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At least 379 records · Page 21

Hydropower potential derived from streamflow extremes for Alaska, USA

Alaska is an expansive region known for its abundant natural resources, including thousands of miles of streams and rivers. These rivers represent potential opportunities for future hydropower development that could provide reliable energy supply for local communities. There is limited long-term high temporal resolution streamflow data available for the region, making data-driven estimates of potential hydropower and its variability across the state challenging. This study provides a novel data-driven approach for hydropower capacity estimation across Alaska. We use supervised machine learning to develop a relationship between the daily and peak flow duration curves in order to augment the size of our dataset from 44 sites to 67 sites. We perform a stochastic hydropower estimation across the 67 sites and identify approximately 1000 MW of total potential hydropower capacity distributed across these sites. Our study provides the first step towards more comprehensive hydropower estimation for this critical region, highlighting the need for future work integrating high-resolution spatial data, community needs, and economic constraints in estimates of potential hydropower development in Alaska.

Hydropower↗

Rapid Electrochemical Methane Functionalization Involves Pd–Pd Bonded Intermediates

High-valent Pd complexes are potent agents for the oxidative functionalization of inert C-H bonds, and it was previously shown that rapid electrocatalytic methane monofunctionalization could be achieved by electro-oxidation of Pd II to a critical dinuclear Pd III intermediate in concentrated or fuming sulfuric acid. However, the structure of this highly reactive, unisolable intermediate, as well as the structural basis for its mechanism of electrochemical formation, remained elusive. Herein, we use X-ray absorption and Raman spectroscopies to assemble a structural model of the potent methane-activating intermediate as a Pd III dimer with a Pd-Pd bond and a 5-fold O atom coordination by H x SO 4 (x-2) ligands at each Pd center. We further use EPR spectroscopy to identify a mixed-valent M-M bonded Pd 2 II,III species as a key intermediate during the Pd II -to-Pd III 2 oxidation. Combining EPR and electrochemical data, we quantify the free energy of Pd dimerization as <-4.5 kcal/mol for Pd 2 II,III and <-9.1 kcal/mol for Pd III 2 . The structural and thermochemical data suggest that the aggregate effect of metal-metal and axial metal-ligand bond formation drives the critical Pd dimerization reaction in between electrochemical oxidation steps. This work establishes a structural basis for the facile electrochemical oxidation of Pd II to a M-M bonded Pd III dimer and provides a foundation for understanding its rapid methane functionalization reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of Dynamic Force Coefficients for an Additively Manufactured Hermetic Squeeze Film Bearing Support Damper Utilizing a Pass-Through Channel

Abstract The following paper presents breakthrough experimental results for a new hermetic squeeze film damper (HSFD) concept that is integrally designed within an externally pressurized tilting-pad radial gas bearing support. The flexibly damped gas bearing module was designed for a 7.2″ (183 mm) diameter shaft and fabricated using direct metal laser melting (DMLM); also known as additive manufacturing. The bearing and HSFD were sized based on ongoing studies for oil-free supercritical carbon dioxide (sCO2) power turbines in the 8.5 MW–10 MW power range. The development of the new damper concept was motivated by past dynamic testing on HSFD, which generated frequency-dependent stiffness and damping force coefficients. In efforts to eliminate the frequency dependency, a new HSFD architecture was conceived that adds accumulator volumes and a pass-through channel to previously conceived HSFD flow network designs. The other motivation for the work is the need to develop a cost-effective and reliable oil-free bearing technology that is scalable to large power turbomachinery applications. There were several objectives for the following work. The first objective was to successfully design and fabricate a single piece bearing-damper using additive manufacturing, while dimensionally controlling critical design features. The paper discusses the manufacturing steps and shows cut-ups that reveal adequate clearance control capability with internal damper clearances. The second objective was to perform experimental testing with the new HSFD design in efforts to extract stiffness and damping coefficients for excitation frequencies within 20–160 Hz and peak vibration amplitudes between 0.25 mils (6.35 microns) to 1 mil (25.4 microns). The test results for a single HSFD bearing module indicated that the design modifications to the HSFD architecture were successful in eliminating nearly all the frequency dependencies for the stiffness force coefficient. The dynamic tests yielded a stiffness coefficient that varied between 112 klb/in. (19.6 MN/m) and 96 klb/in. (16.8 MN/m). The damping force coefficient however, exhibited relatively more variation with frequency with values residing between 175 lb-s/in. (31 kN-s/m) to 214 lb-s/in. (37 kN-s/m). Finally, the paper advances a three-dimensional fluid-structure interaction (FSI) model using transient finite element analysis (FEA) coupled to a computational fluid dynamics (CFD) model. The FSI analysis performed between 20 Hz and 80 Hz was used to predict the stiffness and damping of the HSFD using a quarter-section model of the damper. The FSI analysis was able to support test results by showing only a 6–7.4% change in the magnitude of force coefficients. Stiffness predictions agree reasonably well with experiments whereas damping is underpredicted.

