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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Exploring Critical Synthetic Parameters for Nanoscale ε-Fe 2 O 3 and Their Influence on Magnetic Behaviors

An intermediate polymorph of iron oxide, ε-Fe 2 O 3 , has attracted significant attention due to its giant coercive field ( H c ) and potential applications in high-frequency millimeter-wave absorption and high-density magnetic recording. However, the fabrication of ε-Fe 2 O 3 with high phase purity is still a challenge due to complicated synthetic procedures and a large variety of reaction parameters. In this study, we have identified critical reaction parameters to improve the phase purity of ε-Fe 2 O 3 , and the effects of all possible reaction parameters have been tested through systematic studies. A combination of structural and magnetic characterization techniques provides us with an accurate and reliable phase purity analysis of the ε-Fe 2 O 3 phase. Specifically, we observed that (1) the reaction temperature and time and (2) the addition of Ba are critical parameters to improve the phase purity. We identified the optimal conditions that maximize the coercivity and phase purity, giving insight into the effects of each parameter on the γ- to ε- to α-phase-transition pathway. We obtained nearly single-phase ε-Fe 2 O 3 (~87 wt % with ~13 wt % α-phase) with a large coercivity of H c = 20.6 kOe, enabling us to obtain pure ε-Fe 2 O 3 by a simple magnetic separation protocol, and tuned the H c of the ε-Fe 2 O 3 nanoparticles in the range of 4.0–20.6 kOe by controlling the reaction parameters. Furthermore, the structural properties of the resulting ε-Fe 2 O 3 nanoparticles are confirmed by characterizing their chemical and magnetic properties using X-ray absorption spectroscopy and X-ray magnetic circular dichroism measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2026

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics↗
DOE OSTI2025

Boosting the Oxygen Evolution Reaction by Tuning the Interfacial Iron Adsorption on Layered Double Hydroxide

Understanding the interaction between ions in the electrolyte and electrode materials plays an important role in optimizing the water electrolysis performance for hydrogen production. Herein, the synergistic effect of iron (Fe) in the electrolyte and interlayer anions within the layered structure on the oxygen evolution reaction (OER) has been investigated by combining material synthesis with controlled structure, multiple characterization techniques, and first-principles calculations. Nickel aluminum layered double hydroxides (NiAl-LDHs) with different interlayer anions (CO 3 2– , Cl – , and Br – ) show similar oxygen evolution activity in the absence of Fe species in the electrolyte. The addition of Fe into the electrolyte results in improved performance for all of the NiAl-LDHs, following the rank LDH-Br > LDH-Cl > LDH-CO 3 , under all of the conditions with varied concentration of Fe. X-ray absorption spectroscopy and identical location electron microscopy analyses show that the LDH structure remains unchanged after the OER activity test, while in situ stationary probe rotating disk electrode inductively coupled plasma mass spectrometry (SPRDE-ICP-MS) measurements show partial dissolution of the intercalating halide ions during cycling, with less dissolution for Br-intercalated materials. Insights from theoretical calculations demonstrate the thermodynamic preference of Br – to remain intercalated in the presence of Fe, while the stronger adsorption of Fe(OH) 3 species on the LDH-Br sample promotes the OER activity. In conclusion, these results provide mechanistic insights into the rational design of active layered materials with an enhanced OER performance for efficient water electrolysis.

58 GEOSCIENCES↗
DOE OSTI2025

Warpage-Resistant, Under-Extrusion-Free, High-Surface-Quality Additive Manufacturing Process for Polyethylene-Based Composite Radiation Shielding Material

Polyethylene (PE) is one of the best shielding materials for primary space radiation due to its high hydrogen content. For effective secondary neutron shielding, boron-rich fillers are incorporated to enhance performance. The semicrystalline nature and high thermal expansion coefficient of PE impede its adoption for in situ additive manufacture in space via the fused deposition modeling (FDM) 3D printing. Here, we developed an optimized PE blend to mitigate the effects of under-extrusion and warpage. Guided by studies on extrusion and warpage, we developed an optimal set of printing parameters for the proposed PE blend. The optimum PE blend─both in its pure form and when doped with fillers─has been tested on different FDM printers. The printed structures exhibit high and uniform density, smooth surfaces, no warpage, and competitive mechanical properties. The FDM-printed plates demonstrate efficient shielding from thermal neutrons, predicted via modeling and confirmed experimentally using extended Q-range small-angle neutron scattering.

