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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.

 

Iron- and nitrogen-doped carbon (Fe-N-C) represents a promising class of alternative electrocatalysts to noble metals for the oxygen reduction reaction (ORR) in acidic environments. To make Fe-N-C active, one of the most critical parameters is microporosity, which must be controlled to maximize the active site density. However, the use of microporosity must be optimized for the requirement of high-flux mass transport. Here, we synthesized and demonstrated gyroidal mesoporous Fe-N-C with microporous pore walls as an avenue to combine a high active-site density with favorable mass transport at high flux. The gyroidal mesoporous Fe-N-C catalysts have competitive gravimetric and volumetric ORR activities, comparable to the ORR activity obtained in purely microporous configurations despite having mesoporous features. Our result suggests that the ORR activity of microporous Fe-N-C electrocatalysts can be combined with mesoporosity through the use of mesoporous Fe-N-C with microporous pore walls. We further investigate effects of the nitrogen incorporation method on mesoporous N-doped carbon electrocatalysts. We find that despite having ∼2 × higher N concentration, nitrogen incorporationviaNH₃yields similar ORR activity to incorporationviaa chemical additive, a finding we attribute to the role of pyridinic and quaternary N in the ORR.

 

Materials combining an asymmetric pore structure with mesopores everywhere enable high surface area accessibility and fast transport, making them attractive for e.g., energy conversion and storage applications. Block copolymer (BCP)/inorganic precursor co‐assembly combined with non‐solvent induced phase separation (NIPS) provides a route to materials in which a mesoporous top surface layer merges into an asymmetric support with graded porosity along the film normal and mesopores throughout. Here, the co‐assembly and non‐solvent‐induced phase separation (CNIPS) of poly(isoprene)‐b‐poly(styrene)‐b‐poly(4‐vinylpyridine) (ISV) triblock terpolymer and titanium dioxide (TiO₂) sol‐gel nanoparticlesare reported. Heat‐treatment in air results in free‐standing asymmetric porous TiO₂. Further thermal processing in ammonia results in free‐standing asymmetric porous titanium nitride (TiN). processing changes alter structural membrane characteristics is demonstrated. Changing the CNIPS evaporation time results in various membrane cross‐sections ( finger‐like to sponge‐like). Oxide and nitride material composition, crystallinity, and porosity are tuned by varying thermal processing conditions. Finally, thermal processing condition effects are probed on phase‐pure asymmetric nitride membrane behavior using cyclic voltammetry to elucidate their influence, e.g., on specific capacitance. Results provide further insights into improving asymmetric and porous materials for applications including energy conversion and storage, separation, and catalysis and motivate a further expansion of CNIPS to other (in)organic materials.

 

Crystalline and 3D continuous mesoporous quaternary CsTaWO₆semiconductors are prepared with different degrees of long‐range periodic order and local order, respectively, to investigate the influence of periodic pore order on the photocatalytic performance in hydrogen evolution of mesoporous photocatalysts. The degree of long‐range order of the mesopores is changed by modifying the ratio between metal precursors and soft polymer template poly(isoprene‐b‐styrene‐b‐ethylene oxide) (PI‐b‐PS‐b‐PEO; ISO) in the sol–gel synthesis. Long‐range periodic order is found to have no appreciable advantage compared with an only locally ordered continuous pore system. On the contrary, nonperiodically ordered mesopores result in higher activity toward photocatalytic hydrogen evolution, even with slightly smaller pore diameter and lower cumulative pore volume. Most importantly, it is shown that pore connectivity and heterogeneous pore systems in mesoporous photocatalysts play a major role for hydrogen evolution when other parameters are confirmed to be not rate limiting.

 

We have prepared the first crystalline and 3D periodically ordered mesoporous quaternary semiconductor photocatalyst in an evaporation-induced self-assembly assisted soft-templating process. Using lab synthesized triblock-terpolymer poly(isoprene- b -styrene- b -ethylene oxide) (ISO) a highly ordered 3D interconnected alternating gyroid morphology was achieved exhibiting near and long-range order, as evidenced by small angle X-ray scattering (SAXS) and electron microscopy (TEM/SEM). Moreover, we reveal the formation process on the phase-pure construction of the material's pore-walls with its high crystallinity, which proceeds along a highly stable W 5+ compound, by both in situ and ex situ analyses, including X-ray powder diffraction (XRPD), Fourier transform infrared spectroscopy (FTIR) and electron paramagnetic resonance (EPR). The resulting photocatalyst CsTaWO 6 with its optimum balance between surface area and ordered mesoporosity ultimately shows superior hydrogen evolution rates over its non-ordered reference in photocatalytic hydrogen production. This work will help to advance new self-assembly preparation pathways towards multi-element multifunctional compounds for different applications, including improved battery and sensor electrode materials.