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We present a rib waveguide design in β-barium borate-on-insulator platform for coherent deep-ultraviolet generation down to a wavelength of 230 nm via nonlinear frequency conversion.
Copper and rare earth element-containing dealuminated Beta zeolites (CuREE/deAlBeta) are promising catalysts for the conversion of ethanol to C 3+ olefins en route to sustainable aviation fuel. Product selectivities over CuREE/deAlBeta depend on the identity of the REE. Here, in this study, a suite of La/deAlBeta catalysts of varied La loading are prepared, and their reactivities, selectivities, and apparent C-C coupling kinetics in the cascade reaction between ethanol and acetaldehyde are reported. Ex situ and in situ titrations to quantify Lewis acidic La sites quantify distinct numbers of sites, suggesting a distribution of site types. Across a series of REE/deAlBeta catalysts (REE = Y, La, Lu, Yb, Gd), the selectivity to secondary products correlates with the pyridine heats of adsorption at REE Lewis acid sites. The turnover frequency (per Lewis acid site) for C–C coupling was similar across the series of REE/deAlBeta catalysts. Y/deAlBeta and La/deAlBeta, which have the most disparate secondary product selectivities, had similar kinetics for C–C coupling. These findings demonstrate the complexity of quantifying active sites in REE/deAlBeta zeolites, and the sensitivity of the selectivity, but not the reactivity for C–C coupling, to the identity of the REE atom in REE/deAlBeta zeolites.
Zeolites serve as essential catalytic platforms for many industrial processes, including emerging ethanol-to-olefins (ETO) upgrading technologies. Although metal-loaded (Cu, Zn, Y) dealuminated beta (deAlBeta) zeolite powders are promising catalysts for direct ETO conversion with high selectivity to butene-rich C3+ olefins necessary for production of sustainable aviation fuels (SAF), development of these materials as shaped technical bodies through the incorporation of binders is required for scale-up and commercial viability. Here, we report the ethanol upgrading performance of Cu-Zn-Y/deAlBeta extruded catalysts formulated with either alumina or kaolin clay binders. Both extrudates exhibit high ethanol dehydration reactivity which competes with the initial ethanol dehydrogenation step in the direct ETO reaction network. Consequently, elevated selectivity to dehydration side products (ethylene, diethyl ether) at ∼100% ethanol conversion is observed on Cu-Zn-Y/deAlBeta extrudates compared to the powder catalyst, which inhibits production of desired C3+ olefins. Utilizing microscopy and spectroscopic characterizations, we attribute this to Al migration from binder to zeolite particles within the extrudates, thus re-aluminating the zeolite and generating Brønsted acid sites active for dehydration reactions. This work elucidates the effects of binder incorporation on ETO product distributions and emphasizes that binder selection must be carefully considered during design of extruded zeolite catalysts.
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Various machine learning (ML) and deep learning (DL) techniques have been recently applied to the forecasting of laboratory earthquakes from friction experiments. The magnitude and timing of shear failures in stick-slip cycles are predicted using features extracted from the recorded ultrasonic or acoustic emission (AE) signals. In addition, the Rate and State Friction (RSF) constitutive laws are extensively used to model the frictional behavior of faults. In this work, we use data from shear experiments coupled with passive acoustic (variance, kurtosis, and AE rate) interleaved with active source ultrasonic monitoring (transmitted wave amplitude) to develop physics-informed neural network (PINN) models incorporating the RSF law and AE rate generation equation with wave amplitude serving as a proxy for friction state variable. This PINN framework allows learning RSF parameters from stick-slip experiments rather than measuring them through a series of velocity step experiments. We observe that when the stick-slip cycles are irregular, the PINN models outperform the data-driven DL models. Transfer learning (TL) PINN models are also developed by pre-training on data collected at one normal stress level followed by forecasting shear failures and retrieving RSF parameters at other stress levels (i.e., with different recurrence intervals) after retraining on a limited amount of new data. Our findings suggest that TL models perform better compared to standalone models. Both standalone and TL PINN-estimated RSF parameters and their ground truth values show excellent agreements thus demonstrating that RSF parameters can be retrieved from laboratory stick-slip experiments using the corresponding acoustic data and that the transmitted wave amplitude provides a good representation of the evolving frictional state during stick-slips.
