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At least 235 records · Page 13

Hydrated Metal and Metal-Nitrate Complexes in Water: Full Lanthanide(III) Series plus Miscellaneous Metal Ions

This is a dataset of hydrated metal complexes and metal–nitrate hydrated complexes intended for public use, reproducibility, and downstream structural analysis. A key feature is coverage across the full lanthanide(III) series (La–Lu), enabling systematic comparisons of coordination motifs and bonding trends across the entire lanthanide sequence. In addition to the lanthanides, the dataset also includes other metal ions such as UO2(VI), Fe(II), and Fe(III). The dataset provides optimized geometries for hydrated and nitrate-containing hydrated complexes, together with representative ab initio molecular dynamics (AIMD) trajectories saved in standard XYZ formats. The accompanying NWChem input decks enable reproduction of the reported calculations and provide a starting point for extending the simulations to related coordination environments. Computationally, DFT calculations employ the B3LYP functional with DFT-D3BJ dispersion corrections and a COSMO continuum solvent model (dielectric constant 78.4) to represent solvation beyond the explicitly treated first hydration shell. AIMD simulations are performed with the NWChem qmd module at 298 K, integrating nuclear motion with the velocity-Verlet algorithm and controlling temperature using a Nosé–Hoover thermostat. Trajectories are approximately 4.8 ps in length and are used primarily to assess short-time stability of candidate coordination motifs, including (for lanthanides) differences between 8- versus 9-water coordination and comparisons between nitrate-bound and nitrate-free hydrated complexes.

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗

The Role of Hydrophobic Nodes in the Dynamics of Class A β-Lactamases

Class A β-lactamases are known for being able to rapidly gain broad spectrum catalytic efficiency against most β-lactamase inhibitor combinations as a result of elusively minor point mutations. The evolution in class A β-lactamases occurs through optimisation of their dynamic phenotypes at different timescales. At long-timescales, certain conformations are more catalytically permissive than others while at the short timescales, fine-grained optimisation of free energy barriers can improve efficiency in ligand processing by the active site. Free energy barriers, which define all coordinated movements, depend on the flexibility of the secondary structural elements. The most highly conserved residues in class A β-lactamases are hydrophobic nodes that stabilize the core. To assess how the stable hydrophobic core is linked to the structural dynamics of the active site, we carried out adaptively sampled molecular dynamics (MD) simulations in four representative class A β-lactamases (KPC-2, SME-1, TEM-1, and SHV-1). Using Markov State Models (MSM) and unsupervised deep learning, we show that the dynamics of the hydrophobic nodes is used as a metastable relay of kinetic information within the core and is coupled with the catalytically permissive conformation of the active site environment. Finally, our results collectively demonstrate that the class A enzymes described here, share several important dynamic similarities and the hydrophobic nodes comprise of an informative set of dynamic variables in representative class A β-lactamases.

59 BASIC BIOLOGICAL SCIENCES↗

Insights on seasonal solifluction processes in warm permafrost Arctic landscape using a dense monitoring approach across adjacent hillslopes

Solifluction processes in the Arctic are highly complex, introducing uncertainties in estimating current and future soil carbon storage and fluxes, and assessment of hillslope and infrastructure stability. This study aims to enhance our understanding of triggers and drivers of soil movement of permafrost-affected hillslopes in the Arctic. To achieve this, we established an extensive soil deformation and temperature sensor network, covering 48 locations across multiple hillslopes within a 1 km² watershed on the Seward Peninsula, AK. We report depth-resolved measurements down to 1.8 m depth for May to September 2022, a period conducive to soil movement due to deepening thaw layers and frequent rain events. Over this period, surface movements of up to 334 mm were recorded. In general, these movements occur close to the thawing front, and are initiated as thawing reaches depths of 0.4 to 0.75 m. The largest movements were observed at the top of the south-east facing slope, where soil temperatures are cold (mean annual soil temperatures averaging -1.13°C) and slopes are steeper than 15°. Our analysis highlights three primary factors influencing movements: slope angle, soil thermal conditions, and thaw depth. The latter two significantly impact the generation of pore water pressures at the thaw–freeze interface. Specifically, soil thermal conditions govern the liquid water content, while thaw depth influences both the height of the water column and, consequently, the pressure at the thawing front. These factors affect soil properties, such as cohesion and internal friction angle, which are crucial determinants of slope stability. This underscores the significance of a precise understanding of subsurface thermal conditions, including spatial and temporal variability in soil temperature and thaw depth, when assessing and predicting slope instabilities. Based on our observations, we developed a Factor of Safety proxy that consistently falls below the triggering threshold for all probes exhibiting displacements exceeding 50 mm. This study offers novel insights into patterns and triggers of hillslope movements in the Arctic and provides a venue to evaluate their impact on soil redistribution.

