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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Real-time evaluation of cybersecurity threats to DER inverter grid-support functions

In this project we aim to contribute to the understanding of the type and severity of potential cybersecurity attacks to the grid-support functionalities of DER systems interconnected to the AC distribution grid via inverters. Our preliminary work focused on developing a small-scale testbed allowing to study cybersecurity threats to an isolated photovoltaic-battery system using a real-time simulator (Typhoon HIL602+) with a real DNP3 communication connection over TCP/IP, allowing for safe and efficient monitoring and manipulation of data traffic between the simulated hardware and supervisory control and data acquisition (SCADA) system. In this project we propose to expand upon this development by utilizing a) a recently acquired NovaCor RTDS (Real Rime digital Simulator) to emulate the DER-inverter-grid topology including main grid-support functions as defined by IEEE Std. 1547-2018, and b) an industrial control and automation device to enable realistic evaluation of control functions and utilization of communication protocols for real-time data transmission.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

QCD splitting functions beyond kinematical limits

In this talk, I will present a new decomposition of QCD splitting functions, carried out systematically up to second order in the strong coupling. The core idea is to separate the splitting functions into two components: scalar dipole radiator functions and pure splitting remainders. While these pieces include terms that are formally subleading in the soft or collinear limits, they turn out to be universal and well understood. Unlike conventional approaches, our construction does not rely on any soft or collinear approximations. This framework not only offers a clearer understanding of the structure of higher-order QCD corrections but also paves the way for more robust subtraction schemes in precision calculations.

Knobbe, Max [Fermilab]↗
DOE OSTI2023

Determination of particle-dependent light response for defining detector response functions

This study comprehensively characterizes two scintillation detectors, an organic deuterated liquid and a stilbene crystal, concerning their response to charged particles such as electrons, protons, alphas, and carbon nuclei. The Birks function was used to determine the detectors’ response to charged particles, enabling the determination of particle-dependent light responses. The particle-dependent light characterization was used to determine detector response functions (DRF) using Geant in combination with Gamma Detector Response and Analysis Software (GADRAS). These DRFs enhance GADRAS by enabling full spectral analysis functionality for previously underrepresented detector materials. Additionally, neutron-specific DRFs are determined for neutron energy spectrum unfolding applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Omics Approaches for Understanding Biogenesis, Composition and Functions of Fungal Extracellular Vesicles

Extracellular vesicles (EVs) are lipid bilayer structures released by organisms from all kingdoms of life. The diverse biogenesis pathways of EVs result in a wide variety of physical properties and functions across different organisms. Fungal EVs were first described in 2007 and different omics approaches have been fundamental to understand their composition, biogenesis, and function. In this review, we discuss the role of omics in elucidating fungal EVs biology. Transcriptomics, proteomics, metabolomics, and lipidomics have each enabled the molecular characterization of fungal EVs, providing evidence that these structures serve a wide array of functions, ranging from key carriers of cell wall biosynthetic machinery to virulence factors. Omics in combination with genetic approaches have been instrumental in determining both biogenesis and cargo loading into EVs. We also discuss how omics technologies are being employed to elucidate the role of EVs in antifungal resistance, disease biomarkers, and their potential use as vaccines. Finally, we review recent advances in analytical technology and multi-omic integration tools, which will help to address key knowledge gaps in EVs biology and translate basic research information into urgently needed clinical applications such as diagnostics, and immuno- and chemotherapies to fungal infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

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.↗
DOE OSTI2023

Density functional modeling of the binding energies between aluminosilicate oligomers and different metal cations

