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At least 217 records · Page 12

Node Distortions as a Means of Defect Engineering in Zr-Based MOFs

Defect engineering in Zr-based metal–organic frameworks (Zr-MOFs) has focused primarily on missing-linker defects. However, recent studies suggest that node dehydroxylation–which creates distortions and coordinatively unsaturated Zr sites (Zr cus )–may have a more significant impact on properties. The present work uses pair distribution function (PDF) and thermogravimetric analysis coupled with systematic defect manipulation to study the effect of node dehydroxylation and missing-linker defects in UiO-66. By employing rapid heat treatment (RHT) under humid flow, we tracked the transition from high-symmetry [Zr 6 O 4 (OH) 4 ] 12+ to distorted [Zr 6 O 6 ] 12+ nodes. This structural evolution significantly improves As(V) uptake, whereas increasing the number of missing linkers–via chemical treatment or RHT of mixed-ligand frameworks–fails to enhance performance. Crucially, our detection of distorted nodes in as-synthesized UiO-66 also raises the possibility that these defects were silently present in many earlier studies that span various applications, where their role in governing performance may have been inadvertently overlooked. The present study challenges the prevailing “missing-linker” paradigm and establishes cluster dehydroxylation as a defect-engineering strategy to enhance Lewis-acidic performance in Zr-MOFs.

Adsorption↗

Investigation of Causal Relationships of the Cross‐Scale Wave Coupling Through Information Theoretical Approach

On 2015 October 2, MMS spacecraft observed an electron micro-injection event near the southern hemispheric high-altitude cusp, coinciding with intense wave activity across several frequency bands. Here, we investigated the MMS magnetic field and plasma during this event to explore cross-scale coupling among the wave modes. Employing the Hilbert-Huang transform, we perform an empirical mode decomposition to extract frequencies and amplitudes of the intrinsic mode functions (IMFs). In this analysis, we establish both linear and nonlinear relationships and examine the information transfer between the IMFs. Notably, the transfer entropy suggests that high frequency ion cyclotron waves may be driven by the mirror mode structures. Our case study effectively demonstrates the utility of the information theory based tools for studying cross-scale wave coupling phenomena.

Rivera, Elmer C. [Andrews University, Berrien Spri↗

Active site design enables industrial scale H 2 O 2 electrosynthesis with metal-free catalysts

The electrosynthesis of hydrogen peroxide (H 2 O 2 ) via a two-electron oxygen reduction reaction enables decentralized H 2 O 2 production. While metal-free carbon catalysts are sustainable and low-cost, their performance is hindered by poorly defined active sites and uncontrolled defect states. Here, we resolve these challenges through active site design and catalyst screening using fluorine (F) and nitrogen (N) codoped carbons as model materials. Statistical analysis combined with density functional theoretical calculations reveals that F-induced structural modification and defect passivation optimize OOH* binding, with F-doping and adjacent F atoms predominantly lowering abs ΔG(OOH*). Experimental results confirm that semi-ionic C–F bonds passivate defects in nitrogen-doped carbon, enhancing catalytic activity and durability. The resulting (N, F)-codoped carbon achieves nearly 100% H 2 O 2 selectivity at 0.5–0.65 V versus the reversible hydrogen electrode and maintains > 95% across 0.01–0.65 V versus the reversible hydrogen electrode. In an electrolyzer, (N, F)-codoped carbon exhibits an H 2 O 2 yield rate of 74.35 mol g cat. −1 h -1 and sustains 300 mA cm -2 for 105 hours with ~95% faradaic efficiency. Coupling the two-electron oxygen reduction reaction with methanol oxidation further reduces cell voltage and enhances productivity. This work provides a means to design efficient catalysts for industrial H 2 O 2 electrosynthesis.

H2O2 electrosynthesis↗

A compendium of human gene functions derived from evolutionary modelling

A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms 1,2 . Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗

Computational insights into hydrogen adsorption energies on medium-entropy oxides

