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At least 73 records · Page 4

Anion-dependent phase behavior of methylimidazolium-based ionic liquids mixed with water: Correlation between local molecular structure and mesoscale behaviors

The mesoscopic phase behavior of decylmethylimidazolium (C 10 mim) ionic liquids (ILs) bearing three monovalent anions—thiocyanate (SCN − ), nitrate (NO 3 − ), and chloride (Cl − )—mixed with water at relatively high IL contents (50–95 wt%) was investigated. Small-angle and wide-angle X-ray scattering (SAXS/WAXS) were employed to follow the evolution of both local and mesoscale structures across this composition range. In the absence of water, C 10 mimSCN and C 10 mimCl behaved as disordered liquids, whereas C 10 mimNO 3 spontaneously formed a hexagonally ordered cylindrical mesophase and displayed a sticky-solid macroscopic appearance. Upon addition of water, C 10 mimSCN remained a viscous liquid and only weakly ordered lamellar domains were observed. This limited ordering is attributed to the lack of hydrogen bonding and weak interaction energy between SCN − anions and C 10 mim + cations. In contrast, the trigonal-planar NO 3 − and point-like Cl − anions promoted the formation of well-defined hexagonal mesophases up to 35–45 wt% water. The formation of hydrogen bonding of the two anions with imidazolium ring protons likely enabled the creation of compact ion clusters that effectively exclude water molecules from the immediate vicinity of the IL aggregates. These findings demonstrate that the interaction energy between ion pairs dictate IL-water interactions and therefore control the transition from disordered liquids to ordered mesophases in IL/water mixtures with high IL contents. In conclusion, the combined SAXS/WAXS analysis reveals a correlation between local intermolecular structure and the emergence of mesoscopic order, providing a systematic framework for tailoring mesoscale structures in alkylimidazolium-based IL/water systems.

36 MATERIALS SCIENCE↗

Carbonation of Alkaline Earth Metal Hydroxides: Structure across Nano- to Mesoscales

The conversion of gaseous CO 2 into a solid constitution through mineralization is an active area of carbon capture, and alkaline earth metal hydroxides (M(OH) 2 , M = Ca 2+ , Mg 2+ ) are frontrunners in this area. As model systems, nanolime samples are excellent templates for the study of this reaction. Here, we have examined these under ambient pressure conditions with controlled humidity and CO 2 . Utilizing a broad range of analytical methods, we first established the purity and structures of the selected materials. We then examined the structural changes due to carbonation, using infrared spectroscopy, X-ray scattering, and neutron scattering. The resulting structural changes are resolved from nanoscale to mesoscale and from early-stage to late-stage carbonation. Ca(OH) 2 and Mg(OH) 2 are found to behave quite differently. As expected from prior work, the carbonation of Ca(OH) 2 is kinetically favored. Further, our structure studies suggest this is due to a facile reaction at the fractal interface of the particles. From early- to late-stage carbonation, there is a consistent increase in the fractal roughness. This is in contrast to Mg(OH) 2 where the same surface evolves into a smooth conformal coating. For this material the major reacting component is at the mesoscale, suggesting globular particle growth or evolving macro-porosity. Because neutron scattering is sensitive to hydrogen content, we expected a significant change as M(OH) 2 evolves to MCO 3 . Such a change is found for Ca(OH) 2 but not for Mg(OH) 2 , providing evidence for the formation of hydrated carbonates for the later material. The formation of a conformal layer along with water-rich carbonate formation is an impediment to the use of Mg(OH) 2 for carbon capture. For energy-efficient carbon capture, it would be desirable to enhance carbonation rates for Mg(OH) 2 , and one possible route would be the use of anhydrous fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonlocal Effect of Percolated Particle Networks on Viscoelasticity of Polymer–Filler Nanocomposites: A Mesoscale Simulation Study

