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Results for “Correlation analysis”

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

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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Uncertainty analysis of steady-state measurements with a hot-filament type calorimetric emissometer

Calorimetric emissometers measure total hemispherical emissivity by measuring the heat transferred from a heated sample to its surroundings under a vacuum. The accuracy of emissometers standardized by the ASTM C835-06 are well understood. This work uses the Guide to the Evaluation of Uncertainty in Measurement (GUM) for the propagation uncertainties for an ASTM compliant emissometer. The GUM method was able to develop a measurement model and expressions to determine the uncertainty for other emissometers of this type. Data on ‘as-received’ Hastelloy X was used to develop a detailed uncertainty analysis of the emissivity measurement. Data on ‘as-received’ SS 347 and sandblasted A387 Gr. 91 and previous data by the group on A508/A533B were used to determine uncertainty over the ranges 0.16 to 0.81. For all samples, relative uncertainties in emissivities varied from 0.77% to 2.5% when using a fluxgate magnetometer sensor (FMS) to measure the DC heating current. Data on Hastelloy X using a Hall-effect sensor for DC current and low alloy steel showed the DC current and voltage across the test section to be dominate sources of uncertainty. When these sources were reduced, the specimen temperature and the surface area of the test sections were main sources of uncertainty in the emissivity, especially at higher temperatures. As thermal expansion of the surface was considered in the calculations, correlation between specimen temperature and surface area was examined. It was found to be a small contribution to emissivity's uncertainty despite the differences in linear CTE and its uncertainty for the materials analyzed in this study. For low temperatures, the chamber temperature can be a significant source of uncertainty if not sufficiently cooled. The GUM was also briefly compared to uncertainty from the 2nd and 3rd expansions of the Taylor series. We found that the results were the same when rounding to two significant figures.

42 ENGINEERING↗
DOE OSTI2022

Effectiveness of fat grafting in scar reduction: A systematic review and meta‐analysis

Abstract Background Scar brings great physical and mental pain to patients. Fat grafting may be a new and simple way to treat scar. This review aimed to systematically evaluate the correlation between fat grafting and scar reduction. Methods The author searched Chinese and English literature databases such as CNKI, Wanfang Data, Cqvip, Pubmed, Web of Science, Embase, CBM, etc. for articles published in the period from 2011 to 2021 about the randomized controlled trials (RCTs) to assess the effect of fat grating on scar reduction, and then performed meta‐analysis with Review Manager 5.4. Results A total of nine articles were included in the assessment of the effect of fat grafting on scar reduction, with meta‐analysis suggesting statistical significance (OR = 5.63, 95% CI: 3.01–10.53, p < 0.01). There was statistical significance in the difference observed between the simple fat grating group ( p = 0.004) and the group of existing therapies combined with fat grafting ( p < 0.0001). Conclusion Fat grafting may be a good method for scar treatment, especially when it's combined with other therapies. Still, due to the limitations of included RCTs, more large‐scale high‐quality RCTs must be carried out before solid conclusions can be drawn.

Zhang, Xiaoyuan↗
DOE OSTI2022

Ion Correlations and Partial Ionicities in the Lamellar Phases of Block Copolymeric Ionic Liquids

Recently, significant interest has arisen on the impact of dynamical ion correlations on the conductivity and transport properties of polymeric electrolyte materials. It has been hypothesized that confining ion motion to narrow channels may reduce such ion correlations and enhance the resulting ionic conductivity. Motivated by such considerations, in this study we used a multiscale simulation framework to study the dynamical ion correlations in the microphase-separated lamella phase of block copolymeric ionic liquids and compare with the corresponding results for homopolymeric systems. We probed the influence of ion correlations through the partial ionicity, Δ, which quantifies the ratio of true conductivity to the ideal, Nernst–Einstein conductivity for the anion-related contributions. Consistent with our original hypothesis, our results demonstrate that the partial ionicity relating to the mobile anions is much larger in the lamella phases of block copolymers compared to that in homopolymers. Analysis of the distinct conductivity contributions demonstrates that such results arise as a result of an intricate compensation among the nonideal dynamical correlations relating to anions in lamella phases. Overall, our results suggest that self-assembled phases of block copolymers may provide an avenue to tune the dynamical ion correlations in polymer electrolyte systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Drought Shifts Sorghum Root Metabolite and Microbiome Profiles and Enriches for Pipecolic Acid

