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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Performance of the Pair Spectrometer in Hall D at Jefferson Lab

This article describes the performance of the pair spectrometer installed in experimental Hall D at Jefferson Lab and its successfully operation in multiple experiments with the GlueX detector. The primary purpose of the pair spectrometer is the precise determination of the flux of beam photons incident on the GlueX target, a critical input for physics analyses such as absolute cross-section measurements. The photon energy spectrum is determined by reconstructing electron–positron pairs produced in a thin converter inserted into the photon beam. The spectrometer is integrated into the GlueX trigger system, whose electronics enable continuous real-time monitoring of the photon flux and the recording of e+e- pair candidates for offline analysis. In addition, the pair spectrometer provides a versatile test facility for evaluating calorimeter prototypes using leptons with well-defined energies produced via electromagnetic pair production.

Somov, Alexander [Jefferson Lab]↗
DOE OSTI2025

Performance evaluation of the SPES FEBIAD ion source

SPES (Selective Production of Exotic Species) is the Radioactive Ion Beam (RIB) facility that is currently in the installation phase at the Istituto Nazionale di Fisica Nucleare in the Laboratori Nazionali di Legnaro (LNL-INFN). The main purpose of the facility is to deliver neutron-rich radioactive beams with a range of mass between 60 and 160 amu produced as fission products originated within a Uranium Carbide (UC x ) target impinged by high energy protons (40–70 MeV). In the last few years, the SPES group and their collaborators have focused on multiple aspects: development of various ISOL targets, ion sources, a high-power beam dump, versatile Front-End designs, primary proton beam and RIB diagnostics, design of beam optic components, and remote target handling. The development and optimization of ionization sources represents one of the most important R&D activities. The collaboration between SPES and ISOLDE (CERN) groups has enabled the evaluation of the performances of a novel FEBIAD ion source taking advantage of the ISOLDE off-line Front-End. In this paper, the results of efficiency and transversal emittance measurements of the new SPES FEBIAD ion source are presented and discussed. Particular attention is dedicated to the description of the experimental setup and to the comparison of experimental data with simulation to promote the reproducibility of the experimental tests with other types of sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Thickness and uniformity mapping of thin foils using resistive silicon detectors

Alpha energy loss is a common tool used for measuring target thicknesses. However, these measurements are often made without position information, which either forfeits knowledge of material uniformity and local thickness or requires a prohibitive number of measurements per target to partially recover this information. In consideration of this, a method for measuring position-dependent thicknesses is described in this work; by using the position-sensitivity of the dual-axis duo-lateral (DADL) silicon detector, thicknesses across the entire face of the material can be measured to sub-mm precision with a single measurement. Several examples are presented using a number of targets with varying characteristics, which altogether demonstrate the precision, accuracy, and versatility of this technique.

Foil uniformity↗
DOE OSTI2025

Unveiling X-ray absorption signatures of boron nitride via first-principles simulation and machine learning

Boron nitride (BN) allotropes hold great promise in many advanced applications ranging from optical and photonic devices to energy storage and battery systems to tribological components. The diverse functionalities of this material stem from BN’s highly tunable structural and electronic properties, which are governed by the versatile boron–nitrogen bonding configurations. Exploring the structural landscape of BN can unveil novel structures possessing unique properties suited for specific applications, therefore accelerating the design of next-generation advanced functional materials. In this work, we leverage boron K-edge X-ray absorption spectroscopy (XAS) as an effective probe for local structural features and chemical environments. A total of 210 BN crystal structures are generated via analogies to the extensive array of carbon allotropes, and XAS is simulated for each unique local motif within the resulting collection of structures. A mapping between structural features and spectral signatures was established by synergizing first-principle simulations with data-driven based post-analysis approaches. Specifically, we developed a neural network model that can satisfactorily predict spectra line shapes from local structural descriptors. Toward automatic spectroscopic interpretation of any new BN structures, supervised machine learning models, trained on this structure–spectrum dataset, can accurately infer local coordination environments from simulated XAS, highlighting the strength of this unique approach of combining high-fidelity first-principles simulation and machine-learning to accelerate target design of novel BN materials via rational understanding of local structure-spectrum correlations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Second-order wave excitation forces in WEC-Sim/MOST: Implementation, experimental validation, and code-to-code comparison