additive manufacturing↗
DOE OSTI2021

Efficient calculation of carrier scattering rates from first principles

Abstract The electronic transport behaviour of materials determines their suitability for technological applications. We develop a computationally efficient method for calculating carrier scattering rates of solid-state semiconductors and insulators from first principles inputs. The present method extends existing polar and non-polar electron-phonon coupling, ionized impurity, and piezoelectric scattering mechanisms formulated for isotropic band structures to support highly anisotropic materials. We test the formalism by calculating the electronic transport properties of 23 semiconductors, including the large 48 atom CH 3 NH 3 PbI 3 hybrid perovskite, and comparing the results against experimental measurements and more detailed scattering simulations. The Spearman rank coefficient of mobility against experiment ( r s = 0.93) improves significantly on results obtained using a constant relaxation time approximation ( r s = 0.52). We find our approach offers similar accuracy to state-of-the art methods at approximately 1/500th the computational cost, thus enabling its use in high-throughput computational workflows for the accurate screening of carrier mobilities, lifetimes, and thermoelectric power.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Modified structure of protons and neutrons in correlated pairs

The atomic nucleus is made of protons and neutrons (nucleons), which are themselves composed of quarks and gluons. Understanding how the quark-gluon structure of a nucleon bound in an atomic nucleus is modified by the surrounding nucleons is an outstanding challenge. Although evidence for such modification-known as the EMC effect-was first observed over 35 years ago, there is still no generally accepted explanation for its cause. Recent observations suggest that the EMC effect is related to close-proximity short-range correlated (SRC) nucleon pairs in nuclei. Here we report simultaneous, high-precision measurements of the EMC effect and SRC abundances. We show that EMC data can be explained by a universal modification of the structure of nucleons in neutron-proton SRC pairs and present a data-driven extraction of the corresponding universal modification function. This implies that in heavier nuclei with many more neutrons than protons, each proton is more likely than each neutron to belong to an SRC pair and hence to have distorted quark structure. This universal modification function will be useful for determining the structure of the free neutron and thereby testing quantum chromodynamics symmetry-breaking mechanisms and may help to discriminate between nuclear physics effects and beyond-the-standard-model effects in neutrino experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow Battery

The solvation free energy of organic molecules is a critical parameter in determining emergent properties such as solubility, liquid-phase equilibrium constants, and pKa and redox potentials in an organic redox flow battery. In this work, we present a machine learning (ML) model that can learn and predict the aqueous solvation free energy of an organic molecule using Gaussian process regression method based on a new molecular graph kernel. To investigate the performance of the ML model on electrostatic interaction, the nonpolar interaction contribution of solvent and the conformational entropy of solute in solvation free energy, three data sets with implicit or explicit water solvent models, and contribution of conformational entropy of solute are tested. We demonstrate that our ML model can predict the solvation free energy of molecules at chemical accuracy with a mean absolute error of less than 1 kcal/mol for subsets of the QM9 dataset and the Freesolv database. To solve the general data scarcity problem for a graph-based ML model, we propose a dimension reduction algorithm based on the distance between molecular graphs, which can be used to examine the diversity of the molecular data set. It provides a promising way to build a minimum training set to improve prediction for certain test sets where the space of molecular structures is predetermined.

25 ENERGY STORAGE↗
DOE OSTI2018

The gluon structure of hadrons and nuclei from lattice QCD

I discuss recent lattice QCD studies of the gluon structure of hadrons and light nuclei. After very briefly highlighting new determinations of the gluon contributions to the nucleon's momentum and spin, presented by several collaborations over the last year, I describe first calculations of gluon generalised form factors. The generalised transversity gluon distributions are of particular interest since they are purely gluonic; they do not mix with quark distributions at leading twist. In light nuclei they moreover provide a clean signature of non-nucleonic gluon degrees of freedom, and I present the first evidence for such effects, based on lattice QCD calculations. The planned Electron-Ion Collider, designed to access gluon structure quantities, will have the capability to test this prediction, and measure a range of gluon observables including generalised gluon distributions and transverse momentum dependent gluon distributions, within the next decade.