Engineering↗

Sorption of rare-earth elements onto a ligand-associated media for pH-dependent extraction and recovery of critical materials

Toward recovering rare-earth elements, we prepared a solid-phase media that binds and elutes metals for extraction and enrichment. We report the synthesis and methodology for a solid-phase media that exhibits pH-dependent binding of aqueous rare-earth elements. The media shows pH-dependent binding of Nd III and retains efficiency over at least six cycles of binding and elution. Mixed solutions of rare-earth elements demonstrated a preference for mid and heavy rare-earth elements based on thermodynamic binding preferences of the ligand, and selectivity for rare-earth elements over iron and aluminum were observed with coal fly ash leachate. In conclusion, we expect this new recovery method to be a significant step towards aqueous-based extraction and enrichment of critically important rare-earth elements.

01 COAL, LIGNITE, AND PEAT↗

Uncertainty Propagation within Chained Models for Machine Learning Reconstruction of Neutrino-LAr Interactions

Sequential or chained models are increasingly prevalent in machine learning for scientific applications, due to their flexibility and ease of development. Chained models are particularly useful when a task is separable into distinct steps with a hierarchy of meaningful intermediate representations. In reliability-critical tasks, it is important to quantify the confidence of model inferences. However, chained models pose an additional challenge for uncertainty quantification, especially when input uncertainties need to be propagated. In such cases, a fully uncertainty-aware chain of models is required, where each step accepts a probability distribution over the input space, and produces a probability distribution over the output space. In this work, we present a case study for adapting a single model within an existing chain, designed for reconstruction within neutrino-Argon interactions, developed for neutrino oscillation experiments such as MicroBooNE, ICARUS, and the future DUNE experiment. We test the performance of an input uncertainty-enabled model against an uncertainty-blinded model using a method for generating synthetic noise. By comparing these two, we assess the increase in inference quality achieved by exposing models to upstream uncertainty estimates.

97 MATHEMATICS AND COMPUTING↗

From MAST-U to STEP: Power exhaust control challenges and opportunities

This work explores the challenges and opportunities for power exhaust control in STEP, informed by dedicated MAST-U experiments. The STEP system primarily relies on hydrogenic and argon gas injection into the divertors, compensating for transients originating in the plasma core. Fast transients (>10 Hz) that evolve too quickly for actuators to compensate must be absorbed passively; the enhanced transient buffering of the foreseen long-legged divertor provides a clear advantage over conventional geometries, as demonstrated in the MAST-U Super-X divertor. Experiments further indicate that STEP’s tight divertor baffling enables near-independent control of the upper and lower divertors. The most challenging transients are expected from power-sharing fluctuations, as MAST-U experiments observed extremely fast dynamics. Fluctuations from core pellet fuelling remain relatively benign due to the small pellet size according to simulations. Exhaust control in a reactor like STEP requires an integrated approach befitting its machine-critical nature. A predictive control element, integrated with core plasma control, allows pre-emptive preparation of the divertor for incoming transients. An observer-based diagnostic approach is foreseen to monitor the divertor in the challenging reactor environment, supported by an extended diagnostic set in the non-nuclear phase to validate the required dynamic models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reactive burn model calibration using high-throughput initiation experiments at sub-millimeter length scales