Interactions between negatively charged aluminosilicate species and positively charged metal cations are critical to many important engineering processes and applications, including sustainable cements and aluminosilicate glasses. In an effort to probe these interactions, here we have calculated the pair-wise interaction energies (i.e., binding energies) between aluminosilicate dimer/trimer and 17 different metal cations M n+ (M n+ = Li + , Na + , K + , Cu + , Cu 2+ , Co 2+ , Zn 2+ , Ni 2+ , Mg 2+ , Ca 2+ , Ti 2+ , Fe 2+ , Fe 3+ , Co 3+ , Cr 3+ , Ti 4+ and Cr 6+ ) using a density functional theory (DFT) approach. Analysis of the DFT-optimized structural representations for the clusters (dimer/trimer + M n+ ) shows that their structural attributes (e.g., interatomic distances) are generally consistent with literature observations on aluminosilicate glasses. The DFT-derived binding energies are seen to vary considerably depending on the type of cations (i.e., charge and ionic radii) and aluminosilicate species (i.e., dimer or trimer). A survey of the literature reveals that the difference in the calculated binding energies between different M n+ can be used to explain many literature observations associated with the impact of metal cations on materials properties (e.g., glass corrosion, mineral dissolution, and ionic transport). Analysis of all the DFT-derived binding energies reveals that the correlation between these energy values and the ionic potential and field strength of the metal cations are well captured by 2nd order polynomial functions ( R 2 values of 0.99–1.00 are achieved for regressions). Given that the ionic potential and field strength of a given metal cation can be readily estimated using well-tabulated ionic radii available in the literature, these simple polynomial functions would enable rapid estimation of the binding energies of a much wider range of cations with the aluminosilicate dimer/trimer, providing guidance on the design and optimization of sustainable cements and aluminosilicate glasses and their associated applications. Finally, the limitations associated with using these simple model systems to model complex interactions are also discussed.

Gong, Kai↗
DOE OSTI2023

Biochemical and genetic studies define the functions of methylthiotransferases in methanogenic and methanotrophic archaea

Methylthiotransferases (MTTases) are radical S-adenosylmethionine (SAM) enzymes that catalyze the addition of a methylthio (-SCH 3 ) group to an unreactive carbon center. These enzymes are responsible for the production of 2-methylthioadenosine (ms 2 A) derivatives found at position A37 of select tRNAs in all domains of life. Additionally, some bacteria contain the RimO MTTase that catalyzes the methylthiolation of the S12 ribosomal protein. Although the functions of MTTases in bacteria and eukaryotes have been established via detailed genetic and biochemical studies, MTTases from the archaeal domain of life are understudied and the substrate specificity determinants of MTTases remain unclear. Here, we report the in vitro enzymatic activities of an MTTase (C4B56_06395) from a thermophilic Ca. Methanophagales anaerobic methanotroph (ANME) as well as the MTTase from a hyperthermophilic methanogen – MJ0867 from Methanocaldococcus jannaschii. Both enzymes catalyze the methylthiolation of N 6 -threonylcarbamoyladenosine (t 6 A) and N 6 -hydroxynorvalylcarbamoyladenosine (hn 6 A) residues to produce 2-methylthio-N 6 -threonylcarbamoyladenosine (ms 2 t 6 A) and 2-methylthio-N 6 -hydroxynorvalylcarbamoyladenosine (ms 2 hn 6 A), respectively. To further assess the function of archaeal MTTases, we analyzed select tRNA modifications in a model methanogen – Methanosarcina acetivorans – and generated a deletion of the MTTase-encoding gene (MA1153). We found that M. acetivorans produces ms 2 hn 6 A in exponential phase of growth, but does not produce ms 2 t 6 A in detectable amounts. Upon deletion of MA1153, the ms 2 A modification was absent, thus confirming the function of MtaB-family MTTases in generating ms 2 hn 6 A modified nucleosides in select tRNAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Editorial: Functional microcircuits in the brain and in artificial intelligent systems

Fundamental principles underlying higher-order cognitive functions remain elusive, but recent breakthroughs in neurophysiology and deep learning offer new perspectives. First, experimental studies have uncovered neural circuit motifs consisting of various neuron types; see Brain Initiative Cell Census Network (https://www.nature.com/collections/cicghheddj). For example, inhibitory neuron types expressing exclusive genes have specific targets and distinct functions (Pfeffer et al., 2013). Furthermore, diverse neuron types in cortex and their connectomes were identified in cortical columns (Jiang et al., 2015); see also Barth et al. (2016) for a debate on neuron types. Second, artificial neural networks were originally inspired by structures of the brain (McCulloch and Pitts, 1943) and could be trained to perform complex functions similar to human perception/cognition by deep learning (DL) (Lecun et al., 2015).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Functional Diversification of Populus FLOWERING LOCUS D-LIKE3 Transcription Factor and Two Paralogs in Shoot Ontogeny, Flowering, and Vegetative Phenology