With nanoparticles (NPs) as fillers, polymer nanocomposites (PNCs) usually exhibit enhanced mechanical properties. However, a direct connection between the microscopic structural relaxation and macroscopic mechanical properties of PNCs remains to be established. To investigate the micro-to-macro connection, we develop a mesoscale model, in which the NPbridging polymer chains are represented by a dynamic bonded interaction between NPs, and the bulk polymer matrix is implicitly modeled by overdamped Langevin dynamics. Extensive equilibrium simulations are performed to quantify the microscopic dynamics of model PNCs. Systematic analyses of modified Rouse dynamics, dynamic structure factor, and relaxation modulus uncover that the microscopic relaxation dynamics of PNCs are significantly decelerated across different length scales because of nonlocal effects of percolated particle networks a phenomenon that has not been adequately captured in prior simulation studies. We find that NPvolume- fraction and NP-bonding-energy barrier are the two critical variables that affect bulk viscoelasticity the most. The proposed mesoscale model is versatile and provides a powerful framework for studying structure−property relations of different PNCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Mesoscale Degradation in Nickel-Rich Cathode Materials through Machine-Learning-Revealed Strain–Redox Decoupling

The degradation of nickel-rich cathode materials for lithium-ion batteries upon prolonged electrochemical cycling features a complicated interplay among electronic structure, lattice configuration, and micro-morphology. The underlying mechanism for such an entanglement of different material properties at nano- to mesoscales is fundamental to the battery performance but not well-understood yet. Here we investigate the correlation between the local redox reaction and lattice mismatch through a nano-resolution synchrotron spectro-microscopy study of LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM 811) cathode particles. With assistance from a machine-learning-based data classification method, we identify local regions that demonstrate a strain–redox decoupling effect, which can be attributed to different side reactions. Overall, our results highlight the mesoscale reaction heterogeneity in the battery cathode and suggest that particle structure engineering could be a viable approach to mitigate the chemomechanical degradation of cathode materials.

25 ENERGY STORAGE↗

Mechanism of Mesoscale Woodpile Development via Photoelectrochemical Deposition of Se–Te

A combination of experiments and optical modeling provided insight into the mechanism of mesoscale woodpile formation in response to an orthogonal shift in polarization during photoelectrochemical deposition of Se–Te. Cathodic deposition of semiconducting Se–Te using spatially uniform, linearly polarized illumination produced arrays of lamellae that were aligned parallel to the optical E-field oscillation. Continued deposition in conjunction with an orthogonal shift in the polarization direction then produced aligned bridging features that spanned the void space between, and were orthogonal to, the preexisting lamellae. The height and pitch, respectively, in each layer of the woodpile were a function of the charge density and illumination wavelength during deposition. A Monte Carlo model, in which material addition was scaled by the absorption magnitude obtained from electromagnetic simulations, produced morphologies that were nominally identical to those observed experimentally. Here, the formation of mesoscale woodpiles is consistent with a mechanism that involves a series of spontaneously initiated, concerted light–matter interactions during the photoelectrochemical deposition process.

absorption↗

Mesoscale Polymer Surfactants: Photolithographic Production and Localization at Droplet Interfaces

Stabilization of fluid droplets, classically as oil-in-water or water-in-oil emulsions, is typically conducted using molecular surfactants or small particulates that localize at oil-water interfaces. In this paper, we describe a method whereby thin polymer films are converted photolithographically to ribbon-like mesoscale objects, which in turn adsorb to fluid inter-faces where they extend as appendages, or arms, from the droplet surface. These “mesoscale polymer surfactants”, or MPSs, were prepared from thin polymer films containing reactive functional moieties, including coumarin for photo-crosslinking, triphenylsulfonium for photoacid generation, and tert-butyl ester for solubility switching. The resultant MPSs, prepared initially on Si substrates, were released into water to reveal an exquisite shape sensitivity (forming straight, bent, or helical structures) and affinity for droplet interfaces based on their preparation conditions and the properties of the surrounding liquid. Notably, the lithographic techniques employed were amenable to differentiating the wettability of MPS segments, affording access to diblock-like MPSs which adhered to dispersed droplets via their hydrophobic segments, allowing their hydrophilic segments to extend into the continuous phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Wavelet Analysis of Properties of Marine Boundary Layer Mesoscale Cells Observed From AMSR–E