We report a first-of-its-kind model calibration was performed using Sandia National Laboratories’ high-throughput initiation (HTI) experiment for two types of vapor-deposited explosive films consisting of hexanitrostilbene (HNS) or pentaerythritol tetranitrate (PETN). These films exhibit prompt initiation, and they reach steady detonation at sub-millimeter length scales. Following prior work on HNS, we test the hypothesis of approximating these explosive films as fine-grained homogeneous solids with simple Arrhenius kinetics burn models. The model calibration process is described herein using a single-step as well as a two-step Arrhenius rate law, and it consists of systematic parameter sampling leading to a reduction in the model degrees of freedom. Multiple local minima are observed; results are given for seven different optimized parameter sets. Each model set is further evaluated in a two-dimensional simulation of the critical failure thickness for a sustained detonation. Overall, the two-step Arrhenius kinetics model captures the observed behavior for HNS; however, neither model produces a good fit to the PETN data. We hypothesize that the HTI results for PETN correspond to a heterogeneous response, owing to the smaller reaction zone of PETN compared to HNS (i.e., it does not homogenize the fine-grained hot spots as well). Future work should consider using the ignition and growth model for PETN, as well as other reactive burn models such as xHVRB, AWSD, PiSURF, and CREST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An interoperable implementation of collective‐variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. Here, in this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computing the shape gradient of stellarator coil complexity with respect to the plasma boundary

Coil complexity is a critical consideration in stellarator design. The traditional two-step optimization approach, in which the plasma boundary is optimized for physics properties and the coils are subsequently optimized to be consistent with this boundary, can result in plasma shapes which cannot be produced with sufficiently simple coils. To address this challenge, we propose a method to incorporate considerations of coil complexity in the optimization of the plasma boundary. Coil complexity metrics are computed from the current potential solution obtained with the REGCOIL code (Landreman, Nucl. Fusion , vol. 57, 2017, 046003). While such metrics have previously been included in derivative-free fixed-boundary optimization (Drevlak et al. , Nucl. Fusion , vol. 59, 2018, 016010), we compute the local sensitivity of these metrics with respect to perturbations of the plasma boundary using the shape gradient (Landreman & Paul, Nucl. Fusion , vol. 58, 2018, 076023). We extend REGCOIL to compute derivatives of these metrics with respect to parameters describing the plasma boundary. In keeping with previous research on winding surface optimization (Paul et al. , Nucl. Fusion , vol. 58, 2018, 076015), the shape derivatives are computed with a discrete adjoint method. In contrast with the previous work, derivatives are computed with respect to the plasma surface parameters rather than the winding surface parameters. To further reduce the resolution required to compute the shape gradient, we present a more efficient representation of the plasma surface which uses a single Fourier series to describe the radial distance from a coordinate axis and a spectrally condensed poloidal angle. This representation is advantageous over the standard cylindrical representation used in the VMEC code (Hirshman & Whitson, Phys. Fluids , vol. 26, 1983, pp. 3553–3568), as it provides a uniquely defined poloidal angle, eliminating a null space in the optimization of the plasma surface. In comparison with previous spectral condensation methods (Hirshman & Breslau, Phys. Plasmas , vol. 5, 1998, p. 2664), the modified poloidal angle is obtained algebraically rather than through the solution of a nonlinear optimization problem. The resulting shape gradient highlights features of the plasma boundary that are consistent with simple coils and can be used to couple coil and fixed-boundary optimization.

