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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nonlocal nucleon matrix elements in the rest frame

Extracting parton structure from lattice quantum chromodynamics (QCD) calculations requires studying the coordinate scale 𝑧 3 dependence of the matrix elements of bilocal operators. The most significant contribution comes from the 𝑧 3 dependence induced by ultraviolet (UV) renormalization of the Wilson line. We demonstrate that the next-to-leading order perturbative calculations of the renormalization factor can describe, to a few percent accuracy, the logarithm of the lattice QCD rest frame matrix elements with separations up to distances of 0.6 fm on multiple lattice spacings. The residual discrepancies can be modeled by a leading effect from the structure of the nucleon.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Observing the effects of numbers of valence nucleons on 0$^{+}_{𝑔⁡𝑠}$ → 2$^{+}_{1}$ transitions in deformed nuclei by comparing proton and neutron transition matrix elements

We examined the ratios of neutron and proton transition matrix elements, 𝑀 𝑛 /𝑀 𝑝 , for the 0$^{+}_{𝑔⁡𝑠}$ → 2$^{+}_{1}$ transitions in 48 even-even stable nuclei with 𝑁 > 20 for which electromagnetic matrix elements were compiled by Pritychenko et al. and for which high-quality inelastic proton-scattering data were available. Several deformed rare-earth nuclei have (𝑀 𝑛 /𝑀 𝑝 )/(𝑁/𝑍) values significantly below 1.0, which is not consistent with a simple liquid-drop picture. However, this phenomenon can be explained using a schematic picture in which 𝑀 𝑝 reaches a maximum at proton midshell (𝑍 = 66) and 𝑀𝑛 reaches its maximum at neutron midshell (𝑁 = 104). Several midmass vibrational nuclei have 𝑀 𝑛 /𝑀 𝑝 values significantly below 𝑁/𝑍, which is not consistent with the expectation that 𝑀 𝑛 /𝑀 𝑝 = 𝑁/𝑍 in such nuclei. As a result, a shell-model investigation of these observations might yield insights about this behavior.

Collective levels↗
DOE OSTI2025

Shear and bulk viscosity for a pure glue theory using an effective matrix model

At nonzero temperatures, the deconfining phase transition can be analyzed using an effective matrix model to characterize the change in holonomy. The model includes gluons and two-dimensional ghost fields in the adjoint representation, or “teens.” As ghosts, the teen fields are responsible for the decrease of the pressure as 𝑇 →𝑇 𝑑 , with 𝑇 𝑑 the transition temperature for deconfinement. Using the solution of this matrix model for a large number of colors, the parameters of the teen fields are adjusted so that the expectation value of the Polyakov loop is close to the values from the lattice. The shear, 𝜂, and bulk, 𝜁, viscosities are computed at nonzero holonomy to leading logarithmic order in weak coupling. In the pure glue theory, the value of the Polyakov loop is relatively large in the deconfined phase, ≈1/2 at 𝑇 𝑑 . Consequently, if 𝑠 is the entropy density, while 𝜂/𝑠 decreases as 𝑇 →𝑇 𝑑 , it is still well above the conformal bound. In contrast, 𝜁/𝑠 is largest at 𝑇 𝑑 , comparable to 𝜂/𝑠, then falls off rapidly with increasing temperature and is negligible by ∼2⁢𝑇 𝑑 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Development of Mixed Matrix Membranes by Using NH 2 ‐Functionalized UiO‐66 and [APTMS][AC] Ionic Liquid for the Separation of CO 2

The ever‐escalating CO 2 concentration in the atmosphere calls for accelerated development and deployment of carbon capture processes to reduce emissions. Mixed matrix membranes (MMMs), which are fabricated by incorporating the beneficial properties of highly selective inorganic fillers into a polymer matrix, have exhibited significant progress and the ability to enhance the performance of a membrane for gas separation. In this research, an amine‐based ionic liquid (IL) [APTMS][AC] was prepared, which has greater CO 2 affinity and greater solubility due to its amine moiety. The metal–organic framework (MOF) UiO‐66 with a multidimensional crystalline structure was used as a filler due to its appropriate porosity and tunable properties, and it was functionalized with NH 2 . MOFs were further modified with an IL to prepare UiO‐66@IL and UiO‐66‐NH 2 @IL, and MMMs incorporating each MOF were fabricated with the polymer Pebax‐1657. All the prepared membranes and MOFs were characterized to predict their separation efficiency. Several characterization techniques, namely, FTIR spectroscopy, XRD, and SEM, were used to successfully synthesize UiO‐66@IL and UiO‐66‐NH 2 @IL composites and confirmed proper dispersion and excellent polymer‒filler compatibility at filler loadings ranging from 0 to 30 wt.%. The separation performances were investigated, and the results showed that the incorporation of RTIL with the highly crystalline structure and large surface area of UiO‐66 enhanced the separation efficiency of the membrane. The permeability of CO 2 for all fabricated membranes continuously increased with increasing filler concentration, wherein the permeability was comparatively high for the UiO‐66‐NH 2 MMMs. The CO 2 /CH 4 selectivity improved by 35%, 54%, and 60%, respectively, for UiO‐66@IL, UiO‐66‐NH 2 , and UiO‐66‐NH 2 @IL MMMs compared to simple UiO‐66 for CO 2 /CH 4 and by 28%, 36%, and 63%, respectively, for CO 2 /N 2 , with an increase in filler loading in the MMMs.

