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Results for “SCALING”
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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A new multi-scale structure finding algorithm to identify cosmological structure
We introduce a new structure finding algorithm that self-consistently parses large scale cosmological structure into clusters, filaments and voids. This structure finding algorithm probes the structure at multiple scales and classifies the appropriate regions with the most probable structure type and size. We show that it can identify the baryon fraction of intercluster medium and cosmological voids.
Drive Cycles, Battery Pack Scaling, and Usage Considerations for Long-Haul and Regional-Haul Electric Trucks
Electrifying Class-8 heavy-duty trucks presents a promising opportunity to enhance energy efficiency and reduce freight transport costs. Battery electric trucks (BETs), once considered niche, are gaining traction due to advancements in battery technology and cost reductions. However, accurately predicting battery lifespan under realistic usage conditions remains a key challenge. Understanding battery failure mechanisms and their links to design, operation, and management is essential for developers and fleet operators. This study introduces a method to develop simplified, lab-testable dynamic stress test (DST) cycles for regional and long-haul Class-8 BETs, derived from real-world diesel truck usage. These DSTs enable benchmarking of battery technologies, identification of aging stressors, and optimization of battery design, life, and cost. The approach supports evaluation of key metrics such as levelized cost of driving and total cost of ownership, aiding fair comparisons and adoption decisions. We also propose feasible battery pack sizes that meet current driving demands with strategic charging, and a method to scale pack-level DSTs to cell-level cycles for lab-based testing. These tools facilitate tradeoff analysis across battery chemistries, pack sizing, and charging strategies, while offering means to get insights into battery aging under realistic conditions-ultimately supporting informed BET deployment decisions.
Impacts of detrital nano- and micro-scale particles (dNP) on contaminant dynamics in a coal mine AMD treatment system
Abstract not provided
3D elemental mapping with nanometer scale depth resolution via electron optical sectioning
Not Available
Nature of Lone-Pair–Surface Bonds and Their Scaling Relations [On the Nature of Lone Pair-Surface Bonds and Their Scaling Relations]
Here, we investigate the (surface) bonding of a class of industrially and biologically important molecules in which the chemically active orbital is a 2 p electron lone pair located on an N or O atom bound via single bonds to H or alkyl groups. This class includes water, ammonia, alcohols, ethers, and amines. Using extensive density functional theory (DFT) calculations, we discover scaling relations (correlations) among molecular binding energies of different members of this class: the bonding energetics of a single member can be used as a descriptor for other members. We investigate the bonding mechanism for a representative (H 2 O) and find the most important physical surface properties that dictate the strength and nature of the bonding through a combination of covalent and noncovalent electrostatic effects. We describe the importance of surface intrinsic electrostatic, geometric, and mechanical properties in determining the extent of the lone-pair–surface interactions. We study systems including ionic materials in which the surface positive and negative centers create strong local surface electric fields, which polarize the dangling lone pair and lead to a strong “electrostatically driven bond”. We emphasize the importance of noncovalent electrostatic effects and discuss why a fully covalent picture, common in the current first-principles literature on surface bonding of these molecules, is not adequate to correctly describe the bonding mechanism and energy trends. By pointing out a completely different mechanism (charge transfer) as the major factor for binding N- and O-containing unsaturated (radical) adsorbates, we explain why their binding energies can be tuned independently from those of the aforementioned species, having potential implications in scaling-driven catalyst discovery.
Nanometer-Scale Correlations in Aqueous Salt Solutions
The intermediate-range (1–4 nm) correlation of cations, an- ions, and water in aqueous alkaline earth salt solutions is measured using synchrotron X-ray diffraction. We differentiate from the entire solution structure factor, S(Q), a separate region at low Q (<1 °A-1) containing local diffraction maxima (pre-peaks) that indicate nanometer-scale oscillatory behavior. These features are quantitatively reproduced with classical molecular dynamics simulations. At high concentrations, the pre-peaks emerge from correlations arising from existence of small quasi close-packed lattice- like structures comprised of cation hydration spheres. We also analyze the concentration dependence of the pre-peak and discuss the overall results in light of the rich literature dealing with intermediate-range correlations underlying universal phenomena in concentrated electrolytes. The authors were supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest National Laboratory (PNNL) is operated by Battelle for the U.S. Department of Energy under Contract No. DE-AC05-76RL01830. Computing resources were generously allocated by PNNL's Institutional Computing program. DOE Contract No. DEAC02- 06CH11357 supports operation of the Advanced Photon Source at Argonne National Laboratory.
