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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31

Controlling Metal–Organic Framework/ZnO Heterostructure Kinetics through Selective Ligand Binding to ZnO Surface Steps

Metal–organic framework (MOF) heterostructures exhibit unique properties beyond those of individual components, but their design requires an understanding of energetic and kinetic controls at MOF–substrate interfaces. Although the structural relationship has been widely used in heterostructure design, it overlooks the interplay between the organic ligand and the substrate which controls the kinetics and energetics of growth of the final structure. In this study, we used zeolitic imidazolate frameworks (ZIF-8) on ZnO as a model system to evaluate this interplay via in situ monitoring and simulations. Our results demonstrate multiple roles of the 2-methyl-imidazole (2-MIM) ligand as “dissolution-promoter”, “step-pinner”, and “terrace-binder” on the ZnO (001) face and “dissolution-promoter” and “terrace-binder” on the ZnO (100) face. Through these multiple face-specific roles, 2-MIM modulates ZnO dissolution kinetics and, hence, the Zn 2+ release rate, tuning local supersaturations that dictating the characteristic ZIF-8 crystallization kinetics on different substrate faces. The critical thickness for transition from 2D to 3D growth is dictated by competition between interfacial and strain energies. The atomic-scale mechanism of the coupled substrate dissolution and MOF growth, mediated by selective linker–substrate binding, furnishes a new synthesis pathway for other complex heterostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Precession modulation of the South Pacific westerly wind belt over the past million years

The southern westerly wind belt (SWW) interacts with the Antarctic Circumpolar Current and strongly impacts the Southern Ocean carbon budget, and Antarctic ice-sheet dynamics across glacial–interglacial cycles. We investigated precipitation-driven sediment input changes to the Southeast Pacific off the southern margin of the Atacama Desert over the past one million years, revealing strong precession (19/23-ka) cycles. Our simulations with 2 ocean–atmosphere general circulation models suggest that observed cyclic rainfall changes are linked to meridional shifts in water vapor transport from the tropical Pacific toward the southern Atacama Desert. These changes reflect a precessional modulation of the split in the austral winter South Pacific jet stream. For precession maxima, we infer significantly enhanced rainfall in the southern Atacama Desert due to a stronger South Pacific split jet with enhanced subtropical/subpolar jets, and a weaker midlatitude jet. Conversely, we derive dry conditions in northern Chile related to reduced subtropical/subpolar jets and an enhanced midlatitude jet for precession minima. The presence of precessional cycles in the Pacific SWW, and lack thereof in other basins, indicate that orbital-scale changes of the SWW were not zonally homogeneous across the Southern Hemisphere, in contrast to the hemispherewide shifts of the SWW suggested for glacial terminations. Finally, the strengthening of the jet is unique to the South Pacific realm and might have affected winter-controlled changes in the mixed layer depth, the formation of intermediate water, and the buildup of sea-ice around Antarctica, with implications for the global overturning circulation and the oceanic storage of atmospheric CO 2 .

54 ENVIRONMENTAL SCIENCES↗

Collisionality driven turbulent particle transport changes in DIII-D H-mode plasmas

The results of the experimental dimensionless scan in this paper confirm that there is an increase in density peaking towards lower collisionality and that this can be partly linked to a shift in the turbulence regime from ITG towards TEM. However at the lowest collisionality, the changes in turbulence and transport are much more pronounced than expected from direct collisionality effect on the turbulence. In this paper, the collisionality, ν * is varied by a factor 5, while keeping ρ * , q , β , M , fixed. Additionally, a 3 Hz gas puff modulation is applied to modulate the electron density profile and extract the perturbed transport coefficients using two diagnostics. The transport analysis shows that the increase in density peaking at low ν * is linked to an increase in the inward particle pinch and not an increase in core fueling. These observations are not only in agreement with prior modeling scans of how turbulence changes as a function of collisionality and its impact upon the particle fluxes, but also with the multi-machine database (Fable E. et al 2010 Plasma Phys. Control. Fusion 52 015007) (Angioni C. et al 2003 Phys. Rev. Lett. 90 205003). The changes in turbulence across the collisionality scan were captured at large scale by the BES and at smaller scale by the DBS. A comparison with gradient-driven GENE simulations showed similar trends at both scales. Moreover, the changes observed in overall transport are in agreement with gradient-driven TGLF particle flux simulations. This indicates that TGLF/GENE when given the gradients as input, are able to reproduce the experimentally observed turbulence changes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Thermal Optimization of a Silicon Carbide, Half-Bridge Power Module