54 ENVIRONMENTAL SCIENCES↗

Delving into the depths of NGC 3783 with XRISM V. Broad-band modelling of ionized outflows

The Seyfert 1 galaxy NGC 3783 hosts a multi-phase warm absorber (WA) that has been extensively studied in the X-ray band. High-resolution spectra from 2000−2001 revealed a complex outflow with multiple ionization and velocity components. Two decades later, new XMM-Newton and XRISM observations allow us to investigate the long-term evolution of these outflows. We performed joint spectral modelling of the XMM-Newton /RGS and XRISM/Resolve time-averaged spectra using the pion photoionization code within SPEX. We derived the ionization parameter, column density, turbulent velocity, and outflow velocity for each absorption component, and investigated their thermal stability and absorption measure distribution (AMD) to characterize the physical and dynamical properties of the WA in NGC 3783 in 2024. We compared these results with the 2000−2001 epoch to assess long-term variability, stability, and possible changes in the absorber population. We identify eight WA components spanning log ξ = 1.08 − 3.38 and outflow velocities of 480−1230 km s −1 . The ranges of column densities and turbulent velocities remain broadly consistent with the WAs from 2000−2001, but the earlier data contained more low-ionization, high-velocity components. The total column density of all the outflows in 2024 is 1.5 times larger than in 2000−2001, which means that it has been replenished by fresh material. The dominant unresolved transition array (UTA) absorber (component B3) has increased its column density by a factor of three while maintaining a similar ionization parameter. The WAs in NGC 3783 have undergone significant structural and dynamical evolution over the past 24 years.

79 ASTRONOMY AND ASTROPHYSICS↗

Data-Driven Security Assessment of Power Grids Based on Machine Learning Approach: Preprint

Data-driven security assessment provides key indicators on power system stability using simulations on scheduling models, as opposed to dynamic simulations that are more time-consuming. This paper investigates data-driven security assessment of power grids based on machine learning. Multivariate random forest regression is used as the machine learning algorithm due to its high robustness to the input data. Three stability issues are analyzed using the proposed machine learning tool, including transient stability, frequency stability and small signal stability. The estimation values from machine learning tool are compared with those from dynamic simulations. Results show that the proposed machine learning tool can effectively predict the stability margins for the three stability metrics.

14 SOLAR ENERGY↗

A Simulation Modeling Approach to Optimizing Nuclear Waste Dispositioning

The dispositioning of nuclear waste generated at facilities across the country is an ongoing battle that affects us all. National laboratories and research centers dealing in medical research, clean energy, and other nuclear activities such as the Department of Energy (DOE) facilities face the need to properly manage and dispose of nuclear waste. A dynamic modeling solution would enable the DOE and others to make decisions on waste disposal and technological options. In doing so, this research explores modeling techniques using available data to address these situations. The focus being on developing an initial robust and adaptable discrete event model using the ExtendSim tool. This modeling effort will target the dispositioning of transuranic waste at the Savannah River National Laboratory (SRNL) which can be expanded to represent the current state of disposition process for waste generated at other DOE facilities. The model aims to assess resource allocation and waste processing options to stabilize productivity and cut the backlog of nuclear waste. By assessing the results of different scenarios, this research aims to provide actionable insights for the DOE. This approach has the potential to significantly improve the management of radioactive waste, offering the capability of evaluating options for optimizing the process for nuclear waste disposal. The findings of this study can serve as a valuable resource for decision-makers and other national laboratories, or research entities engaged in nuclear operations by enabling them to make more informed choices.