Plant-associated microbial communities shift in composition as a result of environmental perturbations, such as drought. It has been shown that Actinobacteria are enriched in plant roots and rhizospheres during drought stress. However, the correlations between microbiome dynamics and plant response to drought are poorly understood. Here we apply a combination of bacterial community composition analysis and plant metabolite profiling in Sorghum bicolor roots, rhizospheres, and soil during drought and drought recovery to investigate potential contributions of host metabolism to shifts in bacterial composition. Our results provide a detailed view of metabolic shifts across the plant root during drought and show that the response to rewatering differs between root and soil; additionally, we identify drought-responsive metabolites that are highly correlated with the observed changes in Actinobacteria abundance. Furthermore, we find that pipecolic acid is a drought-enriched metabolite in sorghum roots, and that exogenous application of pipecolic acid inhibits root growth. Finally, we show that this activity functions independent of the systemic acquired resistance pathway and has the potential to impact Actinobacterial taxa within the root microbiome.

165 RRNA↗
DOE OSTI2025

Preliminary modeling of triply periodic minimal surface (TPMS) structures using RELAP5-3D

With the United States Department of Energy (DOE)’s goal of quadrupling the nation’s nuclear energy supply by 2050, and with the Advanced Fuels Campaign pushing for new types of advanced reactor fuels and geometries, the need has arisen for new nuclear fuel designs. One such design is to swap out current nuclear fuel geometries in exchange for another type of geometry, called a Triply Periodic Minimal Surface (TPMS). TPMSs are self-supporting, infinitely repeating lattices—attributes that lend themselves well to additive manufacturing. These surfaces also possess enhanced heat transfer properties thanks to their internal area changes and large surface-area-to-volume ratios. Their drawback, however, is an increased pressure drop. Given the small amount of correlations and data (Reynolds numbers in the 2,000–8,000 range), and the minimal amount of experience so far obtained by modeling TPMS structures using 1D systems codes such as the Reactor Excursion and Leak Analysis Program (RELAP5-3D), further research into this topic was needed. Using data from the University of Wisconsin - Madison (UW), curve fits were created for both a Heat Transfer Coefficient (HTC) correlation and a Darcy friction factor empirical coefficient correlation. The curves’ coefficients and multipliers were then output and utilized in RELAP5-3D models of two upcoming experiments—Flow Loop for INFLUX Pressure drop (FLIP) and Microreactor Agile Non-nuclear Experimental Test (MAGNET)—aimed at increasing the available data for Reynolds numbers to the 16,000–36,000 range for TPMS structures. The models were run under the conditions utilized by a Computational Fluid Dynamics (CFD) analysis performed by another group at Idaho National Laboratory. Only CFD pressure drop values were obtained from the FLIP test, and those values showed that the RELAP5-3D models had a lower rate of pressure increase in comparison to the CFD values. In addition, there seemed to be a vertical shift upward in the pressure drop for both models whenever the TPMS porosity decreased, and the RELAP5-3D models showed a higher vertical shift in comparison to the CFD values. The MAGNET results did not correspond to any CFD or experimental results against which they could be compared, so they were instead compared against the proposed CFD input conditions. These values were then compared with each other to make sure the model seemed to be performing as expected, paving the way for future tests that can be run for the purpose of further analyses and comparisons. The pressure drop increased with temperature and mass flow rate independently. The temperature change would decrease with increasing mass flow rate and temperature, which was just as we expected based on the fact that the lower viscosity and decreased density would result in higher friction and churning losses. The last metric that was assessed was the enthalpy flow change, which increased with increasing mass flow rate and decreasing temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks

In this report computational screening was employed to calculate the enantioseparation capabilities of 45 functionalized homochiral metal–organic frameworks (FHMOFs), and machine learning (ML) and molecular fingerprint (MF) techniques were used to find new FHMOFs with high performance. With increasing temperature, the enantioselectivities for (R,S)-1,3-dimethyl-1,2-propadiene are improved. The “glove effect” in the chiral pockets was proposed to explain the correlations between the steric effect of functional groups and performance of FHMOFs. Moreover, the neighborhood component analysis and RDKit/MACCS MFs show the highest predictive effect on enantioselectivities among the four ML classification algorithms with nine MFs that were tested. Based on the importance of MF, 85 new FHMOFs were designed, and a newly designed FHMOF, NO 2 -NHOH-FHMOF, with high similarity to the optimal MFs achieved improved chiral separation performance, with enantioselectivities of 85%. The design principles and new chiral pockets obtained by ML and MFs could facilitate the development of new materials for chiral separation.