This project describes the modeling process to design the packaging and heat exchanger for a half-bridge wide-bandgap (WBG) power semiconductor module. The module uses two silicon carbide, metal-oxide-semiconductor field-effect transistor (MOSFET) devices per switch position that are soldered to an aluminum nitride, direct-bond copper (DBC) substrate. A baseplate cooling configuration (e.g., no thermal grease) is used along with a water-ethylene glycol, jet-impingement-style heat exchanger. The heat exchanger was designed to be fabricated using prototyping equipment from the National Renewable Energy Laboratory, complies with automotive standards (for minimal channel sizes, flow rates, and coolant), and considers reliability aspects (i.e., erosion/corrosion). Device-scale computational fluid dynamics (CFD) is used first to design the slot jet impingement cooling configuration and compute the effective heat transfer coefficient (HTC) of the concept. The computed HTCs are then used as boundary conditions for a finite element study to optimize the package geometry (e.g., device layout and baseplate thickness) to minimize thermal resistance and minimize temperature variation between the module's four devices. Finally, a fluid manifold is designed to generate the slot jets and cool the devices. Module-scale CFD predicts a relatively low junction-to-fluid thermal resistance of 16.7 mm2 K/W, a 1.4 degrees C temperature variation between devices, and a total pressure drop of 5,860 Pa (0.85 psi) for the design. The thermal resistance of the module design is about 67% lower than the 2015 BMW i3 power electronics/modules thermal resistance.

DIRECT ENERGY CONVERSION↗

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression. Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to previous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding. Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

AthenaK: A Performance-portable Version of the Athena++ Adaptive Mesh Refinement Framework

We describe AthenaK: a new implementation of the Athena++ block-based adaptive mesh refinement framework using the Kokkos programming model. Finite volume methods for Newtonian, special relativistic, and general relativistic (GR) hydrodynamics and magnetohydrodynamics (MHD), and GR-radiation hydrodynamics and MHD, as well as a module for evolving Lagrangian tracer or charged test particles (e.g., cosmic rays) are implemented using the framework. In two companion papers, we describe (1) a new solver for the Einstein equations based on the Z4c formalism, and (2) a GRMHD solver in dynamical spacetimes also implemented using the framework, enabling new applications in numerical relativity. By adopting Kokkos, the code can be run on virtually any hardware, including CPUs, GPUs from multiple vendors, and emerging Advanced RISC Machine processors. AthenaK shows excellent performance and weak scaling, achieving over 1 billion cell updates per second for hydrodynamics in three dimensions on a single NVIDIA Grace Hopper processor. It does this with a typical parallel efficiency of 80% on 65,536 AMD GPUs on the OLCF Frontier system. Such performance portability enables AthenaK to leverage modern exascale computing systems for challenging applications in astrophysical fluid dynamics, numerical relativity, and multimessenger astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗

Mesoscale Convective Systems Modulated by Convectively Coupled Equatorial Waves

Mesoscale convective systems (MCSs) produce over 50% of tropical precipitation and account for the majority of extreme rainfall and flooding events. MCSs are considered the building blocks of larger-scale convectively coupled equatorial waves (CCEWs). While CCEWs can provide favorable environments for convection, how CCEWs can systematically impact organized convection and thereby MCS characteristics is less clear. We examine this question by analyzing a global MCS tracking data set. During the active phase of CCEWs, MCS frequency increases and MCSs rain harder, produce more lifetime total rain, and grow larger in size. The probability of extreme MCSs also elevates. These changes are most pronounced when MCSs are associated with Kelvin waves and tropical depression-type waves while less so with the Madden-Julian Oscillation. Furthermore, these results can be benchmarks to improve model representation of MCS interactions with large-scale circulations and can be leveraged for operational forecasts of high-impact MCSs at extended lead times.