Shanahan, Phiala A.↗
DOE OSTI2024

Reexpansion of charged nanoparticle assemblies in concentrated electrolytes

Electrostatic forces in solutions are highly relevant to a variety of fields, ranging from electrochemical energy storage to biology. However, their manifestation in concentrated electrolytes is not fully understood, as exemplified by counterintuitive observations of colloidal stability and long-ranged repulsions in molten salts. Highly charged biomolecules, such as DNA, respond sensitively to ions in dilute solutions. Here, we use non-base-pairing DNA-coated nanoparticles (DNA-NP) to analyze electrostatic interactions in concentrated salt solutions. Despite their negative charge, these conjugates form colloidal crystals in solutions of sufficient divalent cation concentration. We utilize small-angle X-ray scattering (SAXS) to study such DNA-NP assemblies across the full accessible concentration ranges of aqueous CaCl 2 , MgCl 2 , and SrCl 2 solutions. SAXS shows that the crystallinity and phases of the assembled structures vary with cation type. For all tested salts, the aggregates contract with added ions at low salinities and then begin expanding above a cation-dependent threshold salt concentration. Wide-angle X-ray scattering (WAXS) reveals enhanced positional correlations between ions in the solution at high salt concentrations. Complementary molecular dynamics simulations show that these ion–ion interactions reduce the favorability of dense ion configurations within the DNA brushes below that of the bulk solution. Measurements in solutions with lowered permittivity demonstrate a simultaneous increase in ion coupling and decrease in the concentration at which aggregate expansion begins, thus confirming the connection between these phenomena. Our work demonstrates that interactions between charged objects continue to evolve considerably into the high-concentration regime, where classical theories project electrostatics to be of negligible consequence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

An optimal FFT-based anisotropic power spectrum estimator

Measurements of line-of-sight dependent clustering via the galaxy power spectrum's multipole moments constitute a powerful tool for testing theoretical models in large-scale structure. Recent work shows that this measurement, including a moving line-of-sight, can be accelerated using Fast Fourier Transforms (FFTs) by decomposing the Legendre polynomials into products of Cartesian vectors. Here, we present a faster, optimal means of using FFTs for this measurement. We avoid redundancy present in the Cartesian decomposition by using a spherical harmonic decomposition of the Legendre polynomials. With this method, a given multipole of order ℓ requires only 2ℓ+1 FFTs rather than the (ℓ+1)(ℓ+2)/2 FFTs of the Cartesian approach. For the hexadecapole (ℓ = 4), this translates to 40% fewer FFTs, with increased savings for higher ℓ. The reduction in wall-clock time enables the calculation of finely-binned wedges in P ( k ,μ), obtained by computing multipoles up to a large ℓ{sub max} and combining them. This transformation has a number of advantages. We demonstrate that by using non-uniform bins in μ, we can isolate plane-of-sky (angular) systematics to a narrow bin at 0μ ≅ while eliminating the contamination from all other bins. We also show that the covariance matrix of clustering wedges binned uniformly in μ becomes ill-conditioned when combining multipoles up to large values of ℓ{sub max}, but that the problem can be avoided with non-uniform binning. As an example, we present results using ℓ{sub max}=16, for which our procedure requires a factor of 3.4 fewer FFTs than the Cartesian method, while removing the first μ bin leads only to a 7% increase in statistical error on f σ{sub 8}, as compared to a 54% increase with ℓ{sub max}=4.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Novel functional and distributed approaches to data analysis available in ROOT