Marine boundary layer clouds tend to organize into closed or open mesoscale cellular convection (MCC). Here, two-dimensional wavelet analysis is applied for the first time to passive microwave retrievals of cloud water path (CWP), water vapor path (WVP), and rain rate (RR) from Advanced Microwave Scanning Radiometer for Earth Observing System in 2008 over the Northeast and Southeast Pacific, and the Southeast Atlantic subtropical stratocumulus to cumulus transition regions. The (co-)variability between CWP, WVP, and RR in 160 × 160 km 2 analysis boxes is partitioned between four mesoscale wavelength octaves (20, 40, 80, and 160 km). The cell scale is identified as the wavelength of the peak CWP variance. Together with a machine-learning classification of cell type, this allows the statistical characteristics of open and closed MCC of various scales, and its relation to WVP, RR, and potential environmental controlling factors to be analyzed across a very large set of cases. Here, the results show that the cell wavelength is most commonly 40–80 km. Cell-scale CWP perturbations are good predictors of the WVP and RR perturbations. For cells larger than 20 km, there is no obvious dependence of cell scale on the environmental controlling factors tested, suggesting that the cell scale may depend more on its historical evolution than the current environmental conditions.

54 ENVIRONMENTAL SCIENCES↗

Convective and Orographic Origins of the Mesoscale Kinetic Energy Spectrum

The mesoscale spectrum describes the distribution of kinetic energy in the Earth's atmosphere between length scales of 10 and 400 km. Since the first observations, the origins of this spectrum have been controversial. At synoptic scales, the spectrum follows a –3 spectral slope, consistent with two-dimensional turbulence theory, but a shallower –5/3 slope was observed at the shorter mesoscales. The cause of the shallower slope remains obscure, illustrating our lack of understanding. Through a novel coarse-graining methodology, we are able to present a spatio-temporal climatology of the spectral slope. We find convection and orography have a shallowing effect and can quantify this using “conditioned spectra.” These are typical spectra for a meteorological condition, obtained by aggregating spectra where the condition holds. This allows the investigation of new relationships, such as that between energy flux and spectral slope. Potential future applications of our methodology include predictability research and model validation.

54 ENVIRONMENTAL SCIENCES↗

Compound Mesoscale Convective Systems and Low‐Pressure Systems in Tropical Monsoon Regions: Assessing Their Meteorology and Precipitation

Mesoscale convective systems (MCS) and low-pressure systems (LPS) are both strongly associated with precipitation across the regions where they occur, particularly within global monsoon systems; however, their co-occurrence and its relationship to precipitation have not been systematically examined. Here, we use LPS and MCS trackers to detect compound MCS and LPS events in five monsoon regions and assess the association of this co-occurrence with anomalies of winds, precipitation, and other atmospheric variables. Additionally, we investigate the spatial distribution of precipitating MCS and LPS events. Our results show that most (∼60%) MCS and LPS co-occurrences are located in the lower latitudes, where they contribute up to 40% of annual precipitation. We find that compound events generally produce more extreme precipitation than MCS-only or LPS-only events. Furthermore, our assessment of the synoptic and mesoscale composites reveals that the underlying dynamics of compound events exhibit anomalously positive convective available potential energy and an anomalously low-pressure within the location of the event. In terms of the synoptic environment of the features, the compound MCS and LPS events are associated with inverted troughs in three out of five monsoon locations assessed.

Environmental sciences↗

Mesoscale interplay between phonons and crystal electric field excitations in quantum spin liquid candidate CsYbSe 2

In this report CsYbSe 2 , a recently identified quantum spin liquid (QSL) candidate, exhibits strong crystal electric field (CEF) excitations. Here, we identify phonon and CEF modes with Raman spectroscopy and observe strong CEF-phonon coupling resulting in a vibronic bound state. Complex, mesoscale interplay between phonon modes and CEF modes is observed in real space. Additionally, an unexpected resonant Raman excitation condition is satisfied, yielding up to third-order combination modes, with a total of 17 modes identified in the spectra. This study paves the way to coherent control of possible QSL ground states with optically accessible CEF-phonon manifolds and mesoscale engineering of CEF-phonon interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mesoscale simulation of granular materials under weak shock compaction–pore size distribution effects