54 ENVIRONMENTAL SCIENCES↗

Nonparametric Multiparticle Set Methods for Interpreting Environmental Samples

Collection and analysis of environmental samples is commonly used by a range of stakeholders in nuclear safeguards and security contexts. While the ubiquity of samples and their transport in the environment allow regular collection, developing and demonstrating methods for analyzing these samples is difficult. In this work, an environmental sample consists of a set of one or more individual particles. Recent advances in reactor simulation have allowed us to generate data that are more representative of real-world environmental samples, enabling statistically defensible method development and testing. The most notable of these advances is a drastic increase in the number of material depletion regions, which allows our simulations to capture the variation in isotopic composition seen at length scales consistent with environmental samples. Traditional approaches for handling multiparticle samples treat each particle in the sample individually, estimating the quantity of interest (e.g., core-average burnup) resulting from measurement and analysis of signatures (e.g., nuclide assays) from each individual particle. Individual estimates are then averaged to generate a single estimate of the quantity of interest over the entire sample. In this presentation, we introduce two novel approaches for interpreting environmental samples that comprise of multiple particles: (1) the Quantile-Quantile Comparator, which uses a multivariate generalization of quantile-quantile plots for comparing unknown statistical distributions, and (2) the Set Transformer, an attention-based neural network module designed to model interactions among elements (particles) in the input set (sample). Statistically representative sampling cannot be guaranteed as samples are passively collected and are beholden to what particles are available in the environment. These new analysis methods for set-input problems are expected to be more robust than traditional approaches to issues of sampling bias where particles are not uniformly distributed throughout regions of interest, as well as generally outperform traditional approaches by jointly considering all elements in the set. We will present results comparing the performance of traditional single particle approaches and the novel Quantile-Quantile Comparator and Set Transformer for interpretation of simulated environmental samples.

Phathanapirom, Birdy↗

Environmental Conditions Affecting Global Mesoscale Convective System Occurrence

Abstract The ERA5 environments of mesoscale convective systems (MCSs), tracked from satellite observations, are assessed over a 20-yr period. The use of a large set of MCS tracks allows us to robustly test the sensitivity of the results to factors such as region, latitude, and diurnal cycle. We aim to provide novel information on environments of observed MCSs for assessments of global atmospheric models and to improve their ability to simulate MCSs. Statistical analysis of all tracked MCSs is performed in two complementary ways. First, we investigate the environments when an MCS has occurred at different spatial scales before and after MCS formation. Several environmental variables are found to show marked changes before MCS initiation, particularly over land. The vertically integrated moisture flux convergence shows a robust signal across different regions and when considering MCS initiation diurnal cycle. We also found spatial scale dependence of the environments between 200 and 500 km, providing new evidence of a natural length scale for use with MCS parameterization. In the second analysis, the likelihood of MCS occurrence for given environmental conditions is evaluated, by considering all environments and determining the probability of being in an MCS core or shield region. These are compared to analogous non-MCS environments, allowing discrimination between conditions suitable for MCS and non-MCS occurrence. Three environmental variables are found to be useful predictors of MCS occurrence: total column water vapor, midlevel relative humidity, and total column moisture flux convergence. Such relations could be used as trigger conditions for the parameterization of MCSs, thereby strengthening the dependence of the MCS scheme on the environment. Significance Statement Large storm systems called mesoscale convective systems form across Earth. These are collections of thunderstorms, with associated high-level clouds that produce substantial, lighter rainfall and modulate Earth’s energy balance. They produce hazardous weather conditions, such as floods and high winds, and are responsible for a high percentage of rainfall in many regions globally. We investigate the environmental conditions under which they form, so that we can understand the spatial extent of the environment which is important for their formation, and also where and when the effects of these storms might be felt. The novel information generated here should help improve the representation of these storms in weather and climate models, improving the prediction of rainfall, thunderclouds, and high-level clouds.