The bright future of particle physics at the Energy and Intensity frontiers poses exciting challenges to the scientific software community. The traditional strategies for processing and analyzing data are evolving in order to (i) offer higher-level programming model approaches and (ii) exploit parallelism to cope with the ever increasing complexity and size of the datasets. This contribution describes how the ROOT framework, a cornerstone of software stacks dedicated to particle physics, is preparing to provide adequate solutions for the analysis of large amount of scientific data on parallel architectures. The functional approach to parallel data analysis provided with the ROOT TDataFrame interface is then characterized. The design choices behind this new interface are described also comparing with other widely adopted tools such as Pandas and Apache Spark. The programming model is illustrated highlighting the reduction of boilerplate code, composability of the actions and data transformations as well as the capabilities of dealing with different data sources such as ROOT, JSON, CSV or databases. Details are given about how the functional approach allows transparent implicit parallelization of the chain of operations specified by the user. The progress done in the field of distributed analysis is examined. In particular, the power of the integration of ROOT with Apache Spark via the PyROOT interface is shown. In addition, the building blocks for the expression of parallelism in ROOT are briefly characterized together with the structural changes applied in the building and testing infrastructure which were necessary to put them in production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Silicon wafer fracture stress for tracking sensors in particle physics experiments

For the construction of the ATLAS Inner Tracker strip detector, silicon strip sensor modules are glued directly onto carbon fibre support structures using a soft silicone gel. During tests at temperatures below -35°C, several of the sensors were found to crack due to a mismatch in coefficients of thermal expansion between polyimide circuit boards with copper metal layers (glued onto the sensor) and the silicon sensor itself. While module assembly procedures were developed to minimise variations between modules, cold tests showed a wide range of temperatures at which supposedly comparable modules failed. The observed variance (fracture temperatures between -35°C and -70°C) for supposedly comparable modules suggests an undetected variation between modules suspected to be intrinsic to the silicon wafer itself. Therefore, a test programme was developed to investigate the fracture stress of representative sensor wafer cutoffs. This paper presents results for the fracture stress of silicon sensors used in detector modules.

Detector design and construction technologies and ↗
DOE OSTI2025

Dark energy survey year 3 results: Cosmological constraints from cluster abundances, weak lensing, and galaxy clustering

Galaxy clusters provide a unique probe of the late-time cosmic structure and serve as a powerful independent test of the Λ⁢CDM model. This work presents the first set of cosmological constraints derived with ∼16,000 optically selected redMaPPer clusters across nearly 5000 deg 2 using DES year 3 datasets. Our analysis leverages a consistent modeling framework for galaxy cluster cosmology and DES-Y3 joint analyses of galaxy clustering and weak lensing (3 × 2⁢pt), ensuring direct comparability with the DES-Y3 3 × 2⁢pt analysis. Here, we obtain constraints of 𝑆 8 = 0.864 ± 0.035 and Ω m = $0.26⁢5^{+0.019}_{−0.031}$ from the cluster-based data vector. We find that cluster constraints and 3 × 2⁢pt constraints are consistent under the Λ⁢CDM model with a posterior predictive distribution (PPD) value of 0.53. The consistency between clusters and 3 × 2⁢pt provides a stringent test of Λ⁢CDM across different mass and spatial scales. Jointly analyzing clusters with 3 × 2⁢pt further improves cosmological constraints, yielding 𝑆 8 = $0.81⁢1^{+0.022}_{−0.020}$ and Ω m = $0.29⁢4^{+0.022}_{−0.033}$, a 24% improvement in the Ω m − 𝑆 8 figure of merit over 3 × 2⁢pt alone. Moreover, we find no significant deviation from the Planck CMB constraints with a probability to exceed (PTE) value of 0.6, significantly reducing previous 𝑆 8 tension claims. Finally, combining DES 3 × 2⁢pt, DES clusters, and Planck CMB places an upper limit on the sum of neutrino masses of ∑𝑚 𝜈 < 0.26 eV at 95% confidence under the Λ⁢CDM model. These results establish optically selected clusters as a key cosmological probe and pave the way for cluster-based analyses in upcoming stage-IV surveys such as LSST, Euclid, and Roman.