Physics↗

A dendritic strontium river isoscape for fisheries applications in the Sacramento River basin, California, USA

Objective Understanding the origins and movements of fish is fundamental to effective conservation and fisheries management. Strontium isotope ratios ( 87 Sr/ 86 Sr) in otoliths provide a powerful tracer of natal origin and migratory pathways. However, existing 87 Sr/ 86 Sr isoscapes for the Sacramento River basin, an ecosystem that supports ecologically and economically important salmon populations, rely on discrete classification approaches that overlook unsampled habitats and do not incorporate spatial uncertainty. Our objective was to develop a continuous, network-explicit 87 Sr/ 86 Sr isoscape with quantified uncertainty to fill in data gaps and enable probabilistic assignments of fish origin and movement. Methods We used river water 87 Sr/ 86 Sr data from 106 sites (1997–2021) to develop spatial stream network models that use dendritic connectivity and watershed characteristics (lithology, bedrock age, and land cover) to predict river water 87 Sr/ 86 Sr throughout the basin. Models were fitted using maximum and restricted likelihood and were evaluated via Akaike’s information criterion and leave-one-out cross validation. We produced both historical (pre-dam) and present-day (below-dam) isoscapes, delineated uncertainty-informed isotopic ranges using k -means clustering, and applied a proof-of-concept Bayesian assignment to estimate natal origins and early rearing habitats for two endangered winter-run Chinook Salmon Oncorhynchus tshawytscha. Results Cross validation indicated strong performance of the 87 Sr/ 86 Sr model (leave-one-out cross validation: R 2 = 0.91; root mean square error = 0.0005). Uncertainty-informed clustering identified 19 isotopic “suites” (reaches with indistinguishable 87 Sr/ 86 Sr values) in present-day anadromous habitats and 25 suites in the historical network. Example natal and early rearing assignments included predictions that challenged expectations for juvenile salmon migration based on predicted river 87 Sr/ 86 Sr compositions. Conclusions This study developed a continuous, network-explicit 87 Sr/ 86 Sr isoscape that integrates existing river data to predict 87 Sr/ 86 Sr in unsampled reaches and the likely achievable range and resolution of otolith-based origin and life history inference. The resulting river isoscape provides a valuable tool to predict salmon movements and identify habitats supporting their survival and growth that otherwise might remain undetected. Coupling these predictions with complementary approaches that ground-truth juvenile presence (e.g., targeted fish surveys) represents an important step toward science-informed restoration and management of critical habitats throughout the Sacramento River basin.

Environmental sciences↗

Reducing nighttime light exposure in the urban environment to benefit human health and society

Nocturnal light pollution can have profound effects on humans and other organisms. Recent research indicates that nighttime outdoor lighting is increasing rapidly. Evidence from controlled laboratory studies demonstrates that nocturnal light exposure can strain the visual system, disrupt circadian physiology, suppress melatonin secretion, and impair sleep. There is a growing body of work pointing to adverse effects of outdoor lighting on human health, including the risk of chronic diseases, but this knowledge is in a more nascent stage. In this Review, we synthesize recent research on the context-specific factors and physiology relevant to nocturnal light exposure in relation to human health and society, identify critical areas for future research, and highlight recent policy steps and recommendations for mitigating light pollution in the urban environment.

Science & Technology - Other Topics↗

Quantifying Nitrogen Bioextraction by Seaweed Farms – A Real-time Modeling-Monitoring Case Study in Hood Canal, WA