Both the evolution of tree taxa and whole-genome duplication (WGD) have occurred many times during angiosperm evolution. Transcription factors are preferentially retained following WGD suggesting that functional divergence of duplicates could contribute to traits distinctive to the tree growth habit. We used gain- and loss-of-function transgenics, photoperiod treatments, and circannual expression studies in adult trees to study the diversification of three Populus FLOWERING LOCUS D-LIKE (FDL) genes encoding bZIP transcription factors. Expression patterns and transgenic studies indicate that FDL2.2 promotes flowering and that FDL1 and FDL3 function in different vegetative phenophases. Study of dominant repressor FDL versions indicates that the FDL proteins are partially equivalent in their ability to alter shoot growth. Like its paralogs, FDL3 overexpression delays short day-induced growth cessation, but also induces distinct heterochronic shifts in shoot development—more rapid phytomer initiation and coordinated delay in both leaf expansion and the transition to secondary growth in long days, but not in short days. Our results indicate that both regulatory and protein coding sequence variation contributed to diversification of FDL paralogs that has led to a degree of specialization in multiple developmental processes important for trees and their local adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The Field Epidemiology Training Program’s Contribution to Essential Public Health Functions in Seven National Public Health Institutes

Objective: This study explores how Field Epidemiology Training Programs (FETP) whose National Public Health Institutes (NPHI) are supported by U.S. Centers for Disease Control and Prevention (CDC) have contributed to strengthening essential public health functions. Methods: We conducted 96 semi-structured interviews with public health experts including NPHI staff, non-NPHI government staff, and staff from non-governmental and international organizations in Cambodia, Colombia, Liberia, Mozambique, Nigeria, Rwanda, and Zambia. We managed data using MAXQDA and employed direct content analysis to derive themes. Results: Three overarching themes emerged in relation to FETPs’ role within the NPHIs’ public health functions. These themes included contribution to improving country surveillance systems, role in providing leadership in outbreak responses, and strengthening countries’ and the NPHIs’ surveillance workforce capacity. Participants also shared challenges around FETPs’ implementation and suggestions for improvement. Conclusion: The results demonstrate the value of FETPs in strengthening public health systems through building workforce capacity and improving surveillance systems. By identifying the successes of FETPs in contributing to essential public health functions, our findings might inform current and future FETP implementation and its integration into NPHIs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice

Positron emission tomography (PET) radioligands that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[ 18 F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [ 18 F]Nifene, displaying similar pKa and binding affinity to nicotine. Time–activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the β2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

2-FA85380↗
DOE OSTI2025

Synergistic Density Functional Theory and Molecular Dynamics Approach to Elucidate PNIPAM–Water Interaction Mechanisms

This study employs Density Functional Theory (DFT) and Molecular Dynamics (MD) simulations to investigate interactions between water molecules and Poly(N-isopropylacrylamide) (PNIPAM). DFT reveals preferential water binding sites, with enhanced binding energy observed in the linker zone. Quantum Theory of Atoms in Molecules (QTAIM) and electron localization function (ELF) analyses highlight the roles of hydrogen bonding and steric hindrance. MD simulations unveil temperature-dependent hydration dynamics, with structural transitions marked by changes in the radius of gyration (Rg) and the radial distribution function (RDF), aligning with DFT findings. Our work goes beyond prior studies by combining a DFT, QTAIM and MD simulations approach across different PNIPAM monomer-to-30mer structures. It introduces a systematic quantification of pseudo-saturation thresholds and explores water clustering dynamics with structural specificity, which have not been previously reported in the literature. These novel insights establish a more complete molecular-level picture of PNIPAM hydration behavior and temperature responsiveness, emphasizing the importance of amide hydrogen and carbonyl oxygen sites in hydrogen bonding, which weakens above the lower critical solution temperature (LCST), resulting in increased hydrophobicity and paving the way for understanding water sorption mechanisms, offering guidance for future applications such as dehumidification and atmospheric water harvesting.

