribution, and shape of the domains. Such descriptors will enable researchers to quantitatively track and compare differences within and between samples.

Sonocrystallization of conjugated polymers with ultrasound fields.

Ultrasound acoustic waves are demonstrated to assemble poly-3-hexylthiophene (P3HT) chains into nanofibers after they are fully dissolved in what are commonly considered to be 'good' solvents. In the absence of ultrasound, the polymer remains fully dissolved and does not self-assemble for weeks. UV-vis spectroscopy, ultra-small angle X-ray scattering (USAXS) and small angle neutron scattering (SANS) are used to characterize the induced assembly process and to quantify the fraction of polymer that forms nanofibers. It is determined that the solvent type, insonation time, and aging periods are all important factors affecting the structure and final concentration of fibers. The effect of changing polymer regio-regularity, alkyl chain length, and side chain to thiophene ratio are also explored. High intensity focused ultrasound (HIFU) fields of variable intensity are utilized to reveal the physical mechanisms leading to nanofiber formation, which is strongly correlated to cavitation events in the solvent. This in situ HIFU cell, which is designed for simultaneous scattering analysis, is also used to probe for structural changes occurring over multiple length scales using USAXS and SANS. The proposed acoustic assembly mechanism suggests that, even when dispersed in 'good' solvents such as bromobenzene, dichlorobenzene and chloroform, P3HT chains are still not in a thermodynamically stable state. Instead, they are stabilized by local energy barriers that slow down and effectively prevent crystallization. Ultrasound fields are found to provide enough mechanical energy to overcome these barriers, triggering the formation of small crystalline nuclei that subsequently seed the growth of larger nanofibers.