Khalid, Hafiza Mamoona (ORCID:0009000135165855)↗
DOE OSTI2025

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images

The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.

Science & Technology - Other Topics↗
DOE OSTI2024

Scalable, Infiltration-Free Ceramic Matrix Composite Manufacturing for Molten Salt Receiver (SIF-CMC)

Ceramic Matrix Composite (CMC) with high thermomechanical properties is a promising material class for Concentrated Solar Power but current use is limited by a long and tedious manufacturing process with high costs and poor scalability. SIF-CMC provides a novel way to simplify the manufacturing process by dramatically increasing the char yield of the matrix from polymer to ceramic, which makes the CMC affordable and scalable.

Wei, Junhua↗
DOE OSTI2024

Modeling graphene sheet growth and dynamical matrix calculations using molecular dynamics

Molecular dynamics (MD) has been an incredibly useful tool to model physical processes that were synthesized experimentally but not fully understood. MD, through the use of semi-empirical inter-atomic potentials, has allowed understanding of different physical processes in materials science. Yet as well as providing useful insights into materials science, molecular dynamics has a wider range of usability. In this report, I will be detailing how MD can be used to study graphene formation from a carbon liquid which requires high temperatures and pressures. Beyond this, I will describe the usefulness of MD for understanding the physics for phonon transport quantum sensors. To do this, MD was employed to determine the dynamical matrix by treating atoms as coupled oscillators. An accurate understanding of the dynamical matrix of a system is required to calculate the non-equilibrium Green’s function used to describe the phonon transport within phonon wave-guides. I found that, across multiple pressures and temperatures, randomly placed carbon atoms will show evidence of pent-first formation with semi-empirical models. Density functional theory (DFT), on the other hand, was too computationally expensive to use for full scale MD simulations, but we have the possibility of training a machine learned interatomic potential to approximate DFT for carbon in the environments being studied for pent-first graphene sheet formation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

R -matrix analysis of n + nat Cl reactions up to 1.2 MeV

The R -matrix analysis of neutron-induced reactions for two stable chlorine isotopes ( 35 Cl and 37 Cl) was performed in the energy range of thermal up to 1.2 MeV. Starting from the repository of the ENDF/B-VIII.0 library and following recent measurement series, this work represents a significant improvement, particularly in the evaluation of the ( n , p ) reaction channel. The evaluation methodology used the R -matrix code SAMMY to generate a set of Reich–Moore resonance parameters for both stable chlorine isotopes. Consistent with recently measured 35 Cl( n , p ) data, the presented evaluation features a dramatic increase in the magnitude of the ( n , p ) reaction channel over the ENDF/B-VIII.1 nuclear data library and previous ENDF/B libraries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Measuring the Interfacial Chemistry of Micro- and Nano-Plastics Using Matrix Assisted Laser Desorption Ionization

Micro- and nano-plastics (MNPs) pose a significant hazard to both environmental and human health due to their complex interfacial interactions with their surroundings, however there is a lack of techniques available to study the composition of MNPs at their surface. To fill this gap, representative MNPs were coated with matrix that enabled detection via matrix-assisted laser desorption ionization mass spectrometry (MALDI), a technique that has been shown to be surface specific but had not been applied to MNPs previously. Three different coating techniques were tested; evaporation and condensation, drop-casting, and mixed nebulization. Mixed nebulization provided the best balance of results, which was a strong MALDI signal in combination with even coating on the MNP surface from MNPs ≥20 µm. This work provides a new technique for the measurement of MNP surface composition that will help advance the field and enable more thorough studies of the chemical transformations that MNPs undergo in the environment.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Scalable Fabrication of a Fibrous Amine-functionalized Matrix (FAM) Sorbent for Critical Mineral Recovery