In this study, waste forms were being explored for an electrochemical salt simulant, , referred to as ERV3, which is a high-LiCl/KCl salt containing simulated fission products (i.e., Sr, Cs, Nd) and Na to represent bond sodium from Experimental Breeder Reactor-II metallic fast reactor fuel. The goal was to find glassy systems that could be used to immobilize the salt in a single-step process. The envisionment of this process would be find a frit glass that could be added to the salt waste, heat treated, poured into waste canisters, and then stored for disposal. To perform this study, a literature review was conducted, the most promising seven systems were fabricated without the salt, and then mixed with salt simulant and heat treated under different processes. The criteria that were used to screen potential compositions included demonstrated alkali incorporation, could be melted at reasonably low temperature ( T ≤ 1000°C), and if the compositions had some demonstrated data for waste-form-related properties, that was a benefit. High marks were given for compositions that showed amorphous nature after slow cooling of samples containing ERV3.
Pulsed-neutron die-away (PNDA) experiments were completed at Lawrence Livermore National Laboratory (LLNL). The goal of these experiments was to provide a benchmark to validate thermal neutron scattering laws of H 2 O. The experiment was conducted with a deuterium-tritium (D-T) neutron generator producing pulses of 14.1 MeV neutrons that impinged on a moderating target. The neutrons scattered and thermalized within the target and were counted as a function of time using Helium-3 ( 3 He) detectors that surrounded the target. These data provide a time-decay profile of the neutron population from which the time eigenvalue of the experiment is calculated. The time eigenvalue quantity α represents the integral parameter of interest. This report describes the measurements for H 2 O targets. The measurements were conducted over several days beginning on October 23rd, 2023. All measurements were completed at the low-scatter facility at LLNL. The evaluation identifier is FUND-LLNL-DT-H2O-PNDA-001.
Pulsed-neutron die-away (PNDA) experiments were completed at Lawrence Livermore National Laboratory (LLNL). The goal of these experiments was to provide a benchmark to validate thermal neutron scattering laws of H 2 O. The experiment was conducted with a deuterium-tritium (D-T) neutron generator producing pulses of 14.1 MeV neutrons that impinged on a moderating target.
Direct conversion of bioethanol to C₃⁺olefins is a promising pathway for sustainable aviation fuel (SAF) production, but catalyst deactivation limits long-term operation. The stability and deactivation mechanisms of multifunctional Cu–Y/Beta zeolite catalysts were investigated for ethanol-to-olefins conversion over 300 h time-on-stream in the presence of H2. Catalytic testing reveals progressive losses in ethanol conversion and C₃⁺ olefin selectivity accompanied by increased acetaldehyde formation. The catalyst testing studies correlate with a suite of characterizations of fresh, spent, and regenerated catalysts to identify the deactivation factors. The loss of Y Lewis acid sites is the primary deactivation element. Reversible acid site deactivation is caused by coke deposition, which blocks Y-derived Lewis acid sites responsible for aldol condensation, MPV reduction, and alcohol dehydration. Minor irreversible deactivation is observed and possibly results from hydrothermal dehydroxylation of Y–silanol interactions, resulting in permanent loss of Lewis acidity without zeolite framework degradation or Y aggregation. Cu sites undergo limited agglomeration into small nanoparticles but contribute insignificantly to catalyst deactivation, under the investigated time frame. Oxidative regeneration removes coke and redistributes Cu sites, leading to full recovery of the initial catalytic performance though the Y Lewis acid sites are unable to fully recover. These findings establish Lewis acid site degradation as the primary deactivation mechanism impacting long-term catalyst stability
Full scale turbojet engine testing of fuels - pentaborane-jp-4 mixtures and trimethylborate azeotrope performance
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