Anthropogenic nitrogen input is the leading cause of increasing marine eutrophication. Cultivating seaweeds at large scales may provide a viable solution for mitigating eutrophication especially when nitrogen extraction is achieved as an added environmental benefit of biofuel and food production. As the first step to promoting and implementing this solution, it is critical to quantify and assess the effectiveness of nitrogen removal by existing seaweed farms. Pacific Northwest National Laboratory and Hood Canal Mariculture Inc. conducted a case study by applying a coupled modeling-monitoring approach to quantify nitrogen bioextraction by a one-hectare commercial sugar kelp farm in Hood Canal, WA. Through this two-year effort, the project team conducted intensive field monitoring of water quality parameters at the farm site and subsequent laboratory analysis. Meanwhile, the team applied a coupled hydrodynamic-macroalgal growth model to simulate kelp growth and nitrogen bioextraction over the two kelp growing seasons. The model results showed an overall good comparison with field monitoring data and showed the effectiveness of nitrogen removal by kelp farms. The established modeling-monitoring approach can also be transferable for supporting broader research activities in macroalgal farming and eutrophication mitigation.

09 BIOMASS FUELS↗

Proteome-wide characterization of PTMs reveals host cell responses to viral infection and identifies putative antiviral drug targets

Post-translational modifications (PTMs) are biochemical modifications that can significantly alter protein structure, function, stability, localization, and interactions with other molecules, thereby activating or inactivating intracellular processes. A growing body of research has begun to highlight the role of PTMs, including phosphorylation, ubiquitination, acetylation, and redox modifications, during virus-host interactions. Collectively, these PTMs regulate key steps in mounting the host immune response and control critical host pathways required for productive viral replication. This has led to the conception of antiviral therapeutics that focus on controlling host protein PTMs, potentially offering pathogen-agnostic treatment options and revolutionizing our capacity to prevent virus transmission. On the other hand, viruses can hijack the host cellular PTM machinery to modify viral proteins in promoting viral replication and evading immune surveillance. PTM regulation during virus-host interactions is complex and poorly mapped, and the development of effective PTM-targeted antiviral drugs will require a more comprehensive understanding of the cellular pathways essential for virus replication. In this review, we discuss the roles of PTMs in virus infection and how technological advances in mass spectrometry-based proteomics can capture systems-level PTM changes during viral infection. Additionally, we explore how such knowledge is leveraged to identify PTM-targeted candidates for developing antiviral drugs. Looking ahead, studies focusing on the discovery and functional elucidation of PTMs, either on the host or viral proteins, will not only deepen our understanding of molecular pathology but also pave the way for developing better drugs to fight emerging viruses.

Immunology↗

Life-Cycle Inventory of Critical Materials: Nickel, Copper, Titanium, and Rare-Earth Elements

The United States has developed a list of critical minerals/materials whose sustained and reliable supply is pivotal to the robust functioning of critical industrial sectors. A key concern with these minerals is their environmental effects as a function of their production location. This requires material and energy flow details for their processing steps. This report provides a life-cycle inventory (LCI) for producing four critical minerals and/or material systems (nickel, copper, titanium, and rare-earth elements) incorporated in the updated GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model. For these systems, we provide an LCI as a function of production location – domestic (within the United States) and international (geographies from where the US imports these minerals). Our LCI also considers variations in ore grades for nickel and copper. This report also provides an LCI for all intermediate materials used to produce these critical materials.

58 GEOSCIENCES↗

Determining the kinetic rate constants of Fe 3 O 4 -to-Fe and FeO-to-Fe reduction by H 2

Steel production using coal accounts for ~ 8% of global carbon emissions. “Green Steel” is a new grand concept proposed recently to make steel from iron ores using renewable derived “Green Hydrogen” to achieve zero carbon emission. The kinetics and rate-limiting steps of iron ore reduction into iron with H 2 as a reducing agent is critically important to the success of this new technology. While reduction of Fe 2 O 3 into Fe by H 2 follows multiple steps, the past research on this topic mainly deals with the overall averaged kinetics, giving little information on the elemental and rate-limiting steps. In this work, we report a kinetic study specifically design to attain kinetic rate constants of one-step reduction of Fe 3 O 4 -to-Fe and FeO-to-Fe. Guided by thermodynamics, we show first how to create in situ the desirable starting oxide phases, i.e., Fe 3 O 4 and FeO, with precisely controlled the ratio of partial pressures of H 2 O and H 2 . We then show time-dependent raw H 2 O content data collected by a mass spectrometer and the processed reduction data to extract kinetic rate constants. We found that the kinetics of the two one-step reduction reactions follows nicely the Johnson-Mehl-Avrami (JMA) phase transformation model. The one-step reduction mechanisms and activation energy are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rheological characterization of 3D printable geopolymers