We report a novel flat sheet Fibrous Amine-functionalized Matrix (FAM) sorbent platform designed for efficient and selective capture of CM from dilute solutions. The FAM sorbent features crosslinked amine microfilms coated onto/within a glass fiber matrix, providing fast mass transfer and excellent mechanical stability. Systematic batch and flow-through tests with FAM revealed rapid metal uptake kinetics and high capacity for representative species, achieving ~90 mg/g of Gallium, ~100 mg/g of Cobalt, and ~90 mg/g for Neodymium. Moreover, multiple eluents, including mineral acids and complexing agents, enabled highly effective desorption of adsorbed metals, demonstrating the feasibility of regenerating FAM sorbents. Importantly, tests with authentic coal ash leachate demonstrated strong selectivity toward U.S. Department of Energy (DOE)-listed CM and rare earth elements over abundant base cations, confirming the robustness of FAM in realistic complex solutions. The flat sheet geometry was amenable to scaling into durable spiral wound modules, highlighting the potential for future regeneration and reuse. This work establishes FAM sorbents as a promising platform for the recovery of CM from wastewaters, advancing both resource sustainability and environmental stewardship.

critical mineral recovery↗
DOE OSTI2025

Machine Learning–Guided Boolean Matrix Inference for Real-Time O-RAN Conflict Detection

Open Radio Access Networks (O-RAN) are emerging, software-driven cellular architectures that promote flexibility by enabling components from different vendors to interoperate. Multiple control applications called xApps can independently adjust network parameters in near real time, often without awareness of each other's actions. This creates a system highly prone to unintended conflicts and performance degradation due to the inherent complexity of such openness. To model such systems and ultimately prevent or mitigate xApp conflicts, it is essential to understand the dynamic relationships between xApps (A), the control parameters they adjust (P), and the resulting KPI responses (K). While the mappings from A to P and from K to A can often be derived from xApp specifications, the relationship from P to K is typically hidden within the system’s dynamics and must be inferred from observed data. We propose a novel data-driven Boolean inference framework that uncovers the hidden P?K dependencies using machine learning and interpretable rule induction. Continuous parameters and KPIs are first binarized using decision tree classifiers, and a binary influence matrix L is then inferred by solving Boolean matrix equations over time. This compact representation improves interpretability and enables real-time tracking of dynamically evolving parameter-KPI dependencies. We demonstrate the effectiveness of our method in a realistic mobile handover scenario, where it accurately recovers the underlying logic and enables proactive conflict detection.

42 - ENGINEERING↗
DOE OSTI2026

Irradiation of Advanced Cladding Specimens in the High Flux Isotope Reactor: Capsule Designs and Test Matrix

The Advanced Fuels Campaign (AFC) has initiated the Advanced Reactor Cladding (ARC) irradiation campaign to generate irradiation performance data for candidate fuel cladding concepts. The campaign includes a diverse set of ferritic/martensitic steels, oxide dispersion strengthened (ODS) alloys, FeCrAlbased alloys, coated materials, and welded cladding specimens produced through multiple US Department of Energy (DOE) programs and international collaborations. Three complementary experimental thrusts comprise the campaign: tensile testing (ARC Tensile) to rapidly screen candidate alloys, fracture toughness testing (ARC Fracture) to evaluate irradiation effects on crack resistance, and tubular weld testing (ARC Weld) to quantify irradiation-induced changes in the mechanical performance of end cap welds. This report documents the irradiation campaign design, including the selected materials, specimen types, irradiation matrix, and capsule designs for irradiation within the High Flux Isotope Reactor (HFIR). A total of 14 irradiation capsules were developed to achieve target irradiation temperatures between 300°C and 600°C and doses up to 30 dpa. Thermal analyses were performed using finite element methods to establish capsule geometries capable of achieving the desired specimen temperatures while accommodating differences in specimen geometry and material properties. The resulting capsule designs provide the basis for irradiation of the AFC-ARC experimental matrix and subsequent post-irradiation examination to assess the effects of neutron irradiation on advanced cladding materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Nuclear Matrix Elements for Neutrinoless Double-Beta Decay

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare hypothesised process that, if discovered, would establish that the neutrino is Majorana, that is, it is its own antiparticle. Interpretation of experimental results relies on knowledge of nuclear matrix elements, whose large model uncertainty is the limiting factor in comparing measured (bounds on) half-lives to the neutrino mass. Nuclear effective field theory and lattice QCD have the potential to compute these matrix elements with better control over uncertainties, enhancing the discovery potential of next-generation $0\nu\beta\beta$ experiments. This work will survey various lattice QCD double-beta decay calculations and discuss their implications.