High entropy oxides (HEOs) have emerged as promising catalysts for several important chemical transformations including alkane activation. Hydrogen adsorption energy (HAE) has been used as a key descriptor for many reactions including methane C–H activation and hydrogen evolution reactions. Hence, understanding the relationship between HAEs and the surface chemistry of HEO surfaces could lay the foundation for meaningful correlations among methane C–H activation, HAE, and the complex, local environment of HEO surfaces. Here, we used a medium-entropy oxide as a prototypical system – Mg 0.25 Ni 0.25 Cu 0.25 Zn 0.25 O with a rock-salt structure – to interrogate these relationships. We sampled 2000 different surfaces of its (100) plane and calculated the HAEs at randomly chosen surface O sites using density functional theory (DFT). Our analysis of the 2000 data points reveals that the HAEs at the surface O sites are significantly influenced by the local environment around the adsorption sites, particularly the nature of the metal atom directly below the surface O site where H adsorbs. After comparing several popular graph-neural-network-based machine learning models, we found that the DimeNet++ model performed best achieving satisfactory accuracy in predicting HAEs for both Mg 0.25 Ni 0.25 Cu 0.25 Zn 0.25 O and slightly varied compositions. Our work underscores the promise of such models and the need for further refinement to address the complexity of HEOs.

Song, Haohong [Vanderbilt Univ., Nashville, TN (Un↗

Negative linear compressibility and complex phase behaviour in 7 Li 2 CO 3

We present a combination of neutron powder-diffraction measurements demonstrating negative linear compressibility and irregular thermal expansion in 7 Li 2 CO 3 . This is shown to be due to an interplay between the tilting of the rigid carbonate group and the shear strain in the unit cell, which leads to a first-order transition from monoclinic to hexagonal symmetry. The phase evolution is shown to be highly sensitive to the level of hydrostaticity in the sample. Under hydrostatic conditions, the sample begins transformation at 8.5 GPa leading to a change from tetrahedral to octahedral Li coordination. Symmetry adapted basis mode analysis, combined with density functional theoretical (DFT) calculations and Raman spectroscopy, is used to show that this transition is reverse proper ferroelastic in nature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Least H 2 norm updating of quadratic interpolation models for derivative-free trust-region algorithms

One particular class of derivative-free optimization algorithms is trust-region algorithms based on quadratic models given by the under-determined interpolation. Different techniques in updating the quadratic model from iteration to iteration will give different interpolation models. We propose a new way to update the quadratic model by minimizing the $H^{2}$ norm of the difference between neighboring quadratic models. The motivation for applying the $H^{2}$ norm is given. The theoretical properties of our new updating technique are also presented. We propose the projection in the sense of $H^{2}$ norm and the interpolation error analysis of our model function. We obtain the coefficients of the quadratic model function using the Karush–Kuhn–Tucker (KKT) conditions. Numerical results show the advantages of our model on the test set considered, and the derivative-free algorithms based on our least $H^{2}$ norm updating quadratic model functions can solve test problems with fewer function evaluations than the algorithm based on the least Frobenius norm updating model and the other compared methods.

derivative-free optimization↗

Statistical properties of filaments in the cosmic web

ABSTRACT In the context of the cosmological and constrained Exploring the Local Universe with the reConstructed Initial Density field (ELUCID) simulation, this study explores the statistical characteristics of filaments within the cosmic web, focussing on aspects such as the distribution of filament lengths and their radial density profiles. Using the classification of the cosmic web environment through the Hessian matrix of the density field, our primary focus is on how cosmic structures react to the two variables $R_{\rm s}$ and $\lambda _{\rm th}$. The findings show that the volume fractions of knots, filaments, sheets, and voids are highly influenced by the threshold parameter $\lambda _{\rm th}$, with only a slight influence from the smoothing length $R_{\rm s}$. The central axis of the cylindrical filament is pinpointed using the medial-axis thinning algorithm of the COsmic Web Skeleton (COWS) method. It is observed that median filament lengths tend to increase as the smoothing lengths increase. Analysis of filament length functions at different values of $R_{\rm s}$ indicates a reduction in shorter filaments and an increase in longer filaments as $R_{\rm s}$ increases, peaking around $2.5R_{\rm s}$. The study also shows that the radial density profiles of filaments are markedly affected by the parameters $R_{\rm s}$ and $\lambda _{\rm th}$, showing a valley at approximately $2R_{\rm s}$, with increases in the threshold leading to higher amplitudes of the density profile. Moreover, shorter filaments tend to have denser profiles than their longer counterparts.