In Vivo Protein Dynamics on the Nanometer Length Scale and Nanosecond Time Scale
Selectively labeled GroEL protein was produced in living deuterated bacterial cells to enhance its neutron scattering signal above that of the intracellular milieu. Quasi-elastic neutron scattering shows that the in-cell diffusion coefficient of GroEL was (4.7 ± 0.3) × 10 –12 m 2 /s, a factor of 4 slower than its diffusion coefficient in buffer solution. Furthermore, for internal protein dynamics we see a relaxation time of (65 ± 6) ps, a factor of 2 slower compared to the protein in solution. Comparison to the literature suggests that the effective diffusivity of proteins depends on the length and time scale being probed. Retardation of in-cell diffusion compared to the buffer becomes more significant with the increasing probe length scale, suggesting that intracellular diffusion of biomolecules is nonuniform over the cellular volume. This approach outlined here enables investigation of protein dynamics within living cells to open up new lines of research using “in-cell neutron scattering” to study the dynamics of complex biomolecular systems.
Atomic-scale Mechanisms of Enhanced Electrochemical Properties of Mo-doped Co-free Layered Oxide Cathodes for Lithium-Ion Batteries
Cobalt-free layered oxides with high specific capacity and low cost have emerged as promising candidates for next-generation cathodes for lithium-ion batteries. However, implementation of these materials has been hindered by their low rate capability, structural instability, and rapid capacity decay during cycling. Recent studies have shown that introducing cation dopants into layered oxides can strongly improve their electrochemical properties, but the underlying mechanisms remain elusive due to a lack of information at the atomic scale. In this work, we use a combination of atomic-resolution scanning transmission electron microscopy and first principle calculations to reveal the microscopic origin of enhanced electrochemical properties in LiNi0.5Mn0.5O2 doped with ~1 at % Mo. These results indicate that the Mo dopant hinders Li+/Ni2+ cation mixing and suppresses detrimental phase transformations near the particle surface and at grain boundaries, which enhances the cathode’s reversible capacity and cycling stability. Overall, This work provides important insights on how cation doping affects the structure and electrochemical properties of layered oxide cathodes.
Quinone 1 e – and 2 e – /2 H + Reduction Potentials: Identification and Analysis of Deviations from Systematic Scaling Relationships
Quinones participate in diverse electron transfer and proton-coupled electron transfer processes in chemistry and biology. To understand the relationship between these redox processes, an experimental study was carried out to probe the 1 e – and 2 e – /2 H + reduction potentials of a number of common quinones. The results reveal a non-linear correlation between the 1 e – and 2 e – /2 H + reduction potentials. This unexpected observation prompted a computational study of 134 different quinones, probing their 1 e – reduction potentials, p K a values, and 2 e – /2 H + reduction potentials. We report the density functional theory calculations reveal an approximately linear correlation between these three properties and an effective Hammett constant associated with the quinone substituent(s). However, deviations from this linear scaling relationship are evident for quinones that feature intramolecular hydrogen bonding, halogen substituents, charged substituents, and/or sterically bulky substituents. These results, particularly the different substituent effects on the 1 e – versus 2 e – /2 H + reduction potentials, have important implications for designing quinones with tailored redox properties.
Development and Evaluation of an Explicit Treatment of Aerosol Processes at Cloud Scale Within a Multi‐Scale Modeling Framework (MMF)
Abstract Modeling the aerosol lifecycle in traditional global climate models (GCM) is challenging for a variety of reasons, not the least of which is the coarse grid. The multiscale modeling framework (MMF), in which a cloud resolving model replaces conventional parameterizations of cloud processes within each GCM grid column, provides a promising framework to address this challenge. Here we develop a new version of MMF that for the first time treats aerosol processes at cloud scale to improve the aerosol‐cloud interaction representation in the model. We demonstrate that the model with the explicit aerosol treatments shows significant improvements of many aspects of the simulated aerosols compared to the previous version of MMF with aerosols parameterized at the GCM grid scale. The explicit aerosol treatments produce a significant increase of the column burdens of black carbon (BC), primary organic aerosol, and sulfate by up to 40% in many remote regions, a decrease of the sea‐salt aerosol burdens by 40% in remote regions. These differences are caused by the differences in aerosol convective transport and wet removal between these two models. The new model also shows reduced bias of BC surface concentration in North America and BC vertical profiles in the high latitudes. However, the biased‐high BC concentrations in the upper troposphere over the remote Pacific regions remain, requiring further improvements on other process representations (e.g., secondary activation neglected in the model).