Abbott, T. M. C. [NSF’s National Optical-Infrared ↗
DOE OSTI2026

Small-𝑥 behavior in QCD from maximal entanglement and conformal invariance

Recent evidence suggests that, at small Bjorken 𝑥, QCD evolution drives the proton into a state of maximal entanglement. If the evolution kernel is assumed to be conformally invariant—as is the case for the Balitsky-Fadin-Kuraev-Lipatov equation—we can describe it by a conformal field theory. Moreover, the central charge 𝑐 of the corresponding conformal field theory emerges as the key parameter governing the 𝑥 dependence of both the entanglement entropy and the structure function. Here we apply the exact Bethe ansatz methods to the quantum spin chain dual to Lipatov’s high energy effective action to extract the central charge of the theory, and find that 𝑐 = 1. This implies the ∼𝑥 −1/3 small 𝑥 behavior for the structure function—the prediction that can be tested at the forthcoming Electron-Ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Weak charge and weak radius of 12 C

Here, we present a feasibility study of a simultaneous sub-percent extraction of the weak charge and the weak radius of the 12 C nucleus using parity-violating electron scattering, based on a largely model-independent assessment of the uncertainties. The corresponding measurement is considered to be carried out at the future MESA facility in Mainz with E beam = 155 MeV. We find that a combination of a 0.3% precise measurement of the parity-violating asymmetry at forward angles with a 10% measurement at backward angles will allow to determine the weak charge and the weak radius of 12 C with 0.4% and 0.5% precision, respectively. These values could be improved to 0.3% and 0.2% for a 3% backward measurement. This experimental program will have impact on precision low-energy tests in the electroweak sector and nuclear structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Phase Pattern Formation in Grain Boundaries

Here, in this Letter, we derive conditions that predict the existence of two-phase periodic-pattern grain boundary structures that are stable against coarsening. While previous research has established that elastic effects can lead to phase pattern formation on crystal surfaces, the possibility of stable grain boundary structures composed of alternating grain boundary phases has not been previously analyzed. Our theory identifies the specific combination of grain boundary and materials properties that enable the emergence of patterned grain boundary states and shows that the dislocation content of grain boundary phase junctions, absent in surface phenomena, weakens the stability of the patterned structures. The predictions of the theory are tested using a model copper grain boundary that exhibits multiple phases and two-phase pattern formation. We discuss how, similarly to surfaces, elastic effects associated with grain boundary phase junctions have profound implications for how grain boundary phases transform.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Environmental matrix and moisture influence soil microbial phenotypes in a simplified porous media incubation

Soil moisture and porosity regulate microbial metabolism by influencing factors, such as system chemistry, substrate availability, and soil connectivity. However, accurately representing the soil environment and establishing a tractable microbial community that limits confounding variables is difficult. Here, we use a reduced-complexity microbial consortium grown in a glass bead porous media amended with chitin to test the effects of moisture and a structural matrix on microbial phenotypes. Leveraging metagenomes, metatranscriptomes, metaproteomes, and metabolomes, we saw that our porous media system significantly altered microbial phenotypes compared with the liquid incubations, denoting the importance of incorporating pores and surfaces for understanding microbial phenotypes in soils. These phenotypic shifts were mainly driven by differences in expression of Streptomyces and Ensifer, which included a significant decrease in overall chitin degradation between porous media and liquid. Our findings suggest that the success of Ensifer in porous media is likely related to its ability to repurpose carbon via the glyoxylate shunt amidst a lack of chitin degradation byproducts while potentially using polyhydroxyalkanoate granules as a C source. We also identified traits expressed by Ensifer and others, including motility, stress resistance, and carbon conservation, that likely influence the metabolic profiles observed across treatments. Together, these results demonstrate that porous media incubations promote structure-induced microbial phenotypes and are likely a better proxy for soil conditions than liquid culture systems. Furthermore, they emphasize that microbial phenotypes encompass not only the multi-enzyme pathways involved in metabolism but also include the complex interactions with the environment and other community members.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

MQXFS1 Quadrupole Fabrication Report

This report presents the fabrication and QC data of MQXFS1, the first short model of the low-beta quadrupoles (MQXF) for the LHC High Luminosity Upgrade. It describes the conductor, the coils, and the structure that make the MQXFS1 magnet. Qualification tests and non-conformities are also presented and discussed. The fabrication of MQXFS1 was started before the finalization of conductor and coil design for MQXF magnets. Two strand design were used (RRP 108/127 and RRP 132/169). Cable and coil cross-sections were “first generation”.

43 PARTICLE ACCELERATORS↗