Accurate prediction of second-order hydrodynamic loads is essential for floating bodies, including floating offshore wind turbines, wave energy converters, and hybrid wind–wave platforms. These nonlinear effects, arising from both sum- and difference-frequency forcing, are critical for capturing key response characteristics but remain challenging to model efficiently. In this work, we extend the open-source Wave Energy Converter Simulator / MATLAB for Offshore Simulation Tool by implementing second-order wave excitation forces, supporting both the full Quadratic Transfer Function formulation and the Newman approximation. The full Quadratic Transfer Function method is used for all code-to-code comparisons and experimental validation, while the Newman approximation is provided as a computationally lighter alternative. To benchmark the new capability, we perform a code-to-code comparison with OpenFAST and OrcaFlex. We then validate the enhanced model using wave-tank measurements of a 1:96 scale DeepCwind semi-submersible, showing that second-order effects are required to reproduce platform motions. The implementation employs a computationally efficient pre-computation strategy for second-order wave excitation forces, reducing simulation cost while maintaining engineering accuracy. Overall, this work advances the tool as an open-source and versatile tool for modelling floating offshore renewable-energy systems requiring second-order hydrodynamic fidelity.

17 WIND ENERGY↗
DOE OSTI2025

Gaussian integral method for void fraction

Here, a novel method, the Gaussian Integral Method (GIM), is presented for calculating void fractions in Computational Fluid Dynamics–Discrete Element Method (CFD-DEM) simulations. GIM is versatile and applicable to various grid types, including structured and unstructured polyhedral meshes, without requiring special boundary treatments. An optimization technique is introduced to make GIM independent of grid resolution and type. The method is validated against experimental data from a fluidized bed, demonstrating that GIM produces realistic simulations closely resembling experimental observations. Additionally, unstructured polyhedral grids using GIM outperform structured grids of equivalent resolution, yielding results more aligned with experimental data. The gradient of the void fraction is computed in the CFD solver and utilized in the DEM solver for precise estimation at particle locations. Overall, GIM provides an effective solution for void fraction calculations in particulate media simulations with complex geometries, enhancing the accuracy and applicability of CFD-DEM simulations for industrial processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Foundational insights into the mechanical and molecular evolution of porcine skin gelatin during gelation

Gelatin is a widely used material in biomedical fields, particularly in regenerative medicine and tissue engineering, due to its biocompatibility and versatile properties. While prior research has explored methods to enhance gelatin's mechanical strength and stability, fundamental studies on gelatin, specifically its curing process, mechanical stiffness, and chemical evolution during gelation, remain limited. This study uses ultrasonic testing and Fourier Transform Infrared Spectroscopy (FTIR) to examine gelatin's stiffness and molecular changes during gelation. Samples of 175 and 300 Porcine Skin Bloom Strength Gelatin at concentrations of 2% and 6% (w/v) were analyzed. Through transmission ultrasonic testing helped identify key transition points in gelation, with higher concentrations exhibiting delayed transitions. FTIR revealed that C-N bond formation peaks early while N-H bond deformation persists. A correlation emerged between sound speed and peak absorbance, suggesting that changes in molecular mobility may contribute to the observed sound speed behavior during periods of active bond formation. However, as gelation continues, fewer bonding components may be available, potentially decreasing molecular movement and contributing to the observed increase in sound speed. These findings provide insights into gelatin's mechanical and chemical evolution, offering a framework for improved control over its gelation kinetics. Swept-Frequency Acoustic Interferometry (SFAI) was performed at the end of the curing process to measure the sound speed, enabling the calculation of the bulk moduli of the gelatin samples. The combined use of ultrasonic and FTIR testing provides a non-destructive method for characterizing gelatin and other biomaterials. This approach advances understanding of gelatin curing behavior and supports the development of safer biomaterials with tailored mechanical properties for various applications such as tissue engineering and regenerative medicine.