Evaluation of E3SM Simulated Aerosols and Aerosol‐Cloud Interactions Across GCM and Convection‐Permitting Scales
This paper introduces an Earth system modeling testbed for predicting aerosols and aerosol‐cloud interactions (ACIs) at convection‐permitting scales. Using the Energy Exascale Earth System Model (E3SM) version 2 with a four‐mode Modal Aerosol Module, we conduct simulations at 3.25 km resolution on a regionally refined mesh (RRM) across four regions with distinct aerosol and cloud regimes. Results are compared with the standard 100 km E3SM configuration and evaluated against satellite, aircraft, and ground‐based observations. We find that increasing model resolution improves heavy precipitation simulation but amplifies positive bias in light drizzle at coarse resolution. These resolution‐induced changes affect cloud and aerosol properties to varying degrees across regions. Generally, cloud cover and liquid water path (LWP) show better agreement with satellite retrievals at 3.25 km, though surface‐based comparisons suggest otherwise. Aerosol composition remains poorly represented at both resolutions. The RRM increases Aitken mode aerosol number concentrations via enhanced new particle formation. However, accumulation mode aerosols are decreased at higher resolution as aerosol removals become more efficient. This partially contributes to fewer cloud condensation nuclei (CCN) and lower cloud droplet number concentrations (N d ), which produces larger model biases in some scenarios. These findings suggest that solely increasing horizontal resolution to kilometer scales is insufficient to broadly improve aerosol and cloud predictions without concurrent advancements in physical and chemical process representations. Nonetheless, the RRM moderately improves key ACI relationships such as CCN‐N d correlation, reflecting enhanced aerosol activation representation. The LWP‐N d relationship is also better captured by RRM, suggesting a better characterization of LWP adjustment.
Genome-scale engineering of Saccharomyces cerevisiae with single-nucleotide precision
Here, we developed a CRISPR/Cas9 and homology-directed-repair assisted genome-scale engineering method named CHAnGE that can rapidly output tens of thousands of specific genetic variants in yeast. More than 98% of target sequences were efficiently edited with an average frequency of 82%. We validate the single-nucleotide resolution genome-editing capability of this technology by creating a genome-wide gene disruption collection and apply our method to improve tolerance to growth inhibitors.
Black carbon absorption at the global scale is affected by particle-scale diversity in composition
Atmospheric black carbon (BC) exerts a strong, but uncertain, warming effect on the climate. BC that is coated with non-absorbing material absorbs more strongly than the same amount of BC in an uncoated particle, but the magnitude of this absorption enhancement (E abs ) is not well constrained. Modelling studies and laboratory measurements have found stronger absorption enhancement than has been observed in the atmosphere. Here, using a particle-resolved aerosol model to simulate diverse BC populations, we show that absorption is overestimated by as much as a factor of two if diversity is neglected and population-averaged composition is assumed across all BC-containing particles. If, instead, composition diversity is resolved, we find E abs =1-1.5 at low relative humidity, consistent with ambient observations. This study offers not only an explanation for the discrepancy between modelled and observed absorption enhancement, but also demonstrates how particle-scale simulations can be used to develop relationships for global-scale models.
Scaling between magnetic field and temperature in the high-temperature superconductor BaFe 2 (As 1- x P x ) 2
Many exotic metallic systems have a resistivity that varies linearly with temperature, and the physics behind this is thought to be connected to high-temperature superconductivity in the cuprates and iron pnictides. Although this phenomenon has attracted considerable attention, it is unclear how the relevant physics manifests in other transport properties, for example their response to an applied magnetic field. We report measurements of the high-field magnetoresistance of the iron pnictide superconductor BaFe 2 (As 1- x P x ) 2 and find that it obeys an unusual scaling relationship between applied magnetic field and temperature, with a conversion factor given simply by the ratio of the Bohr magneton and the Boltzmann constant. This suggests that magnetic fields probe the same physics that gives rise to the T -linear resistivity, providing a new experimental clue to this long-standing puzzle.
Part-scale evolution of fine-scale microstructural heterogeneity in solid-state additive manufacturing
Current solid-state additive manufacturing methods, refined through costly and time-consuming trial and error, have spurred interest in computational models that replicate material behavior under typical thermomechanical conditions (e.g., strain-rate ~ 102 s−1). These models, however, struggle to capture time-dependent microstructural evolution. In this work, Additive Friction-Stir Deposition (AFSD) is used as a representative case study for part-scale quantification of microstructure evolution at a fine spatial resolution (200 μm) by examining a liquid-nitrogen-cooled stop-action build via energy-dispersive X-ray diffraction coupled with a multi-channel detector. These results inform modeling efforts by linking process asymmetry to stored plastic strain, residual elastic strain, and texture development, and unlike current state-of-the-art characterization methods (e.g., EBSD or neutron diffraction), this approach provides both the spatial resolution and collection efficiency necessary to quantify fine-scale microstructural heterogeneity over large component volumes. As such, this technique provides essential validation data for computational models, e.g., crystal plasticity, enabling future prediction of heterogeneous behavior in AFSD and other additive manufacturing processes.
Non-scaling behavior of electroosmotic flow in voltage-gated nanopores
Ionic size effects and electrostatic correlations result in the non-monotonic dependence of the electrical conductivity on the pore size. For ion transport at a high gating voltage, the conductivity oscillates with the pore size due to a significant overlap of the electric double layers.