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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.

 

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. 

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.

 

Resonant soft X-ray scattering (RSoXS) probes structure with chemical sensitivity that is useful for determining the morphology of multiblock copolymers. However, the hyperspectral scattering data produced by this technique can be challenging to interpret. Here, we use computational scattering simulations to extract the microstructure of a model triblock copolymer from the energy-dependent scattering from RSoXS. An ABC triblock terpolymer formed from poly(4-methylcaprolactone) (P4MCL), poly(2,2,2-trifluoroethylacrylate) (PTFEA), and poly (dodecylacrylate) (PDDA), P4MCL- block -PTFEA- block -PDDA, was synthesized as the model triblock system. Through quantitative evaluation of simulated scattering data from a physics-informed set of candidate structure models against experimental RSoXS data, we find the best agreement with hexagonally packed core–shell cylinders. This result is also consistent with electron-density reconstruction from hard X-ray scattering data evaluated against electron-density maps generated with the same model set. These results demonstrate the utility of simulation-guided scattering analysis to study complex microstructures that are challenging to image by microscopy. 

Semiconducting polymers have the potential to be used in thermoelectric devices that are lightweight, flexible, and fabricated using solution processing. Because of the structural and energetic disorder of these polymers, the relationship between their structure and thermoelectric properties is complex. We review how interrelated processing routes and doping methods affect the thermoelectric properties of polymers. The studies highlighted here have led to correlations between thermopower and electrical conductivity that can be described by theories under investigation. With greater understanding of the materials properties behind their performance, semiconducting polymers can be used in future power generation or cooling devices. 

Thin films of amorphous small molecule semiconductors are widely used in organic light emitting displays and have promising applications in solar cells and thermoelectric devices. Adding dopants increases the conductivity of organic semiconductors, but high concentrations of dopants can disrupt their structural ordering, alter the shape of the electronic density of states in the material, and increase the effects of Coulomb interactions on charge transport. Electrical doping of the solution processable hole-transport material 2,2′,7,7′-tetrakis[ N , N -di(4-methoxyphenyl)amino]-9,9′-spirobifluorene (spiro-OMeTAD) was studied with 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F 4 TCNQ) as a p-type dopant. Infiltration of F 4 TCNQ from the vapor phase into films of spiro-OMeTAD provided a route to highly doped films with up to 39 ± 2 mol% doping. Structural characterization confirmed that the films remain amorphous even at the highest doping levels with no apparent phase separation. We quantitatively determined the carrier concentration using UV-Vis spectroscopy to interpret the evolution of the electrical conductivity. Over the range of carrier concentrations (10 19 –10 20 1 cm −3 ), the electrical conductivity increased no more than linearly with carrier concentration, while the thermopower had a small increase with carrier concentration. The trends in conductivity and thermopower were related to the unique electronic structure of spiro-OMeTAD, which is able to support two carriers per molecule. Temperature-dependent conductivity measurements were used to further analyze the transport mechanism.