54 ENVIRONMENTAL SCIENCES↗

Atomic Origin of the Autocatalytic Reduction of Monoclinic CuO in a Hydrogen Atmosphere

Reducibility is key for the use of bulk metal oxides in chemical transformation involving redox reactions but probing microscopic processes of oxide reduction is challenging. This is because the insulating nature of bulk oxides restricts ion and electron spectroscopic measurements of oxide surfaces. Herein, using a combination of environmental transmission electron microscopy and atomistic modeling, we report direct in-situ atomic-scale observations of the surface and subsurface dynamics and show that the hydrogen induced CuO reduction occurs via the surface decay of Cu-O/Cu bilayer atomic steps, formation of partially reduced CuO superstructure by the self-ordering of O vacancies in the subsurface, and collapse of Cu-O layers in the bulk. In this work, all these substeps can be traced back to the progressively increased concentration and activity of O vacancies in the surface and subsurface of the oxide, thereby leading to the self-accelerated oxide reduction. These results demonstrate the microscopic details that may have broader applicability in modulating various redox processes.

36 MATERIALS SCIENCE↗

Resiliency of Distribution Systems Incorporating Asynchronous Information for System Restoration

Resiliency of distribution systems under extreme operating conditions is critical, especially when the utility is not available. With the large-scale deployment of distributed resources, it becomes possible to restore critical loads with local non-utility resources. Distribution system operators (DSOs) need to determine the critical loads to be restored, considering limited resources and distribution facilities. Several studies on resiliency have been conducted for the restoration of distribution systems. However, the inherent asynchronous characteristic on the information availability has not been incorporated. With incomplete and asynchronous information, decisions may be made that result in underutilization of generation resources. In this paper, a new distribution system restoration approach is proposed, considering uncertain devices and associated asynchronous information. It uses a two-module architecture that efficiently optimizes restoration actions using a binary linear programming model and evaluates their feasibility with unbalanced optimal power flow. Networked microgrids are included in the model. The IEEE 123-node test feeder is used for validation. Results show that asynchronous messages may affect the restoration actions significantly and the impacts can be mitigated by the proposed decision support tool for the DSOs.

Bedoya, Juan C.↗

DRDMannTurb: A Python package for scalable, data-driven synthetic turbulence

Synthetic turbulence models (STMs) are used in wind engineering to generate realistic flow fields and are employed as inputs to industrial wind simulations. Examples include prescribing inlet conditions in large eddy simulations that model loads on wind turbines and tall buildings. We are interested in STMs capable of generating fluctuations based on prescribed second-moment statistics since such models can simulate environmental conditions that closely resemble on-site observations. To this end, the widely used Mann model (see Mann, 1994, 1998) is the inspiration for DRDMannTurb. The Mann model is described by three physical parameters: a magnitude parameter influencing the global variance of the wind field and corresponding to the Kolmogorov constant multiplied by the rate of viscous dissipation of the turbulent kinetic energy to the two-thirds, αϵ 2/3 , a turbulence length scale parameter L, and a nondimensional parameter Γ related to the lifetime of the eddies. A number of studies, as well as international standards (e.g., those by the International Electrotechnical Commission (IEC)), include recommended values for these three parameters with the goal of standardizing wind simulations according to observed energy spectra. Yet, having only three parameters, the Mann model faces limitations in accurately representing the diversity of observable spectra. This Python package enables users to extend the Mann model and more accurately fit field measurements through flexible neural network models of the eddy lifetime function. Following Keith et al. (2021), we refer to this class of models as Deep Rapid Distortion (DRD) models. DRDMannTurb also includes a general module implementing an efficient method for synthetic turbulence generation based on a domain decomposition technique. This technique is also described in Keith et al. (2021).

17 WIND ENERGY↗

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - Simulated Marine Hydrokinetic Tidal Turbine