Grebe, Anthony V. [Fermilab] (ORCID:00000003103201↗
DOE OSTI2025

Optimizing Solar PV Deployment in Manufacturing: A Morphological Matrix and Fuzzy TOPSIS Approach

The growing energy demand of the industrial sector and the need for sustainable solutions highlight the importance of efficient decision making in solar photovoltaic (PV) implementation. Selecting optimal PV configuration is complex due to the interdependent technical, economic, environmental, and social factors involved. This study introduces an integrated decision-making method combining a morphological matrix and fuzzy TOPSIS to systematically select and rank optimal PV system configurations for manufacturing firms. While the morphological matrix exhaustively examines possible design solutions based on sensing, smart, sustainable, and social (S4) attributes, the fuzzy TOPSIS method ranks the alternatives by handling uncertainty in decision making. A case study conducted in a Mexican manufacturing company validates the methodology’s effectiveness. The optimal PV configuration identified comprehensively addresses operational and sustainability criteria, covering all lifecycle stages. This approach demonstrates quantitative superiority and greater robustness compared to existing fuzzy TOPSIS-based methods for solar PV applications. The findings highlight the practical value of data-driven, multi-criteria decision making for industrial solar energy adoption, enhancing project feasibility, cost efficiency, and environmental compliance. Future research will incorporate discrete event simulation (DES) to further refine energy consumption strategies in manufacturing.

Briceño, Citlaly Pérez↗
DOE OSTI2024

Improved Statistical Analysis for the Neutrinoless Double-Beta Decay Matrix Element of 136Xe

Neutrinoless double beta decay nuclear matrix element (M0ν) for 136Xe was recently analyzed using a statistical approach (Phys. Rev. C 107, 045501 (2023)). In the analysis, three initial shell model effective Hamiltonians were randomly altered, and their results for 23 measured observables were used to infer credibility for the M0ν nuclear matrix element (NME) based on a Bayesian Model Averaging approach. In that analysis, a reasonable Gamow-Teller quenching factor of 0.7 was assumed for each starting effective Hamiltonian. Given that the result of the statistical analysis was sensible to this choice, we are here improving that analysis by assuming that the Gamow-Teller quenching factor is also randomly chosen within reasonabe limits for all three starting Hamiltonians. The outcomes are slightly higher expectation values and uncertainties for the M0ν NME.

Astronomy & Astrophysics↗
DOE OSTI2024

Effects of Interactions Between Produced Formation Fluid and Rock Matrix on Pore Structure of Caney Shale, Southern Oklahoma

ABSTRACT: Rock-fluid interactions change properties of shales during exploitation. To investigate effects of rock-fluid interactions on pore structure of shales matrix after hydraulic fracturing, powder samples from two late Mississippian Caney Shale cores in the Ardmore Basin, southern Oklahoma, were used to react with formation produced fluid from the field in the batch reactor analysis. X-ray diffraction for mineralogy and Low-pressure nitrogen adsorption isotherms for pore structure were measured for original, after-7days, and after-30days samples. Results show that the samples consist mainly of quartz, followed by clay minerals, carbonates, and feldspar. The pore sizes of micropore (<2 nm) and mesopore (2-50 nm) increase 14%-233% due to dissolution of pyrite, feldspar, and carbonates after 7 days. Due to the transformation from smectite to illite and the increase of pore size, the specific surface area (SSA) decreases after 7-days interactions. After 30-days interactions, the micropore volume slightly increases and the mesopore and macropore volume decreases. Due to the decrease of pore size, the SSA of 30-days reacted samples increases correspondingly and is lower (for the clay-rich sample) or higher (for the calcareous sample) than that of the unreacted samples. Findings improve our understanding of dynamic alteration of shale properties during production. 1. INTRODUCTION Energy demand will continuously grow owing to the increasing global population as well as energy consumption (EIA, 2023). On the other hand, shale gas and oil reshaped the energy market in the United States, enabling the United States to become a net-export of natural gas country in 2017 (EIA, 2023). However, shale reservoirs are challenging tight formations that are still poorly understood in the extraction and production of hydrocarbons (Ross and Bustin, 2009; Curtis et al., 2012; Xiong et al., 2015, 2021a; Li Y. et al., 2016; Gong et al., 2019a; Benge et al., 2021; Awejori et al., 2022; Huang et al., 2022). One of the most challenging topics is the rock-fluid interactions post hydraulic fracturing and its subsequent impacts on the pore structures of fractured formation matrix.

Xiong, Fengyang↗