Direct Correlation of Single-Particle Motion to Amorphous Microstructural Components of Semicrystalline Poly(ethylene oxide) Electrolytic Films

Machine-Learning Solutions for the Analysis of Single-Particle Diffusion Trajectories

Single-particle traces of the diffusive motion of molecules, cells, or animals are by now routinely measured, similar to stochastic records of stock prices or weather data. Deciphering the stochastic mechanism behind the recorded dynamics is vital in understanding the observed systems. Typically, the task is to decipher the exact type of diffusion and/or to determine the system parameters. The tools used in this endeavor are currently being revolutionized by modern machine-learning techniques. In this Perspective we provide an overview of recently introduced methods in machine-learning for diffusive time series, most notably, those successfully competing in the anomalous diffusion challenge. As such methods are often criticized for their lack of interpretability, we focus on means to include uncertainty estimates and feature-based approaches, both improving interpretability and providing concrete insight into the learning process of the machine. We expand the discussion by examining predictions on different out-of-distribution data. We also comment on expected future developments.

Single-Molecule Fluorescence Investigations of Solute Transport Dynamics in Nanostructured Membrane Separation Materials

Many materials used for membrane separations are composed of nanoscale structures such as pores and domains. Such nanostructures often control the solute permeability and selectivity of the separation membranes. Thus, for future development of highly efficient separation membranes, it is important to understand the structural and chemical properties of these nanostructures and also their influences on solute transport dynamics. For the last two decades, single-molecule fluorescence techniques have been used to measure the detailed dynamics of solute molecules diffusing in various nanostructured materials, giving valuable insights into molecular transport mechanisms influenced by nanoscale material heterogeneity. This Perspective discusses recent single-molecule fluorescence studies on solute diffusion in materials relevant to membrane separations, including dense polymer films and nanoporous materials. These studies have revealed the formation and properties of nanostructures and unique transport dynamics of solute molecules manipulated by their confinement and partitioning to the nanostructures, which play key roles in membrane separations. This Perspective will also point out scientific challenges toward a thorough understanding of molecular-level mechanisms in membrane separations.

Single-Molecule Tracking in Poly(Ethylene Oxide) Films: Revealing the Effects of Molecular Weight, Network Plasticization, and Thermal Annealing on Anionic Dye Diffusion

This paper reports single-molecule tracking (SMT) measurements of the diffusion behaviors of individual, anionic sulforhodamine B (SRB) dye molecules in a series of poly(ethylene oxide) (PEO) films, aimed at clarifying the influences of the molecular weight, network plasticization, and thermal annealing on such dynamics. Micrometer-thick PEO films were prepared by drop-casting from its aqueous (0.2%, 1 nM SRB) solution, followed by drying in air and thermal annealing at 90 °C for 36 h. The diffusion of individual SRB occurring within the amorphous domains was recorded at different relative humidities (5-95%) to characterize the microscale domains' local aspect-ratio, orientation, and molecular permeability at high spatial resolution. The results revealed the involvement of crystalline phases in confining SRB diffusion to submicron distances and guiding longer-range diffusion along one-dimensional-like amorphous morphologies. Upon annealing, amorphous domains were wider, more continuous, and more permeable to SRB probes. The enhanced transport in plasticized PEO, as reflected by the higher SRB mobility and diffusivity, was linked to the polymer's higher chain and segmental mobilities and reduced hydrogen-bonding interactions. This work has demonstrated the usefulness of SMT for an advanced characterization of solid polymer electrolytic films, highly beneficial for the development of safer lithium-ion batteries.