Andaverde, Alexis↗

Stability Analysis of Interface Conditions for Ocean-Atmosphere Coupling

In this paper, we analyze the stability of different coupling strategies for multidomain PDEs that arise in general circulation models used in climate simulations. We focus on fully coupled ocean–atmosphere models that are needed to represent and understand the complicated interactions of these two systems, becoming increasingly important in climate change assessment in recent years. Numerical stability issues typically arise because of different time-stepping strategies applied to the coupled PDE system. In particular, the contributing factors include using large time steps, lack of accurate interface flux, and single-iteration coupling. We investigate the stability of the coupled ocean–atmosphere models for various interface conditions such as the Dirichlet–Neumann condition and the bulk interface condition, which is unique to climate modeling. By analyzing a simplified model, we demonstrate here how the parameterization of the bulk condition and other numerical and physical parameters affect the coupling stability and establish stability conditions for different coupling strategies.

97 MATHEMATICS AND COMPUTING↗

Zinc Oxide–Graphene Nanocomposite-Based Sensor for the Electrochemical Determination of Cetirizine

A nanocomposite electrode of graphene (Gr) and zinc oxide (ZnO) nanoparticles was fabricated to study the electrochemical oxidation behavior of an anti-inflammatory drug, i.e., cetirizine (CET). The voltametric response of CET for bare CPE, Gr/CPE, ZnO/CPE, and the ZnO-Gr nanocomposite electrode was studied. The modifier materials were characterized using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray powder diffraction (XRD) to comprehend the surface morphology of the utilized modifiers. The influence of pH, scan rate, and accumulation time on the electrooxidation of CET was examined. It was found that the electrochemical oxidation of CET was diffusion-controlled, in which two protons and two electrons participated. The detection limit was found to be 2.8 × 10 -8 M in a linearity range of 0.05–4.0 µM. Study of excipients was also performed, and it was found that they had negligible interference with the peak potential of CET. The validation and utility of the fabricated nanocomposite sensor material were examined by analyzing clinical and biological samples. Stability testing of the nanocomposite electrode was conducted to assess the reproducibility, determining that the developed biosensor has good stability and high efficiency in producing reproducible results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Qualification of Sealability and Creep Relaxation of Additively Manufactured Zytel Gaskets for PEM Fuel Cells

The purpose of this thesis is to study the feasibility of low-cost additive manufacturing of gaskets for proton exchange membrane fuel cells exposed to extreme temperature conditions ranging from -55°C to 100°C. With the growing popularity and decreasing costs of additive manufacturing technologies, specifically Material Extrusion (ME), research is being conducted to determine the feasibility of ME components. Thermally cycled PEMFCs may exhibit accelerated gasket deterioration, therefore, the mechanical stability of material extruded gaskets following a harsh thermal cycle must be assessed. The feasibility of the material extruded gaskets will be proven by manufacturing optimization and mechanical testing. The target material for this study is Zytel by DuPont Chemical. The mechanical stability will be assessed via sealability and creep relaxation testing according to ASTM F37B and ASTM F38B respectively. Because the capabilities to conduct sealability testing at temperature were not available, each specimen was thermally soaked and allowed to return to room temperature prior to testing. As a result of sealability experiments, the 100°C-soaked specimens resulted in lower leak rates with a higher precision when compared to specimens soaked at -55°C and 22°C at across all compressive loads. It was observed from results from creep relaxation testing that there is thermal contraction and expansion occurring at 55°C and 100°C respectively, which can be observed by the resultant graphs. The recoverability of thermally cycled specimens are better than those that just experienced a high temperature hold. After the seven-day thermal cycle, the samples stabilized and maintained their structure.