molecular fingerprint↗
DOE OSTI2023

Assessing mechanisms for microbial taxa and community dynamics using process models

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Mesoscopic-scale complexity in macroscopically-uniform plastic flow of an Al 0.3 CoCrFeNi high-entropy alloy

The concept of a smooth and homogeneous plastic flow of solids is nowadays constantly challenged by various observations of the self-organization of crystal defects on mesoscopic scales pertaining, e.g., to acoustic emission or the evolution of the local strain field. Such investigations would be of particular interest for High-Entropy Alloys (HEAs) characterized by extremely complex microstructures. However, the complexity of their deformation has been only studied in relation to the jerky flow. The present work explores a mesoscale complexity of the macroscopically-smooth plastic flow of an Al 0.3 CoCrFeNi alloy. Here, an inclusive approach involving various experimental methods and complementary nonlinear analyses allowed to reveal transitions between distinct dynamical regimes, which may be assimilated with noises of different colors, in particular the blue noise that is rarely observed in complex systems, and various kinds of reddened behavior. Such findings provide significant new insights into the micro/macro transition in the deformation behavior of HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evaluation of CMIP6 models in simulating the statistics of extreme precipitation over Eastern Africa

We report the Eastern Africa region experiences frequent extreme precipitation events that can cause destruction of property and environment, and loss of lives. Thus, there is a need to understand how these events may change in the future and how well the global climate models that are used to make projections can simulate precipitation extremes in this region before they can be used in downscaling or flood and drought impact assessment studies. In this work, we evaluated the ability of sixteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models to simulate present-day precipitation extremes over the Eastern Africa region during the two rainy seasons (March–May and September–November). We used nine extreme precipitation indices (including seven (one) indices of wet (dry) extremes) defined by the Expert Team on Climate Change Detection and Indices. The CMIP6 models were evaluated against two gridded observation datasets: Global Precipitation Climatology Project One-Degree Daily Dataset and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis 3B42. Three model performance metrics (percentage bias, normalized root-mean-square error, and pattern correlation coefficient) were employed to further assess the strengths and weakness of the models. Our results show that the multi-model ensemble mean generally provides a better representation of observed precipitation and related extremes compared to individual models when considering all metrics and seasons. Several consistent biases are evident across CMIP6 models, which tend to overestimate the total-wet day precipitation and consecutive wet days, and underestimate very wet days and maximum 5-day precipitation in both seasons. Furthermore, no single model consistently performs best, model performance varies with the season and index under consideration and is generally independent of horizontal resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

3D analysis of abnormal grain growth in calcia doped alumina in the presence of large pores

Abnormal grain growth has been previously found to increase with the inclusion of large pores (∼60 µm in diameter) in 80 ppm calcium doped alumina. However, the two-dimensional analysis could not accurately describe the proximity of the abnormal grains and pores to establish a correlation. This study uses laboratory-based diffraction contrast tomography and x-ray computed tomography to spatially map the pores and abnormal grains in 3D. A preference towards the formation of abnormal grains near large pores is found when compared to all potential sites. This finding supports that the pores may be a nucleation site for complexion transitions that promote abnormal grain growth. The growth of the abnormal grains in a subsequent heat treatment at 1600°C for 16 hrs was also studied. The elongation along the principal axes is similar for both small and large grains, again supporting that abnormal grain growth was facilitated by a complexion transition.