This study demonstrates a two-step approach that enables quantification of concrete printability through dynamics mode rheological measurements; I) modeling shearing history during extrusion; II) monitoring the hardening evolution of deposited material by applying a strain smaller than the critical strain. It is shown that the shearing history of the material is removed by imposing a pre-shearing above the critical strain, and zero value yield stress is measured for all specimens. At step II, a linear extrapolation of the green strength development can quantify the static yield stress at the origin, which we used to quantify the material printability. As far as this yield stress surpasses the stress level that exists in the printed structure, the material retains its shape stability. We show the performance of the model on a series of geopolymer mortars with a wide range of rheological properties as a function of material composition, aging, and pre-shearing consequences.

36 MATERIALS SCIENCE↗

Two-Step Thermoresponsive Ultrafiltration Membranes from Polymerization of Lyotropic Liquid Crystals

Here, in this study, we present the fabrication of a two-step thermoresponsive ultrafiltration (UF) membrane through polymerization of a lyotropic liquid crystal (LLC). A mixture of commercially available Pluronic F 127 block copolymer, water (containing ammonium persulfate as the initiator), and polymerizable oil (n-butyl acrylate/ethylene glycol dimethacrylate) is used to create an LLC with a lamellar structure, as characterized by cross-polarized light microscopy and atomic force microscopy. Differential scanning calorimetry is employed to evaluate the thermoresponsive behavior of the polymerized LLC (polyLLC). Two-step thermoresponsiveness (~35 and ~50 °C) of the polyLLC is observed due to the lower critical solution temperature (LCST) of F 127 and melting of the crystalline structure of the polyethylene oxide (PEO) chains of the F 127 surfactant. In the next step, the obtained mesophase is cast on a nonwoven polyester support sheet followed by thermal polymerization. The hydration capacity, water flux, water flux recovery after fouling, and molecular weight cutoff (MWCO) of the obtained membrane are evaluated at different temperatures to examine its thermoresponsiveness. The experimental results reveal that the UF membrane has a reversible thermoresponsive behavior at the LCST and PEO melting of polyLLC. Additionally, the cleaning efficiency of the fouled membrane can be enhanced by using its thermoresponsive behavior, resulting in an extended lifetime of the product. Furthermore, the MWCO of the membrane can be altered with temperature due to the pore size change with temperature stimulus.

36 MATERIALS SCIENCE↗

Kinetic model development for single step ethanol to butene rich olefin process over Cu-Y/Beta catalysts

Here, this study presents the first intrinsic kinetic model for the single-step conversion of ethanol to butene-rich olefins over bifunctional Cu-Y/Beta catalysts, addressing a critical gap in the design and scale-up of Sustainable Aviation Fuel (SAF) processes. The reaction network comprises ten global steps involving dehydrogenation, aldol condensation, hydrogenation, and dehydration reactions, distributed across Cu and rare-earth (Y) active sites. The model incorporates dual-site functionality (Cu and Y site) and explicitly accounts for key intermediates such as crotonaldehyde and butanal. Reaction rates are formulated using Langmuir–Hinshelwood–Hougen–Watson (LHHW) kinetics. Kinetic parameters are extracted by fitting the model to lab-scale packed-bed reactor data across a wide range of temperatures and space velocities, demonstrating strong agreement in ethanol conversion and product selectivity. The reaction kinetics developed in this work provide a foundational basis for constructing reactor models that enable process optimization and scale-up of ethanol-to-jet fuel technologies.

Cu-Y/Beta catalyst↗