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Abstract Recent investigations have pointed to physical entanglements that greatly outnumber chemical crosslinks as key sources of energy dissipation and low friction in hydrogel networks. Slide-ring gels are an emerging class of hydrogels described by their mobile crosslinks, which are formed by rings topologically constrained to slide along linear polymer chains within the network. These materials have enjoyed decades of study by polymer chemists but have been underexplored by the tribology community. In this work, we synthesized a pseudo-rotaxane crosslinker from poly(ethylene glycol) diacrylate (PEG-diacrylate) andα-cyclodextrin-acrylate followed by hydrogel networks by connecting the sliding crosslinks with polyacrylamide chains. The mechanical and tribological properties of slide-ring hydrogels were investigated using a custom-built microtribometer. Slide-ring hydrogels exhibit unique behavior compared to conventional covalently crosslinked polyacrylamide hydrogels and offer a vast design space for future investigations. Graphical Abstract 

Molecular architectures known as bottlebrush polymers provide unique opportunities to tune the structure and properties of soft materials with applications ranging from rubbers to thin films and composites. This review addresses recent developments and future opportunities in the field with an emphasis on materials science enabled by contemporary bottlebrush chemistry. 

Doping is required to increase the electrical conductivity of organic semiconductors for uses in electronic and energy conversion devices. The limited number of commonly used p-type dopants suggests that new dopants or doping mechanisms could improve the efficiency of doping and provide new means for processing doped polymers. Drawing on Lewis acid–base pair chemistry, we combined Lewis acid dopant B(C 6 F 5 ) 3 (BCF) with the weak Lewis base benzoyl peroxide (BPO). The detailed behavior of p-type doping of the model polymer poly(3-hexylthiophene) (P3HT) with this Lewis acid–base pair in solution was examined. Solution 19 F-NMR spectra confirmed the formation of the expected counterion, as well as side products from reactions with solvent. BCF : BPO was also found to efficiently dope a range of semiconducting polymers with varying chemical structures demonstrating that the BCF : BPO combination has an effective electron affinity of at least 5.3 eV. In thin films of regioregular P3HT cast from the doped solutions, delocalized polarons formed due to the large counterions leading to a large polaron-counterion distance. At and above 0.2 eq. BCF : BPO doping, amorphous areas of the film became doped, disrupting the structural order of the films. Despite the change in structural order, thin films of regioregular P3HT doped with 0.2 eq. BCF : BPO had a conductivity of 25 S cm −1 . This study demonstrates the effectiveness of a two-component Lewis acid–base doping mechanism and suggests additional two-component Lewis acid–base chemistries should be explored. 

Polarized resonant soft X-ray scattering (P-RSoXS) has emerged as a powerful synchrotron-based tool that combines the principles of X-ray scattering and X-ray spectroscopy. P-RSoXS provides unique sensitivity to molecular orientation and chemical heterogeneity in soft materials such as polymers and biomaterials. Quantitative extraction of orientation information from P-RSoXS pattern data is challenging, however, because the scattering processes originate from sample properties that must be represented as energy-dependent three-dimensional tensors with heterogeneities at nanometre to sub-nanometre length scales. This challenge is overcome here by developing an open-source virtual instrument that uses graphical processing units (GPUs) to simulate P-RSoXS patterns from real-space material representations with nanoscale resolution. This computational framework – calledCyRSoXS(https://github.com/usnistgov/cyrsoxs) – is designed to maximize GPU performance, including algorithms that minimize both communication and memory footprints. The accuracy and robustness of the approach are demonstrated by validating against an extensive set of test cases, which include both analytical solutions and numerical comparisons, demonstrating an acceleration of over three orders of magnitude relative to the current state-of-the-art P-RSoXS simulation software. Such fast simulations open up a variety of applications that were previously computationally unfeasible, including pattern fitting, co-simulation with the physical instrument foroperandoanalytics, data exploration and decision support, data creation and integration into machine learning workflows, and utilization in multi-modal data assimilation approaches. Finally, the complexity of the computational framework is abstracted away from the end user by exposingCyRSoXSto Python usingPybind. This eliminates input/output requirements for large-scale parameter exploration and inverse design, and democratizes usage by enabling seamless integration with a Python ecosystem (https://github.com/usnistgov/nrss) that can include parametric morphology generation, simulation result reduction, comparison with experiment and data fitting approaches. 

Abstract Charge transport in molecular solids, such as semiconducting polymers, is strongly affected by packing and structural order over several length scales. Conventional approaches to modeling these phenomena range from analytical models to numerical models using quantum mechanical calculations. While analytical approaches cannot account for detailed structural effects, numerical models are expensive for exhaustive (and statistically significant) analysis. Here, we report a computationally scalable methodology using graph theory to explore the influence of molecular ordering on charge mobility. This model accurately reproduces the analytical results for transport in nematic and isotropic systems, as well as experimental results of the dependence of the charge carrier mobility on orientation correlation length for polymers. We further model how defect distribution (correlated and uncorrelated) in semiconducting polymers can modify the mobility, predicting a critical defect density above which the mobility plummets. This work enables rapid (and computationally extensible) evaluation of charge mobility semiconducting polymer devices.