Abnormal grain growth↗
DOE OSTI2022

Triacetic Acid Lactone and 4-Hydroxycoumarin as Bioprivileged Molecules for the Development of Performance-Advantaged Organic Corrosion Inhibitors

Biomass conversion, especially the development of bioprivileged molecules utilizing integration of biological and chemical processes, has shown potential to produce novel chemicals with enhanced properties. Here, organic corrosion inhibitors based on triacetic acid lactone and 4-hydroxycoumarin have been synthesized in good yield and tested for corrosion inhibition on mild steel in both sulfuric acid and hydrochloric acid. Sixteen novel corrosion inhibitors derived from triacetic acid lactone and 4-hydroxycoumarin were efficiently synthesized and twelve of them showed high corrosion inhibition efficiency as confirmed by electrochemical impedance spectroscopy (giving values greater than 78%) and polarization analysis. While triacetic acid lactone-based compounds showed good corrosion inhibition performance, the 4-hydroxycoumarin-based compounds showed further improvement in corrosion inhibition performance. Scanning electron microscopy (SEM) analysis of the mild steel coupon in the presence of selected inhibitors showed that corrosion was significantly diminished, with complementary X-ray photoelectron spectroscopy (XPS) analysis suggesting the inhibitor molecules strongly adsorbed on the steel surface. Quantum chemical calculations showed poor correlation between calculated parameters and the performance of these molecules. This large set of corrosion inhibitors containing a dozen promising corrosion inhibitors is useful for future rational design of corrosion inhibitors. In conclusion, the results demonstrate a new direction for the development of bioprivileged molecules.

09 BIOMASS FUELS↗
DOE OSTI2024

Unveiling Hidden Shake-Up Features in the Uranyl M 4 -Edge Spectrum

The M 4,5 -edge high energy resolution X-ray absorption near-edge structure (HR-XANES) spectra of actinyls offer valuable insights into the electronic structure and bonding properties of heavy-element complexes. To conduct a comprehensive spectral analysis, it is essential to employ computational methods that accurately account for relativistic effects and electron correlation. In this work, we utilize variational relativistic multireference configurational interaction methods to compute and analyze the X-ray M 4 -edge absorption spectrum of uranyl. By employing these advanced computational techniques, we achieve excellent agreement between the calculated spectral features and experimental observations. Moreover, the calculations unveil significant shake-up features, which arise from the intricate interplay between strongly correlated 3d core-electron and ligand excitations. This research provides important theoretical insights into the spectral characteristics of heavy-element complexes. Furthermore, it establishes the foundation for utilizing M 4,5 -edge spectroscopy as a means to investigate the chemical activities of such complexes. By leveraging this technique, we can gain a deeper understanding of the bonding behavior and reactivity of heavy-element compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Viscosity in water from first-principles and deep-neural-network simulations

Abstract We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory (DFT). In order to cope with the long simulation times necessary to achieve an acceptable statistical accuracy, our ab initio approach is enhanced with deep-neural-network potentials (NNP). This approach is first validated against AIMD results, obtained by using the Perdew–Burke–Ernzerhof (PBE) exchange-correlation functional and paying careful attention to crucial, yet often overlooked, aspects of the statistical data analysis. Then, we train a second NNP to a dataset generated from the Strongly Constrained and Appropriately Normed (SCAN) functional. Once the error resulting from the imperfect prediction of the melting line is offset by referring the simulated temperature to the theoretical melting one, our SCAN predictions of the shear viscosity of water are in very good agreement with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A non-perturbative pairwise-additive analysis of charge transfer contributions to intermolecular interaction energies

Energy decomposition analysis (EDA) based on absolutely localized molecular orbitals (ALMOs) decomposes the interaction energy between molecules into physically interpretable components like geometry distortion, frozen interactions, polarization, and charge transfer (CT, also sometimes called charge delocalization) interactions. In this work, a numerically exact scheme to decompose the CT interaction energy into pairwise additive terms is introduced for the ALMO-EDA using density functional theory. Unlike perturbative pairwise charge-decomposition analysis, the new approach does not break down for strongly interacting systems, or show significant exchange–correlation functional dependence in the decomposed energy components. Both the energy lowering and the charge flow associated with CT can be decomposed. Complementary occupied–virtual orbital pairs (COVPs) that capture the dominant donor and acceptor CT orbitals are obtained for the new decomposition. It is applied to systems with different types of interactions including DNA base-pairs, borane-ammonia adducts, and transition metal hexacarbonyls. While consistent with most existing understanding of the nature of CT in these systems, we report the results also reveal some new insights into the origin of trends in donor–acceptor interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Revealing the potential of nickel zinc ferrite: Facile synthesis and cost-effective anode for lithium-ion batteries