Zhang, Youcai (ORCID:0000000319674091)↗

Tracking copper nanofiller evolution in polysiloxane during processing into SiOC ceramic

Polymer-derived ceramics (PDCs) remain at the forefront of research for a variety of applications including ultra-high-temperature ceramics, energy storage and functional coatings. Despite their wide use, questions remain about the complex structural transition from polymer to ceramic and how local structure influences the final microstructure and resulting properties. This is further complicated when nanofillers are introduced to tailor structural and functional properties, as nanoparticle surfaces can interact with the matrix and influence the resulting structure. The inclusion of crystalline nanofiller produces a mixed crystalline–amorphous composite, which poses characterization challenges. With this study, we aim to address these challenges with a local-scale structural study that probes changes in a polysiloxane matrix with incorporated copper nanofiller. Composites were processed at three unique temperatures to capture mixing, pyrolysis and initial crystallization stages for the pre-ceramic polymer. We observed the evolution of the nanofiller with electron microscopy and applied synchrotron X-ray diffraction with differential pair distribution function (d-PDF) analysis to monitor changes in the matrix's local structure and interactions with the nanofiller. The application of the d-PDF to PDC materials is novel and informs future studies to understand interfacial interactions between nanofiller and matrix throughout PDC processing.

Chemistry↗

Machine learning inversion from scattering for mechanically driven polymers

A machine learning inversion method is developed for analyzing scattering functions of mechanically driven polymers and extracting the corresponding feature parameters, which include energy parameters and conformation variables. The polymer is modeled as a chain of fixed-length bonds constrained by bending energy, and it is subject to external forces such as stretching and shear. We generate a data set consisting of random combinations of energy parameters, including bending modulus, stretching and shear force, along with Monte Carlo-calculated scattering functions and conformation variables such as end-to-end distance, radius of gyration and off-diagonal component of the gyration tensor. The effects of the energy parameters on the polymer are captured by the scattering function, and principal component analysis ensures the feasibility of the machine learning inversion. Finally, we train a Gaussian process regressor using part of the data set as a training set and validate the trained regressor for inversion using the rest of the data. The regressor successfully extracts the feature parameters.

Gaussian process regressors↗

New results in the CTEQ-TEA global analysis of parton distributions in the nucleon

This report summarizes the latest developments in the CTEQ-TEA global analysis of parton distribution functions (PDFs) in the nucleon. The focus is on recent NNLO fits to high-precision LHC data at 8 and 13 TeV, including Drell–Yan, jet, and top-quark pair production, pursued on the way toward the release of the new generation of CTEQ-TEA general-purpose PDFs. The report also discusses advancements in statistical and numerical methods for PDF determination and uncertainty quantification, highlighting the importance of robust and replicable uncertainties for high-stakes observables. Additionally, it covers phenomenological studies related to PDF determination, such as the interplay of experimental constraints, exploration of correlations between high-x nucleon sea and low-energy parity-violating measurements, fitted charm in the nucleon, the photon PDF in the neutron, and simultaneous SMEFT-PDF analyses.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cyber-informed Engineering Microgrid Analysis Tool

The Cyber-Informed Engineering Microgrid Analysis Tool (CIEMAT) leverages the Department of Energy’s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a microgrid installations, the criticality of those functions, the impacts of denial, disruption or misuse of those functions on the microgrid and dependent functions, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, microgrid designers and operators can quickly identify appropriate engineering mitigations to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.

Wright, VirginiaL [Idaho National Laboratory (INL)↗

Cyber-informed Engineering Battery Analysis Tool

The Cyber-Informed Engineering Battery Analysis Tool (CIEBAT) leverages the Department of Energy’s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a BESS installation, the criticality of those functions, the impacts of denial, disruption or misuse of those functions within the BESS system, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, BESS designers and operators can quickly identify appropriate engineering mitigation opportunities to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.

Lampe, BenjaminR [Idaho National Laboratory (INL),↗

Optimization of the artificial viscosity in Lagrangian staggered discretization codes. Modeling 1D stand-alone shock - case study

We have developed new measures of errors for numerical shock. The new approach is based on analysis of the structure function, and separation of the errors related to oscillations and shock width, which also include error in the position of the ”center” of the numerical shock. We have demonstrated that those measures correctly characterize the numerical solution. We introduced an objective function in, which both types of errors are weighted, and presented optimal values of the coefficients of the linear and quadratic viscosity for different weights and different Mach numbers.

97 MATHEMATICS AND COMPUTING↗

Probing the Coherence of Metal Absorbers toward Background Quasar Pairs

Abstract We investigate the spatial coherence of metal absorption lines in the circumgalactic medium using 4115 quasar pairs from Sloan Digital Sky Survey DR16. We identify 184 Mg ii (15 with dual detections) and 50 C iv (11 with dual detections) absorber pairs. The fraction of pairs with fractional equivalent width difference δW r ≤ 0.5 declines with projected separation: for Mg ii , it drops from ∼52% at 0–25 kpc to ∼7% at 100–200 kpc, while for C iv , it decreases from ∼100% to ∼21% over 0–200 kpc. In every separation bin, C iv absorbers with δW r ≤ 0.5 maintain a higher fraction than Mg ii absorbers. Similar results are obtained when the nondetections are treated as 2 σ W r upper limits in a survival analysis. The transverse autocorrelation function shows strong Mg ii clustering within 0–25 kpc, whereas the C iv excess remains relatively flat out to ∼100 kpc. These findings suggest that high-ionization C iv gas retains coherence over larger transverse scales than low-ionization Mg ii gas, in agreement with previous lensed quasar and high-resolution studies.