Biomaterials↗
DOE OSTI2024

Formation of five-membered ring structures via reactions of o -benzyne

The formation of five-membered ring structures is important for the generation of curved and bowl-shaped polycyclic aromatic hydrocarbons (PAHs) under combustion conditions. Here, we report the identification of the indenyl (C 9 H 7 ) radical – the simplest aromatic hydrocarbon radical carrying an adjacent five- and six-membered ring, as the major product of the o-benzyne (o-C 6 H 4 ) reaction with propargyl (C 3 H 3 ). Because real flames exhibit a complex chemistry, elucidation of a specific reaction is very challenging. Instead, we studied the o-C 6 H 4 + C 3 H 3 reaction in a resistively heated microtubular SiC reactor at controlled conditions of 1150 K and a pressure near 10–20 Torr. To this end, the reactants o-benzyne and propargyl were pyrolytically generated from benzoyl chloride and propargyl bromide. We identified the reactants and the indenyl radical isomer-selectively utilizing photoion mass-selected threshold photoelectron spectroscopy (ms-TPES). In conclusion, the experimentally observed predominant formation of indenyl radicals finally confirms the theoretical predictions of Matsugi and Miyoshi [Phys. Chem. Chem. Phys. 14 (2012), 9722–9728] and highlights a versatile route for the formation of five-membered rings and curved PAHs via reactions of o-benzyne that favor the formation of multiring species over aliphatically substituted aromatic species.

Molecular-weight growth↗
DOE OSTI2026

Investigating the impact of a multi-module operation environment on the task performance time of human operators – An explanatory study

The worldwide demand for Small Modular Reactors (SMRs) has surged in recent years due to their enhanced safety and versatility in supporting diverse industrial sectors. A unique feature of SMR operation is that a single human operator is responsible for managing multiple modules. Therefore, securing a sufficient amount of human performance data pertaining to this new environment is essential for the safe operation of SMRs. In this explanatory study, a series of experiments were conducted using the NuScale simulator, a representative SMR design, with student operators. A total of 12 student operators were assigned two types of off-normal events and asked to cope with them using paper-based procedures. Subsequently, their task performance times were compared with those of student operators responsible for a single unit based on the Task Complexity (TACOM) measure. Results indicate that the performance of student operators under the experimental conditions of this study degraded by a factor of 2 to 3, depending on the characteristics of the off-normal events.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Sentiment analysis of the United States public support of nuclear power on social media using large language models

This study utilized large language models (LLMs) to analyze public sentiment in the United States (US) regarding nuclear power on social media, focusing on X/Twitter, considering climate change challenges and advancements in nuclear power technology. Approximately, 1.26 million nuclear tweets from 2008–2023 were examined to fine-tune LLMs for sentiment classification. We found the crucial role of accurate data labeling for model performance, with potential implications for a 15% improvement, achieved through high-confidence labels. LLMs demonstrated better performance compared to traditional machine learning classifiers, with reduced susceptibility to overfitting and up to 96% classification accuracy. LLMs are used to segment the US public tweets into policy and energy-related categories, revealing that 68% are politically themed. Policy tweets tended to convey negative sentiment, often reflecting opposing political perspectives and focusing on nuclear deals and international relations. Energy-related tweets covered diverse topics with predominantly neutral to positive sentiment, indicating broad support for nuclear power in 48 out of 50 US states. The US public positive sentiments toward nuclear power stemmed from its high power density, reliability regardless of weather conditions, environmental benefits, application versatility, and recent innovations and advancements in both fission and fusion technologies. Negative sentiments primarily focused on waste management, high capital costs, and safety concerns. The neutral campaign highlighted global nuclear facts and advancements, with varying tones leaning towards positivity or negativity. An interesting neutral theme was the advocacy for the combined use of renewable and nuclear energy to attain net-zero goals.

Energy & Fuels↗
DOE OSTI2025

Induction ultrafast sintering

This study proposes and demonstrates induction ultrafast sintering (IUS), which enables rapid densification of refractory and other materials via two contactless modalities: direct IUS (d-IUS), where heating occurs through electromagnetic coupling with the sample, and susceptor IUS (s-IUS), where heating is achieved indirectly via an induction-heated metal case. Ultrahigh heating rates of ∼75 to >450 °C/s and temperatures exceeding 2500 °C are readily achieved. Both d-IUS and s-IUS densify molybdenum to high densities within 120 s, with only ∼1–3 % porosity observed by image analysis. Similarly, 3 mol % yttria-stabilized zirconia (3YSZ) reaches ∼97 % relative density in 30 s via s-IUS. This study further demonstrates ultrafast reactive sintering of two difficult-to-sinter materials: a refractory compositionally complex alloy–carbide (RCCA–CCC) composite, NbMoTaW–(Nb 0.37 Mo 0.11 Ta 0.39 W 0.13 ) 2 C, using d-IUS, and a compositionally complex silicide (CCS), (Mo 1/3 Nb 1/3 Zr 1/3 )Si 2 , using s-IUS. This IUS platform offers a versatile route for high-throughput materials discovery and energy-efficient fabrication of bulk refractory materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