This research established a systematic method to generate various pore-size distributions (PSDs) and studied the effect of PSDs on the shock compaction response of granular materials using two-dimensional mesoscale simulations under identical porosity. Simulations utilized various PSDs for three particle shapes (circle, ellipse, and square). Contacting particle configurations using three PSDs, characterized by spatially uniform distributed pores to heterogeneous distributed pores, and non-contacting particle configurations under a single case of PSD were tested. The PSD of generated particle sets was characterized using coordination number, mean diameter, and bimodality coefficient as statistical metrics. Mesoscale simulations showed that regardless of the conditions of pore distributions, shock compaction of granular materials consistently demonstrates a precursor, shock compaction front, and end. However, the shock compaction velocity of contacting particles was dependent on the PSDs despite the constant initial porosity. The compaction velocity was faster in particle configurations with relatively uniform pore distributions than in heterogeneous pore distributions, which our study demonstrated can be attributed to particle rearrangement during compaction. Circular-shaped particles had high sensitivity in shock compaction response to the various PSDs. Furthermore, a contacting particle configuration tended to propagate the shock compaction wave relatively faster than particles that were in a non-contact configuration. This study established the relative importance of considering PSD as a metric over the coordination number in studies of the shock compaction response of granular materials. Further, insights are provided on the evolving shock substructure to characterize the shock compaction response of granular materials.

36 MATERIALS SCIENCE↗

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

The Application of a Genetic Algorithm to the Optimization of a Mesoscale Model for Emergency Response

Besides solving the equations of momentum, heat, and moisture transport on the model grid, mesoscale weather models must account for subgrid-scale processes that affect the resolved model variables. These are simulated with model parameterizations, which often rely on values preset by the user. Such “free” model parameters, along with others set to initialize the model, are often poorly constrained, requiring that a user select each from a range of plausible values. Finding the values to optimize any forecasting tool can be accomplished with a search algorithm, and one such process—the genetic algorithm (GA)—has become especially popular. As applied to modeling, GAs represent a Darwinian process: an ensemble of simulations is run with a different set of parameter values for each member, and the members subsequently judged to be most accurate are selected as “parents” who pass their parameters onto a new generation. At the U.S. Department of Energy’s Savannah River Site in South Carolina, we are applying a GA to the Regional Atmospheric Modeling System (RAMS) mesoscale weather model, which supplies input to a model to simulate the dispersion of an airborne contaminant as part of the site’s emergency response preparations. An ensemble of forecasts is run each day, weather data are used to “score” the individual members of the ensemble, and the parameters from the best members are used for the next day’s forecasts. As meteorological conditions change, the parameters change as well, maintaining a model configuration that is best adapted to atmospheric conditions. Significance Statement We wanted to develop a forecasting system by which a weather model is run over the Savannah River Site each day and repeatedly adjusted according to how well it performed the previous day. To run the model, a series of values (parameters) must be set to control how the model will calculate winds, temperatures, and other desired variables. Each day the model was run several times using different combinations of these parameters and later compared with observed meteorological conditions. Parameters that produced the most accurate forecasts were preferentially reused to create the forecasts for the next day. The process was tested for the summer of 2020 and exhibited lower errors than forecasts produced by the model using default values of the parameters.

54 ENVIRONMENTAL SCIENCES↗

Impact of Meteorological Factors on the Mesoscale Morphology of Cloud Streets during a Cold-Air Outbreak over the Western North Atlantic

We report postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario.

54 ENVIRONMENTAL SCIENCES↗

Deep-ultraviolet ptychographic pocket-scope (DART): mesoscale lensless molecular imaging with label-free spectroscopic contrast

The mesoscale characterization of biological specimens has traditionally required compromises between resolution, field-of-view, depth-of-field, and molecular specificity, with most approaches relying on external labels. Here we present the Deep-ultrAviolet ptychogRaphic pockeT-scope (DART), a handheld platform that transforms label-free molecular imaging through intrinsic deep-ultraviolet spectroscopic contrast. By leveraging biomolecules’ natural absorption fingerprints and combining them with lensless ptychographic microscopy, DART resolves down to 308-nm linewidths across centimeter-scale areas while maintaining millimeter-scale depth-of-field. The system’s virtual error-bin methodology effectively eliminates artifacts from limited temporal coherence and other optical imperfections, enabling high-fidelity molecular imaging without lenses. Through differential spectroscopic imaging at deep-ultraviolet wavelengths, DART quantitatively maps nucleic acid and protein distributions with femtogram sensitivity, providing an intrinsic basis for explainable virtual staining. We demonstrate DART’s capabilities through imaging of tissue sections, cytopathology specimens, blood cells, and neural populations, revealing detailed molecular contrast without external labels. The combination of high-resolution molecular mapping and broad mesoscale imaging in a portable platform opens new possibilities from rapid clinical diagnostics, tissue analysis, to biological characterization in space exploration.