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset is part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with other energy technologies. This dataset contains inputs and outputs from simulations of a floating marine hydrokinetic turbine over approximately half a tidal cycle (~6.6 hours). Inflow conditions were derived from field measurements in Alaska’s Cook Inlet and represent a tidal environment in which the current speed ramps from near 0 m/s to a peak of 3 m/s and back. The original acoustic doppler current profiler dataset is publicly available on the Marine and Hydrokinetic Data Repository. In a full tidal cycle, the flow reverses and the rotor would reorient; this reversal was not modeled. In the Cook Inlet campaign , turbulence intensity was similar in both directions. Two inflow cases are included. In the first case, labeled “raw” in the files, the measured current time series was used directly in the InflowWind module of OpenFAST. Speed and direction were applied as a function of time and elevation, uniformly in the horizontal direction. With full spatial coherence, this approach captures high turbulent variability and results in pronounced power fluctuations, so it is considered a conservative, near-worst-case representation of loading. In the second case, labeled “average” in the files, a 30-minute moving average was applied to extract the slowly varying mean speed. The residual fluctuations about this mean were used to generate spatially varying, full-field turbulence inputs with TurbSim, giving a more physically realistic representation of the inflow across the rotor disk. Two random realizations were used to produce distinct inflow conditions for two OpenFAST simulations representing a two-turbine array. The same turbulence intensity is applied across the full time series, producing larger fluctuations at the start and end, where the mean speed is low. The second case is the more appropriate framework for performance and power assessment but overpredicts turbulence at lower flow speeds and underpredicts it at higher speeds. As the floating platform moves and the rotor changes its x-position, Taylor’s frozen turbulence hypothesis used by InflowWind assumes a constant rather than a time-varying mean velocity, introducing some inaccuracy in the velocity plane sampling. The turbine modeled is the 500-kW Reference Model 1, a horizontal-axis two-bladed hydrokinetic turbine on a four-column floating semisubmersible substructure . Simulations were performed using OpenFAST v4.1 with the Reference Open Source Controller (ROSCO) v2.10. All input files required to reproduce the simulations are included. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel . This unit supports up to 2.5 MW, but NLR has only a single 1.25-MW stack. The datasets report hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. The system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operating current of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The simulated tidal turbine time series data was translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz. Each zip file represents a single tidal electrolysis experiment and is named: {technology}_{inflow method}_{number of 500 kW tidal turbines connected} For instance, “tidal-500kW-RM1_average_2.zip” is a 6-hour experiment using the 500-kW tidal reference model, scaled by 2x (1-MW) to better match the electrolyzer maximum of 1.25MW, fed with the 30-minute moving average current case. Each zip folder contains the following files: A .csv file of raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. A .csv file combines all tidal profiles as "combined_tidal_experiments.csv." A separate experiment, “characterization_200.zip,” shows the MC250 electrolyzer steady-state response with 30-minute load steps over 5 hours and is accessible with this entry.

08 HYDROGEN↗

Recent Tropical Cyclone Outer Size Increases in the Western North Atlantic

The outer size of a tropical cyclone (TC) plays a pivotal role in its impact through a modulation of wind duration, rainfall extent and storm surge. While global and basin scale trends in TC size have been examined previously, whether there have been regional changes over time remains unclear. Here, using a suite of observations and reanalyses, we detect an increasing TC outer size over the western North Atlantic during 1979–2022. Over the western subtropical North Atlantic where the largest changes are found, the area-averaged increase in the radius of 17 ms -1 winds is about 7.5% over this period. Analysis of the large-scale environment reveals that the air-sea thermodynamic state has become more favorable for storm intensification, and thereby expansion, over that region. Further, numerical model simulations link changes in the environment with those in storm size, and suggest a combination of natural variability and external forcing in driving them.

Balaguru, Karthik [Pacific Northwest National Labo↗

Utilizing commercial heating, ventilating, and air conditioning systems to provide grid services: A review

The modern power grid faces multiple challenges due to an increase in the adoption of renewable generation, such as dynamically balancing supply and demand at different time scales. Demand side management in buildings plays a vital role in achieving this balance because buildings can provide grid services through a variety of building assets. However, the development of grid-interactive, efficient buildings is still in its infancy, and a systematic and holistic understanding of grid service delivery strategies in terms of energy efficiency, load shifting, load shedding and load modulating is still limited. This paper is a comprehensive review of the development and application of building-level control strategies for utilizing heating, ventilating, and air conditioning systems to provide grid services. These strategies have been investigated through numerical and experimental studies. Control algorithms, such as heuristic rule-based control and model-based control, have been used to enable the automatic control delivery of grid services. The advantages and disadvantages of the strategies are summarized and discussed. Finally, research trends are also identified, which include considering predicted mean vote-based and occupant-based thermal comfort, modeling of occupant behavior, integrating power grid operations with building control, and combining different demand flexibility modes in the control design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A novel sub-pilot-scale direct-contact ultrasonic dehydration technology for sustainable production of distillers dried grains (DDG)

