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Abstract Single‐stranded DNA (ssDNA) plays a pivotal role in both nanotechnology and various biological processes. Many processes and applications can be better understood with enhanced structural characterization of ssDNA; however, the dynamic nature of the molecule makes accurate characterization with atomistic resolution extremely difficult. This study uses a method that integrates experimental small‐angle X‐ray scatter (SAXS) data and molecular modeling data using a genetic algorithm (GA) to predict an all‐atom conformational ensemble of ssDNA. The results of this study also validate the performance of various AMBER force fields and implicit solvent models for ssDNA. Overall, the results are able to determine the most accurate atomistic representation of poly‐Thymine (polyT) in solution to date that closely matches the experimental SAXS observations enabling a better understanding of the behavior of ssDNA in solution. 

Abstract The number of applications of informatics or data‐driven discovery is growing in many fields, including materials science. The large amount of data that is readily available, combined with high‐level statistical algorithms, is proving to be extremely useful in developing complex predictive models with little to no human supervision or bias. However, in the field of soft matter, which includes complex materials such as polymers, liquids, emulsions, colloids, and gels, there is a slower adoption of informatics strategies than in adjacent fields. Here, the current state of soft matter informatics is discussed. Challenges specific to soft materials, including data classification, various degrees of organization at multiple length scales, and process‐dependent properties require unique approaches by researchers in order to develop robust informatics approaches in soft matter. The current ability to extract and analyze the information from the PoLyInfo database is demonstrated by the fitting of the Flory–Fox equation for glass transition temperature for several polymers. This Progress Report serves to introduce and excite the scientific community about the remarkable potential of informatics for exploring the properties of soft materials. 

Abstract Langmuir–Blodgett (LB) film deposition gives an opportunity to control the packing density and orientation of anisotropic nanoparticles at a monolayer level, allowing accurate characterization of their anisotropic material properties. The uniaxial deposition of rod‐shaped cellulose nanocrystals (CNCs) over a macroscopically large area is achieved by aligning the long axis of CNCs on the LB trough with the direction of the maximum drag force within the meniscus during the vertical pulling of the substrate from the LB trough. On the uniaxially‐aligned LB films, anisotropic linear and non‐linear optical properties of CNCs are obtained using Mueller matrix spectroscopy and sum frequency generation spectroscopy, respectively, and explained with time‐dependent density functional theory calculations. Also, the frictional anisotropy of the LB film is measured using atomic force microscopy and explained theoretically. The findings of this study will be valuable for preparation of anisotropic nanoparticle thin films with uniform arrangements and utilization of their anisotropic material properties.