60 APPLIED LIFE SCIENCES↗

Mesoscale simulations of pressure-shear loading of granular tungsten carbide

Numerical simulations of pressure-shear loading of a granular material are performed using the shock physics code CTH. A simple mesoscale model for the granular material is used that consists of a randomly packed arrangement of solid circular or spherical grains of uniform size separated by vacuum. The grain material is described by a simple shock equation of state, elastic perfectly plastic strength model, and fracture model with baseline parameters for WC taken from previous mesoscale modeling work. Simulations using the baseline material parameters are performed at the same initial conditions of pressure-shear experiments on dry WC powders. Except for some localized flow regions appearing in simulations with an approximate treatment of sliding interfaces among grains, the samples respond elastically during shear, which is in contrast to experimental observations. By extending the simulations to higher shear wave amplitudes, macroscopic shear failure of the simulated samples is observed with the shear strength increasing with increasing stress confinement. The shear strength is also found to be strongly dependent on the grain interface treatment and on the fracture stress of the grains, though the variation in shear strength due to fracture stress decreases with increasing stress confinement. At partial compactions, the transverse velocity histories show strain-hardening behavior followed by formation of a shear interface that extends through the transverse dimensions of the sample. Near full compaction, no strain hardening is observed and, instead, the sample transitions sharply from an elastic response to formation of an internal shear interface. Agreement with experiment is shown to worsen with increasing confinement stress with simulations overpredicting the shear strengths measured in experiment. The source of the disagreement can be ultimately attributed to the Eulerian nature of the simulations, which do not treat contact and fracture realistically.

36 MATERIALS SCIENCE↗

Synoptic and Mesoscale Modulation of Dynamic and Thermodynamic Impacts on Central Arctic Sea Ice During MOSAiC

The primary objectives of this proposed project are to determine 1) to what extent dynamic and thermodynamic air‐ice interactions in the Central Arctic are driven by atmospheric synoptic and mesoscale phenomena, and 2) the key processes involved in these interactions. These phenomena include large‐scale features such as fronts, high‐ and low‐pressure systems, low‐level jets, and cloud bands, but may also include smaller‐scale phenomena such as mesoscale instabilities (e.g., symmetric instability or slantwise convection), transient meso‐lows and gravity waves. Dynamic air‐ice interactions include direct atmospheric stress and atmospheric stress divergence/deformation; thermodynamic air‐ice interactions involve the net surface energy budget, especially in association with non‐stratocumulus clouds generally occurring with stronger dynamical forcing.

58 GEOSCIENCES↗

Mesoscale Modeling for Restructuring and Fragmentation in High Burnup UO 2

This report summarizes the mesoscale modeling conducted in fiscal year 2025 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, focusing on the microstructural evolution and restructuring in high burnup UO 2 nuclear fuel and its impact on fuel fragmentation. We developed a pioneering phase-field model to simulate restructuring behavior across different regions of high burnup fuel, including the dark zone and rim region. A grand-potential-based phase-field model is employed to concurrently evaluate subgrain formation and the growth of fission gas bubbles within the fuel. An energy-based subgrain formation criterion was introduced to simulate the restructuring process. The effects of temperature and burnup rate were studied to capture how each of these parameters influences the characteristics of the restructured fuel. Subgrain formation was observed to initiate around existing fission gas bubbles and proceed toward triple junctions, grain boundaries, and grain interiors. Under a given subgrain formation rate, the rate of restructuring increases with rising fuel temperature. The restructuring occurs faster with higher burnup rate. A restructuring bias was observed within the microstructure, due to the variation in defect accumulation when comparing different grains. Microstructures corresponding to the dark zone and rim region can be obtained by parameterizing the model with the appropriate defect production rate, as determined based on the burnup rate and temperature. The predicted microstructures are consistent with experimental observations of the restructured regions. Based on the mesoscale simulations, a mechanistic model for restructuring and grain size evolution was implemented in BISON. Thus, this work provides a first-of-its-kind restructuring model for different regions of high-burnup fuel to BISON. It was shown that the model predicts appropriate grain size evolution along fuel radius as those observed in experiments. This model enables BISON to predict the effect of restructuring on the fission gas release. Finally, the phase-field fracture simulation with dark zone specific microstructures were presented to provide the fragmentation criteria for the dark zone. This work introduces a first-of-its-kind restructuring model for high burnup fuel, significantly enhancing BISON's predictive capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