Li, Jing [Guangxi University] (ORCID:0009000148751↗

X-ray and molecular dynamics study of the temperature-dependent structure of molten NaF-Zr⁢F 4

The local atomic structure of NaF-Zr⁢F 4 (53–47 mol%) molten system and its evolution with temperature are examined with x-ray scattering measurements which are then used to validate the quality of ab initio and neural network-based molecular dynamics (NNMD) calculations in the temperature range 515–700°⁢C. The machine-learning enhanced NNMD calculations offer improved efficiency while maintaining accuracy at higher distances compared to ab initio calculations. Looking at the evolution of the pair distribution function with increasing temperature, a fundamental change in the liquid structure within the selected temperature range, accompanied by a slight decrease in overall correlation is revealed. NNMD calculations indicate the coexistence of three different fluorozirconate complexes: [Zr⁢F 6 ] 2– , [Zr⁢F 7 ] 3– , and [Zr⁢F 8 ] 4– , with a shift in the dominant coordination state from the 7-coordinated Zr cation toward a 6-coordinated cation with increasing temperature. The study also highlights the metastability of different local coordination structures, with frequent interconversions between the 6- and 7-coordinate states. Analysis of the Zr-F-Zr angular distribution function reveals the presence of both “edge-sharing” and “corner-sharing” fluorozirconate complexes with specific bond angles and distances in accord with previous studies, while the next-nearest-neighbor cation-cation correlations demonstrate a clear preference for unlike cations as nearest-neighbor pairs, emphasizing nonrandom arrangement. Finally, these findings contribute to a comprehensive understanding of the complex local structure of the molten salt, providing insights into temperature-dependent preferences and correlations within the molten system.

36 MATERIALS SCIENCE↗

Cross-species analysis of FcγRIIa/b (CD32a/b) polymorphisms at position 131: structural and functional insights into the mechanism of IgG- mediated phagocytosis in human and macaque

Introduction Antibodies play a critical role in immunity in part by mediating clearance of pathogens and infected cells by antibody-dependent cellular phagocytosis (ADCP) through engagement of Fc gamma receptors (FcγRs) on innate immune cells. Among these, FcγRIIa (CD32a) is a key activating receptor expressed on macrophages, dendritic cells, and other antigen-presenting cells. Its affinity for IgG and ability to mediate ADCP is influenced by allelic polymorphisms. In humans, a single amino acid polymorphism at position 131, where histidine (H) is substituted with arginine (R), leads to decreased IgG1 and IgG2 subclass binding affinity and, consequently, lower efficiency of phagocytic responses. Rhesus macaques ( Macaca mulatta ), which are widely used as nonhuman primate models, exhibit a similar polymorphism at position 131 of FcγRIIa, but with arginine replaced by proline (P). Here, we investigated structure-function relationships associated with the FcγRIIa polymorphism at position 131 in both species, specifically with respect to IgG1 and IgG2. Methods We determined the structures of complexes formed by each variant with IgG1 Fc and those formed by the higher affinity variant with IgG2 Fc for both species by x-ray crystallography and linked these structures to affinity and activity using SPR and an ADCP assay. We also determined the structure of human inhibitory FcγRIIb (CD32b) in complex with IgG1 Fc by x-ray crystallography. Results Through analysis of these structures, our studies reveal that FcγRIIa engagement is minimally influenced by Fc glycan composition, distinguishing it from FcγRIIIa whose affinity is strongly influenced by glycan-composition. Comparative structures of human and macaque FcγRIIa variants demonstrate species- and allele-specific differences in Fc binding, but our functional assays showed only minimal allele-specific effects in humans. In contrast, allele-specific effects in macaques were highly significant; the macaque P 131 variant showing uniformly reduced IgG affinity. Conclusion These insights highlight fundamental interspecies and allelic distinctions that are critical for interpreting FcγRIIa-mediated effector functions in macaque models and for optimizing translational antibody and vaccine design.

Tolbert, William D.↗