DDG is a major source of protein, calcium, phosphorus, and sulfur is arguably the most important byproduct of the bioethanol industry with increasing demand over the past few years. Reducing energy consumption in the DDG production process and energy recovery from DDG is vital for sustainable bioethanol productions. In this paper, a novel direct-contact multi-frequency, multimode, and modulated (MMM) ultrasonic dryer (US) was developed for the first time and has been applied in dehydration of wet distillers' grain (WDG). Ultrasonic drying (US) was combined with a convective airflow (HA) at different temperatures of 25 (room temperature), 50 and 70 °C to evaluate the impact of US, HA, and US + HA on drying kinetics, activation energy, chemical compositions, microstructure, and color of DDG. Semi-empirical kinetic models were developed and evaluating drying performances showed that the application of ultrasound significantly enhanced the drying rate and decreased the drying time (by 46%), especially at low drying temperatures. The activation energy for moisture removal in the presence of ultrasound was about 50% of that without ultrasound. The final dried distillers' grains product processed by ultrasonic drying had a brighter color, a higher available protein, a higher digestible protein (the lowest acid detergent insoluble crude protein), and a better surface profile with no compromise on minerals and fiber contents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Contrast and Predictability of Island‐Scale El Niño Influences on Hawaii Wave Climate

Abstract The El Niño‐Southern Oscillation (ENSO) influences ocean wave activity across the Pacific, but its effects on island shores are modulated by local weather and selective sheltering of multi‐modal seas. Utilizing 41 years of high‐resolution wave hindcasts, we decipher the season‐ and locality‐dependent connections between ENSO and wave patterns around the Hawaiian Islands. The north and west‐facing shores, exposed to energetic northwest swells during boreal winters, experience the most pronounced ENSO‐related variability, with increased high‐surf activity during El Niño years. While the year‐round trade wind waves exhibit moderate correlation with ENSO, the basin‐wide climate influence is masked by locally accelerated trade winds in channels and around large headlands. The remarkable global‐to‐local pathway through the high‐resolution hindcast enables development of an ENSO‐based semi‐empirical wave model to statistically describe and predict severe wave conditions on vulnerable shores with potential application in coastal risk management and hazard mitigation for Pacific Islands and beyond.

Zhao, Sen [Department of Atmospheric Sciences Scho↗

Probing the Active Sites of MoS 2 Based Hydrotreating Catalysts Using Modulation Excitation Spectroscopy

The reactive surface sites of MoS 2 hydrotreating catalysts (unpromoted as well as Co- and Ni-promoted) supported on MgAl 2 O 4 spinel were investigated with respect to the substitution of sulfur by oxygen using in situ XAS coupled with modulation excitation spectroscopy (MES). Specifically, MES experiments were carried out by periodically cycling between a H 2 O and H 2 S containing hydrogen gas mixture at 400 °C. Due to the low fraction of S–O exchange, conventional XANES and EXAFS data hardly showed any changes when these catalysts were exposed to increasing ratios of H 2 O to H 2 S in an H 2 atmosphere. XANES and EXAFS data extracted at the Mo K-edge by MES analysis showed that for approximately 1% of the Mo atoms, sulfur atoms are replaced by oxygen atoms when exposed to H 2 O, causing partial oxidation of these active sites. The reaction is reversible and Mo returns to its initial sulfide phase when H 2 O is removed and H 2 S is supplied in the feed. In the case of Co- and Ni-promoted catalysts, the magnitude of S–O exchange was found to be reduced, indicating the beneficial effect of promotion. MES at the Ni K-edge showed that Ni was oxidized during H 2 O exposure, which in turn delayed the Mo oxidation in the Ni-promoted catalyst. The structures of these catalysts under S–O exchange were modeled using density functional theory (DFT) calculations, showing that the edge atoms are affected strongly. For all three catalysts, OH substitution is more favorable, while O substitution could be possible at high H 2 O pressure for unpromoted MoS 2 . Mo K-edge XANES spectra calculated using these simulated structures support the results obtained from the MES experiments. In conclusion, the presented approach using MES in combination with XAS and supported by DFT can be extended in general to catalysts under operando conditions and is thus a useful tool for determination of the active site on an atomic-scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