Lazarin, Robert↗

Control Parameter Sensitivity Study for Inverter-Based-Resource Dominated Grids: A Small Signal Stability Approach and Framework

The growing adoption of renewable energy is driving the prevalence of inverter-based resources (IBRs) within power grids. Future power grids will integrate both grid-following IBRs (GFM-IBRs) and grid-forming IBRs (GFL-IBRs) alongside synchronous generators. Therefore, it is crucial to perform stability studies that account for all components and especially control interactions related to IBRs. Extensive research has performed to study the IBR-related stability, however, the sensitivity study of IBRs' control parameters on system stability has not been adequately studied yet, especially from a systematic way. Therefore, this paper conducts a small signal stability analysis for a generic grid with multiple types of resources and develops an analytical framework for assessing the sensitivity of control parameters affecting stability margins. To achieve that, the non-autonomous reduced-order non-linear dynamic model is developed for a generic power system with multiple synchronous generator-based resources (SGBRs), GFM-IBRs, and GFL-IBRs. Based on the analytic model, a systematic framework for parametric sensitivity on systems' asymptotic stability is developed. A parameter sensitivity analysis based on eigenvalue methods is proposed. The impact of the droop controllers of GFM-IBRs, PQ-dispatch and the PLL controller of GFL-IBR on the system asymptotic stability is discussed. This sensitivity study is aiming to provide deep insights on control parameters' impact on system stability, and gives direction for parameter tuning in case of instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimum Multinozzle Configuration for Minimizing the Rayleigh Integral During High-Frequency Transverse Instabilities

This paper develops a formalism for optimizing nozzle location/configuration with respect to combustion stability of high-frequency transverse modes in a can combustor. The stability of these acoustically noncompact flames was assessed using the Rayleigh integral (RI). Several key control parameters influence RI—flame angle, swirling strength, nozzle location, as well as nozzle location with respect to the acoustic mode shape. In this study, we consider a N-around-1 configuration such as typically used in a multi-nozzle can system and study the overall stability of this system for different natural transverse modes. Typically, such nozzles are distributed in a uniformly circular manner for which we study the overall RI, and for cases where RI > 0, we optimize the nozzle distribution that can reduce and minimize RI. For a fixed geometry such as a circular configuration, the analysis shows how the flame's parameters must vary across the different nozzles, to result in a relatively stable system. Additionally, for a fixed set of flame parameters, the analysis also indicates the noncircular distribution of the N nozzles that minimizes RI. Overall, the analysis aims to provide insights on designing nozzle locations around the center nozzle for minimal amplification of a given transverse mode.

42 ENGINEERING↗

200 h of discharge cycling with an all-aqueous copper thermally regenerative ammonia battery

Thermally regenerative ammonia batteries (TRABs) offer an approach to energy storage and electricity generation by harnessing low-grade heat (T < 150 °C). A TRAB discharge resembles that of a flow battery, where electrochemical reactions produce electrical power from energy stored within aqueous electrolytes. While there are many types of TRABs, the all-aqueous copper TRAB (Cu aq -TRAB) has produced the largest power and energy storage densities. Despite many improvements to TRAB performance, most tests have only lasted a few hours, which are not representative of operation times expected of these devices. Herein, we operated a Cu aq -TRAB for 200 h of constant current discharging to assess battery performance and component stability. After 200 h of testing, the average power density increased slightly to 7.2 mW cm -2 , which was within 0.01 % of starting conditions. Likewise, the average energy density for the final cycle was only 0.03 % lower than the initial cycle. The overall insensitivity of the power cell to cycling represents a major milestone in the advancement of TRAB systems. In conclusion, energy dispersive X-ray spectroscopy provides evidence to suggest that these small changes in power and energy density are likely to the membrane acclimating to TRAB electrolytes.

25 ENERGY STORAGE↗

Long-term thermal stability and calibration of Type-II fiber Bragg grating array inscribed in radiation-hardened fibers