08 HYDROGEN↗
DOE OSTI2021

Continuous MOF Membrane-Based Sensors via Functionalization of Interdigitated Electrodes

Three M-MOF-74 (M = Co, Mg, Ni) metal-organic framework (MOF) thin film membranes have been synthesized through a sensor functionalization method for the direct electrical detection of NO 2 . The two-step surface functionalization procedure on the glass/Pt interdigitated electrodes resulted in a terminal carboxylate group, with both steps confirmed through infrared spectroscopic analysis. This surface functionalization allowed the MOF materials to grow largely in a uniform manner over the surface of the electrode forming a thin film membrane over the Pt sensing electrodes. The growth of each membrane was confirmed through scanning electron microscopy (SEM) and X-ray diffraction analysis. The Ni and Mg MOFs grew as a continuous but non-defect free membrane with overlapping polycrystallites across the glass surface, whereas the Co-MOF-74 grew discontinuously. To demonstrate the use of these MOF membranes as an NO 2 gas sensor, Ni-MOF-74 was chosen as it was consistently fabricated as the best thin and homogenous membrane, as confirmed by SEM. The membrane was exposed to 5 ppm NO 2 and the impedance magnitude was observed to decrease 123× in 4 h, with a larger change in impedance and a faster response than the bulk material. Importantly, the use of these membranes as a sensor for NO 2 does not require them to be defect-free, but solely continuous and overlapping growth.

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

Styrene-Based Elastomer Composites with Functionalized Graphene Oxide and Silica Nanofiber Fillers: Mechanical and Thermal Conductivity Properties

The mechanical and thermal conductivity properties of two composite elastomers were studied. Styrene–butadiene rubber (SBR) filled with functionalized graphene oxide (GO) and silica nanofibers, and styrene–butadiene–styrene (SBS) block copolymers filled with graphene oxide. For the SBR composites, GO fillers with two different surface functionalities were synthesized (cysteamine and dodecylamine) and dispersed in the SBR using mechanical and liquid mixing techniques. The hydrophilic cysteamine-based GO fillers were dispersed in the SBR by mechanical mixing, whereas the hydrophobic dodecylamine-based GO fillers were dispersed in the SBR by liquid mixing. Silica nanofibers (SnFs) were fabricated by electrospinning a sol–gel precursor solution. The surface chemistry of the functionalized fillers was studied in detail. The properties of the composites and the synergistic improvements between the GO and SnFs are presented. For the SBS composites, GO fillers were dispersed in the SBS elastomer at several weight percent loadings using liquid mixing. Characterization of the filler material and the composite elastomers was performed using x-ray photoelectron spectroscopy, x-ray diffraction, transmission electron microscopy, scanning electron microscopy, thermogravimetric analysis, dynamic mechanical analysis, tensile testing, nanoindentation, thermal conductivity and abrasion testing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Functional Filaments: Creating and Degrading pH-Indicating PLA Filaments for 3D Printing

With the rapid pace of advancements in additive manufacturing and techniques such as fused filament fabrication (FFF), the feedstocks used in these techniques should advance as well. While available filaments can be used to print highly customizable parts, the creation of the end part is often the only function of a given feedstock. In this study, novel FFF filaments with inherent environmental sensing functionalities were created by melt-blending poly(lactic acid) (PLA), poly(ethylene glycol) (PEG), and pH indicator powders (bromothymol blue, phenolphthalein, and thymol blue). The new PLA-PEG-indicator filaments were universally more crystalline than the PLA-only filaments (33–41% vs. 19% crystallinity), but changes in thermal stability and mechanical characteristics depended upon the indicator used; filaments containing bromothymol blue and thymol blue were more thermally stable, had higher tensile strength, and were less ductile than PLA-only filaments, while filaments containing phenolphthalein were less thermally stable, had lower tensile strength, and were more ductile. When the indicator-filled filaments were exposed to acidic, neutral, and basic solutions, all filaments functioned as effective pH sensors, though the bromothymol blue-containing filament was only successful as a base indicator. The biodegradability of the new filaments was evaluated by characterizing filament samples after aging in soil and soil slurry mixtures; the amount of physical deterioration and changes in filament crystallinity suggested that the bromothymol blue filament degraded faster than PLA-only filaments, while the phenolphthalein and thymol blue filaments saw decreases in degradation rates.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Stars Kepler Missed: Investigating the Kepler Target Selection Function Using Gaia DR2