The increasing demand for lithium-ion batteries (LIBs) underscores the need for cost-effective alternative anode materials to ensure efficient Li-ion storage, given their pivotal role in various industries. This research focuses on the facile synthesis of nickel zinc ferrite (NZFO: Ni 0.65 Zn 0.35 Fe 2 O 4 ) and conducts comprehensive electrochemical analyses to evaluate its potential as a high-capacity alternative anode material for LIBs. The NZFO-CMR [sodium carboxymethyl cellulose (2%) and styrene-butadiene rubber (1%)] exhibited an initial delithiated capacity of ∼1232 mA h g −1 and maintained a stable capacity of around 358 mA h g −1 , along with an average Coulombic efficiency of 99.6% over 200 cycles. Cyclic voltammetry analysis revealed that Li-ion insertion was predominantly governed by ion diffusion, and the consistent correlation observed in electrochemical impedance spectroscopy spectra indicated stable electrochemical behavior throughout cycling. The facile synthesis approach and reasonable electrochemical performance of NZFO suggest its potential as an alternative anode material for advancing LIB's technology.

25 ENERGY STORAGE↗
DOE OSTI2023

Observing signals of spectral features in the cosmic-ray positrons and electrons from Milky Way pulsars

The Alpha Magnetic Spectrometer (AMS-02) has provided unprecedented precision measurements of the electron and positron cosmic-ray fluxes and the positron fraction spectrum. At the higher energies, sources as energetic local pulsars, may contribute to both cosmic-ray species. The discreteness of the source population, can result in features both on the positron fraction measurement and in the respective electron and positron spectra. For the latter, those would coincide in energy and would contrast predictions of smooth spectra as from particle dark matter. In this work, using a library of pulsar population models for the local part of the Milky Way, we perform a power-spectrum analysis on the cosmic-ray positron fraction. We also develop a technique to cross-correlate the electron and positron fluxes. We show that both such analyses, can be used to search statistically for the presence of spectral wiggles in the cosmic-ray data. For a significant fraction of our pulsar simulations, those techniques are already sensitive enough to give a signal for the presence of those features above the regular noise, with forthcoming observations making them even more sensitive. Lastly, by cross-correlating the AMS-02 electron and positron spectra, we find an intriguing first hint for a positive correlation between them, of the kind expected by a population of local pulsars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Quasiclassical evaluation of gluon saturation induced helicity effects

At sub-eikonal order in the high-energy limit, helicity dependences are generally contained in the transverse components of the gluon field. In the gluon saturation regime, novel helicity effects arise from the nonlinear interaction between the eikonal-order longitudinal gluon field and the sub-eikonal-order transverse gluon field. We derive this saturation induced helicity-dependent field both by solving the classical Yang-Mills equations and through direct diagrammatic calculations. Our analysis shows that the saturation induced helicity effect is intrinsically a two-particle (or multiparticle) correlation effect, rather than a single-particle distribution effect. Furthermore, we evaluate this effect in the context of double-spin asymmetry for incoherent diffractive dijet production in longitudinally polarized electron-nucleus collisions, using a simplified helicity-extended McLerran-Venugopalan model. We find that the saturation induced helicity effect further suppresses the back-to-back peak in the dijet azimuthal angle correlation, with a magnitude comparable to that of the direct helicity effect. This gluon saturation induced helicity effect may offer a novel avenue to probe gluon saturation in polarized collisions. Published by the American Physical Society 2025

Li, Ming (ORCID:0000000195509691)↗
DOE OSTI2022

Machine learning reveals key ion selectivity mechanisms in polymeric membranes with subnanometer pores

Designing single-species selective membranes for high-precision separations requires a fundamental understanding of the molecular interactions governing solute transport. Here, we comprehensively assess molecular-level features that influence the separation of 18 different anions by nanoporous cellulose acetate membranes. Our analysis identifies the limitations of bulk solvation characteristics to explain ion transport, highlighted by the poor correlation between hydration energy and the measured permselectivity (R 2 = 0.37). Entropy-enthalpy compensation, spanning 40 kilojoules per mole, leads to a free-energy barrier (ΔG‡) variation of only ~8 kilojoules per mole across all anions. We apply machine learning to elucidate descriptors for energetic barriers from a set of 126 collected features. Notably, electrostatic features account for 75% of the overall features used to describe ΔG‡, despite the relatively uncharged state of cellulose acetate. Our work presents an approach for studying ion transport across nanoporous membranes that could enable the design of ion-selective membranes.

36 MATERIALS SCIENCE↗