This paper investigates the long-term thermal stability of Type-II fiber Bragg grating (FBG) arrays, inscribed by femtosecond laser in radiation-hardened fiber, for potential applications as multiplexed sensors in high-temperature energy systems. The thermal stability of FBG sensors was assessed through 16 thermal cycles from room temperature (RT) to 750 ℃ about two months, involving 100 FBG sensors. The results show that the absolute temperature drift of FBG sensors can be reduced to less than 0.4 pm/day after 54 h thermal annealing process at a constant temperature of 800 ℃. As temperature sensors, the FBGs demonstrated stable performance, achieving a standard deviation (STD) of 1.8 pm (corresponding to a temperature resolution of 0.118 ℃) post-annealing. Repeated thermal cycles revealed a random drift of 2.3 pm in the FBG wavelength at RT. Polynomial fitting was explored as a calibration method to convert FBG wavelength shifts into absolute temperature measurements. By optimizing calibration temperature points (RT, 200 ℃, 400 ℃, and 750 ℃), the study shows that cubic polynomial calibration using four points yields an average R2 of 0.9997 and an RMSE of 3.58 ℃ across the entire temperature range (RT to 750 ℃). This approach represents an 11.53-fold improvement over empirical slope calibration and a 1.34-fold improvement over four-point piecewise fitting. The findings indicate that Type-II FBGs inscribed in radiation-hardened fibers can function as accurate temperature sensors, with performance on par with or exceeding that of thermocouples. With their multiplexing capability, robust signal transmission over long lead cables, and immunity to electromagnetic interference, FBG sensors offer a promising alternative to traditional electronic sensors for energy system monitoring.

Dominguez-Ontiveros, Elvis [ORNL] (ORCID:000000018↗

Evaluation of Force Fields for Molecular Dynamics Simulations of Platinum in Bulk and Nanoparticle Forms

Here, understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties - surface energy, lattice constant, stiffness constants, and the equation of state - and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential - the embedded atom method formalism with a specific parameter set - was identified as best able to model platinum in both bulk and nanoparticle forms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

From lab to lamp: Understanding downconverter degradation in LED packages

Downconverters, primarily inorganic phosphors, are critical components in white solid-state LED-based lighting and liquid crystal display backlights. Research efforts have led to a fundamental understanding of a downconverter's absorption, photoluminescence, and efficiency as a function of composition, structure, and processing conditions. However, considerably less work has focused on the reliability of phosphors once they are incorporated into LED packages. Solving these issues is often the final step before the commercialization of new materials, but the significant resources and time required to evaluate and mitigate materials failure are rarely discussed in the literature. In this Perspective, we discuss the need for conducting downconverter reliability testing and the potential of accelerating, screening, and understanding downconverter failure modes. Our focus highlights the mechanisms of failure and discusses how this influences materials selection and the design of different LED packages. We also stress the potential for accelerated reliability testing protocols and note the potential role first-principles calculations and data-driven models could play in establishing the compositional-processing trends for different aspects of downconverter reliability. In conclusion, we close with possible research directions that could improve downconverter reliability and emphasize the importance of assessing a material's (chemical) stability where multiple manufacturing and processing steps can dictate system performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Open Source High Fidelity Modeling of a Type-5 Wind Turbine Drivetrain

The increasing integration of renewable energy resources in evolving bulk power system (BPS) is impacting the system inertia. Type-5 wind turbine generation has the potential to behave like a traditional synchronous generator and can help mitigate the impact on system inertia. A hydraulic torque converter (TC) and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine unit. A high fidelity model of Type-5 wind turbine drivetrain is not openly and widely available for grid integration and transient stability studies. This hinders appropriate assessment of Type-5 wind power plant’s contribution to bulk grid resilience. This work develops and validates a TC model based on those generally used in automobile’s transmission system. Moreover, the concept of torsional coupling is leveraged to integrate the TC and gearbox system dynamics. The entire integrated model will be open sourced and publicly available for grid integration studies.

17 WIND ENERGY↗

Critical Clearing Time for Droop-Controlled Grid-Forming Inverters With Circular Current Limiting and Virtual Impedance Current Limiting

The critical clearing time is a crucial parameter for assessing the large-signal stability of grid-forming (GFM) inverters. Variations in current limiters can significantly impact an inverter's transient behavior during large disturbances. Here, this letter introduces a method based on the power-angle relationship to evaluate the fault recovery of a droop-controlled GFM inverter under a three-phase bolted fault scenario, considering both the circular current limiter and the virtual impedance method. High-fidelity simulations validate the accuracy of the proposed formulas in estimating the critical clearing time of the GFM inverter.

42 ENGINEERING↗