GenAI4UQ: A software for forward and inverse uncertainty quantification using conditional generative AI

We introduce GenAI4UQ, a software package for forward and inverse uncertainty quantification in model calibration, parameter estimation, and ensemble forecasting. GenAI4UQ leverages a generative AI-based conditional modeling framework to address limitations of traditional inverse modeling techniques, such as Markov Chain Monte Carlo (MCMC) methods. By replacing computationally intensive iterative processes with a direct, learned mapping, GenAI4UQ enables efficient calibration of input parameters and generation of predictions directly from observations. The software supports rapid ensemble forecasting with robust uncertainty quantification while maintaining computational and storage efficiency. Built-in auto-tuning of hyperparameters simplifies model training, ensuring accessibility for users with varying expertise. Its versatile conditional generative framework is applicable across diverse scientific domains. While GenAI4UQ offers significant advantages in flexibility and efficiency, users should interpret its uncertainty estimates with caution in data-sparse scenarios, as the model may overestimate uncertainty—an effect common to all surrogate-based approaches including MCMC with surrogate models. Despite this, GenAI4UQ transforms inverse modeling by providing a fast, reliable, and user-friendly solution. It empowers researchers and practitioners to quickly estimate parameter distributions and generate model predictions for new observations, facilitating efficient decision-making and advancing the state of uncertainty quantification in computational modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystem function and soil quality. Salinity influences carbon cycling through direct effects on microbial activity and indirect alterations to soil physicochemical properties including cation exchange, pH, and soil organic carbon availability. Current models inadequately represent these complexities, relying on linear reduction functions that overlook specific physicochemical changes induced by salinity. To address this gap, we propose an integrated model framework, AquaMEND, that combines microbial-explicit carbon decomposition and geochemical models. This model allows cation exchange and surface complexation processes to capture solute chemistry and nutrient availability in soils upon saltwater intrusion. Using response functions that capture salinity impacts on both salt-sensitive and salt-resistant microbial processes, AquaMEND simulates how the abiotic and biotic mechanisms work individually and collectively to regulate organic and inorganic pools and fluxes. Here, the parallel structure of aqueous and non-aqueous phases, together with microbial functions, result in a versatile model for solving dynamic coupling of organics, minerals and microbes under various environmental settings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A bioinspired approach for adaptive solid-solid phase change material coatings with optimized surface features for passive thermal regulation

The necessity to reduce global energy consumption calls for innovative strategies in building thermal management. Passive thermal regulation, particularly through bio-inspired designs, offers a promising avenue by mimicking nature's efficient control of optical properties. This research introduces a novel, climate-responsive coating that integrates optimized bio-inspired surface features with a solid-solid phase change material (SS-PCM) to dynamically manage solar absorptivity without adding additional thickness, enabling both heating and cooling as needed. Drawing on the photonic architectures of the Saharan silver ant and Morpho Didius butterfly, we employed a modeling and multi-objective optimization framework to tailor these surface features. Simulations reveal that surface texture, rather than the intrinsic phase transition of the SS PCM, dominates optical control. Relative to a flat SS PCM coating, optimized isotropic random roughness and broader range features yielded the highest passive heating power increase of about 144 % and 319 % respectively suitable for cold climates. Saharan ant-inspired features enhanced passive cooling for hot climates, achieving a 21.8 % improvement. For moderate climates, Butterfly-wing-inspired surface features provided a balanced enhancement of 19 % for heating and 7 % for cooling. Across all cases, the optimized surface features reduced combined heating and cooling energy demand more effectively than the baseline coating, while preserving material thickness. These findings demonstrate that climate-adaptive, optimized bio-inspired surface features can unlock the full potential of SS PCM coatings, providing a versatile pathway to significant energy savings in buildings and other applications. The methodology establishes a framework for designing next-generation adaptive envelopes that leverage natural photonic principles for high-impact, low-cost thermal regulation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pulsed contact glow discharge electrification for online material quantification

