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.

Architected Low-Tortuosity Electrodes with Tunable Porosity from Nonequilibrium Soft-Matter Processing.

Mass transport is performance-defining across energy storage devices, often causing limitations at high current rates. To optimize and balance the device-scale energy and power density for a given energy storage demand, tailored electrode architectures with precisely controllable phase dimensions are needed in combination with low-tortuosity channels that maximize the geometric component of diffusion and species flux. A material-agnostic nonequilibrium soft-matter process is reported to fabricate free-standing inorganic composite electrodes with adjustable thicknesses of 100s of µm, featuring straight and accessible channels ranging in diameter from 5-30 µm, coupled with tunable material-to-pore ratios. Such architected anode and cathode electrodes exhibit electrochemical and architectural stability over extended cycling in a full-cell battery. Further, mass-transport constraints appear at high current densities, and the lithiation step is identified as rate-performance limiting, a result of insufficient lithium-ion supply and concentration polarization. The results demonstrate the need for and feasibility of tailored electrode architectures where dimensional ratios between low-tortuosity channels, the charge-storing matrix, and electrode thickness are tunable to meet coupled power and energy-storage requirements.