The Kepler Mission revolutionized exoplanet science and stellar astrophysics by obtaining highly precise photometry of over 200,000 stars over 4 yr. A critical piece of information to exploit Kepler data is its selection function, since all targets had to be selected from a sample of half a million stars on the Kepler CCDs using limited information. Here we use Gaia DR2 to reconstruct the Kepler selection function and explore possible biases with respect to evolutionary state, stellar multiplicity, and kinematics. We find that the Kepler target selection is nearly complete for stars brighter than Kp < 14 mag and was effective at selecting main-sequence stars, with the fraction of observed stars decreasing from 95% to 60% between 14 < Kp < 16 mag. We find that the observed fraction for subgiant stars is only 10% lower, confirming that a significant number of subgiants selected for observation were believed to be main-sequence stars. Conversely we find a strong selection bias against low-luminosity red giant stars (R ≈ 3–5R {sub ⊙}, T {sub eff} ≈ 5500 K), dropping from 90% at Kp = 14 mag to below 30% at Kp = 16 mag, confirming that the target selection was efficient at distinguishing dwarfs from giants. We compare the Gaia Re-normalized Unit Weight Error (RUWE) values of the observed and nonobserved main-sequence stars and find a difference in elevated (>1.2) RUWE values at ∼σ significance, suggesting that the Kepler target selection shows some bias against either close or wide binaries. We furthermore use the Gaia proper motions to show that the Kepler selection function was unbiased with respect to kinematics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Functional Data Analysis for Extracting the Intrinsic Dimensionality of Spectra: Application to Chemical Homogeneity in the Open Cluster M67

High-resolution spectroscopic surveys of the Milky Way have entered the Big Data regime and have opened avenues for solving outstanding questions in Galactic archeology. However, exploiting their full potential is limited by complex systematics, whose characterization has not received much attention in modern spectroscopic analyses. In this work, we present a novel method to disentangle the component of spectral data space intrinsic to the stars from that due to systematics. Using functional principal component analysis on a sample of 18,933 giant spectra from APOGEE, we find that the intrinsic structure above the level of observational uncertainties requires ≈10 functional principal components (FPCs). Our FPCs can reduce the dimensionality of spectra, remove systematics, and impute masked wavelengths, thereby enabling accurate studies of stellar populations. To demonstrate the applicability of our FPCs, we use them to infer stellar parameters and abundances of 28 giants in the open cluster M67. We employ Sequential Neural Likelihood, a simulation-based Bayesian inference method that learns likelihood functions using neural density estimators, to incorporate non-Gaussian effects in spectral likelihoods. By hierarchically combining the inferred abundances, we limit the spread of the following elements in M67: Fe ≲ 0.02 dex; C ≲ 0.03 dex; O, Mg, Si, Ni ≲ 0.04 dex; Ca ≲ 0.05 dex; N, Al ≲ 0.07 dex (at 68% confidence). Our constraints suggest a lack of self-pollution by core-collapse supernovae in M67, which has promising implications for the future of chemical tagging to understand the star formation history and dynamical evolution of the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

New Covariant Density Functionals of Nuclear Matter for Compact Star Simulations

We generate three families of extended covariant density functionals of nuclear matter that have varying slope of symmetry energy and skewness at nuclear saturation density, but otherwise share the same basic parameters (symmetry energy, compressibility, saturation parameters, etc.) with the standard DDME2, DD2, and MPE functionals. Tables of the parameters of these new density functionals are given, which can be straightforwardly used in DDME2, DD2, and MPE parameterization-based codes. Furthermore, we provide tables of a large number of equations of state (81 for each family) that can be used in astrophysical simulations to assess the impact of variations of the not-well-known slope of symmetry energy and skewness of nuclear systems on the astrophysics of compact objects. We also provide tables of computed integral parameters (mass, radius, and tidal deformability) that can be used, e.g., for modeling gravitational waveforms. Finally, for the extended DDME2-based parameterization, we implement a first-order phase transition to quark matter to obtain a family of equations of state that accommodates a phase transition to quark matter. Analogous tables of the equations of state and integral parameters are provided for this case as well.

79 ASTRONOMY AND ASTROPHYSICS↗