Real-time elemental analysis of liquids in extreme environments remains a significant challenge for sensor development, particularly in applications such as advanced nuclear reactors. Plasma-based optical emission spectroscopy offers a promising solution. In this study, we investigate pulsed contact glow discharge electrolysis (CGDE) as an alternative plasma generation method for emission-based material quantification. Using aqueous NaCl solutions, we examine the role of discharge polarity on plasma behavior, emission characteristics, and spectral output. Our results demonstrate that cathodic discharges generate more energetic plasmas, enabling the detection of ionic species such as cerium, while anodic discharges favor atomic emission. These findings reveal a potential dual-mode sensing capability controlled by circuit configuration rather than hardware changes. Through synchronized measurements of emission, current, bubble, and spectral dynamics, we present a model in which electron emission and ohmic heating drive plasma formation. This model enhances our understanding of pulsed-CGDE and supports its potential as a versatile, adaptable platform for future deployment in high-temperature liquids such as molten salts.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2026

Elucidation of odd-chain dicarboxylate metabolism in Acinetobacter baylyi and application to polyethylene upcycling

Polyethylene (PE) is a versatile polymer, but its end-of-life management is challenging due to its recalcitrant structure. We present a promising approach combining chemical degradation and bio-upcycling to convert postconsumer PE waste into a value-added bioproduct. Specifically, PE was degraded into acetic acid and C 4 –C 7 dicarboxylic acids by nitric acid. We then elucidated the catabolic pathways for glutarate (C 5 ) and pimelate (C 7 ) in the nonmodel bacterium Acinetobacter baylyi ADP1 through RNA sequencing, phenotyping, and enzymatic assays. Whole-genome sequencing of evolved isolates also identified a crucial IclR family transcriptional regulator, DcaS, which acts as a repressor of dicarboxylate metabolism. The reverse-engineered strain exhibited enhanced substrate utilization compared to the wild-type strain. Using rational metabolic engineering, the PE deconstruction products were bioconverted into the valuable chemical lycopene, highlighting the potential of this microbial chassis to produce value-added bioproducts from postconsumer PE waste, thus promoting a circular economy for plastics.

metabolic engineering↗
DOE OSTI2024

Innovative biphasic solvent systems for lignocellulosic biorefinery

Bioconversion of lignocellulosics to ethanol is significantly hindered by biomass recalcitrance and, therefore, often requires a biomass pretreatment step. Furan-based compounds such as furfural (FF) and 5-hydroxymethylfurfural (HMF) are versatile building blocks for fuels and chemicals. However, their production during pretreatment often suffers from low yield and low separation efficiency. Biphasic solvent systems are capable of reducing biomass recalcitrance and extracting furans into the organic phase, thus preventing their degradation, increasing their yield, and allowing much easier separation. The development of a sustainable biphasic solvent system is essential to the furan-driven biorefinery and has drawn significant attention. Finally, this review systematically summarizes recent advances in the development of biphasic solvent systems in lignocellulosic biorefinery for improving the production of liquid fuels and furan-based compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Calibrating cryogenic temperature of TEM specimens using EELS

Cryogenic Scanning/Transmission Electron Microscopy has been established as a leading method to image sensitive biological samples and is now becoming a powerful tool to understand materials' behavior at low temperatures. However, achieving precise local temperature calibration at low temperatures remains a challenge, which is especially crucial for studying phase transitions and emergent physical properties in quantum materials. In this study, we employ electron energy loss spectroscopy (EELS) to measure local cryogenic specimen temperatures. Here we use the temperature-dependent characteristics of aluminum's bulk plasmon peak in EEL spectra, which shifts due to changes in electron density caused by thermal expansion and contraction. We successfully demonstrate the versatility of this method by calibrating different liquid nitrogen cooling holders in various microscopes, regardless of whether a monochromated or non-monochromated electron beam is used. Temperature discrepancies between the actual temperature and the setpoint temperatures are identified across a range from room temperature to 100 K. This work demonstrates the importance of temperature calibrations at intermediate temperatures and presents a straightforward, robust method for calibrating local temperatures of cryogenically-cooled specimens in electron microscopes.

36 MATERIALS SCIENCE↗