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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 217 records · Page 12

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗

From Cryogenic to High Temperatures: A Microstructural Evolution of δ-phase Pu-Ga Alloys Investigated by Time-of-Flight High-resolution Neutron Diffraction

Phase stability and phase transformations in binary Pu alloys are critical for multiple applications. Long-term phase stability affects mechanical properties, microstructure, corrosion behavior, and structural integrity. A clear and detailed understanding of phase transformations and phase stability mechanisms is necessary to assess the behavior and response to unexpected stimuli. Gaining advanced knowledge on the behavior of Pu and Pu alloys at a variety of temperatures, pressures, and time will ensure better predictions and control on evolution outside laboratory measurements.

36 MATERIALS SCIENCE↗

Shake-Down Spectroscopy as State- and Site-Specific Probe of Ultrafast Chemical Dynamics

Tracking the multifarious ultrafast electronic and structural changes occurring in a molecule during a photochemical transformation is a challenging endeavor that benefits from recent experimental and computational progress in time-resolved techniques. Measurements of valence electronic states, which provide a global picture of the bonding structure of the molecule, and core electronic states, which provide insight into the local environment, traditionally require different approaches and are often studied separately. Here, we demonstrate that X-ray pulses from a seeded free-electron laser (FEL) enable the measurement of high-resolution, time-resolved X-ray photoelectron spectra (XPS) that capture weak satellite states resulting from shake-down processes in a valence-excited molecule. This approach effectively combines the advantages of both valence- and core-state investigations. We applied this method to investigate photoexcited CS2 molecules, where the role of internal conversion (IC) and intersystem crossing (ISC) in determining the predissociation dynamics is controversial. We present XPS spectra from photoexcited CS2, obtained at the FERMI FEL. High-resolution measurements, compared to the corresponding spectra obtained from accurate multireference quantum chemical calculations, reveal that shake-down satellite channels are highly sensitive to both valence electronic and geometric changes. Previous studies of the predissociation dynamics have led to uncertain assignments of the branching between singlet and triplet excited states. We derive a propensity rule that demonstrates the spin-selectivity of the shake-downs. This selectivity allows us to unequivocally assign contributions from the bright and dark singlet excited states, with populations tracked along the predissociation dynamic pathway.

Thompson, Henry J. [Univ. of Southampton (United K↗

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗

Time-refraction near the critical angle and angular streaking with attosecond resolution [Invited]

We study the time-refraction of optical waves as they propagate through a time-varying slab and find the frequency shift associated with the abrupt change in the refractive index. We discover a geometrical mechanism responsible for an ultrafast blueshift followed by a redshift, occurring while the refractive index is increased monotonically. Furthermore, we find high sensitivity to incident angles near the traditional critical angle and unravel a new critical angle that varies in time. Finally, we introduce an innovative concept of a streak camera design that utilizes ultrafast nonlinearities in time-varying media and offers attosecond resolution capabilities.

Fruhling, Colton (ORCID:0000000282968802)↗

Atomic-resolution imaging as a mechanistic tool for studying single-site heterogeneous catalysis

Heterogeneous catalysts dominate the chemical industry but typically feature diverse, incompletely defined active sites. Thus, describing structure-activity relationships, unlike homogeneous catalysts, remains challenging. In contrast, molecularly defined single-site heterogeneous catalysts (SSHCs), using appropriate tools, are poised to address these challenges and provide new avenues for catalysis research and development. The present study explores eco-friendly H 2 production mediated by discrete MoO 2 sites supported on carbon nanohorns (CNHs) and active for alcohol dehydrogenation. While informative, detailed ensemble EXAFS/XANES/XPS, kinetic measurements, and DFT analysis alone cannot provide a full molecular picture of the reaction pathway. Here, using single-molecule atomic-resolution time-resolved electron microscopy (SMART-EM), we propose the identification of four key catalytic intermediates anchored to CNHs and uncover a new reaction pathway involving alkoxide/hemiacetal equilibration and acetal oligomerization. Furthermore, these intermediates are inferred through a combination of theory and SMART-EM, showcasing the potential of SMART-EM as a complementary tool for exploring mechanistic hypotheses in catalysis.

36 MATERIALS SCIENCE↗

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗

Identification of Suitable Vacuum Gas Oils as Plasticizers Using HT-GC × GC-HRMS

Vacuum gas oils (VGOs) have long been heralded as effective plasticizers due to their high boiling-points and lubricating properties. One of these VGOs, HyVac Oil 93050, is a paraffinic plasticizer that is currently utilized in polymer–plasticizer explosive formulations, while this oil effectively increases the elasticity and decreases the sensitivity for current formulations. We seek to identify alternative VGOs with similar density, viscosity, molecular composition, and impurities for future formulations. In this study, 18 VGOs, including HyVac Oil 93050, were initially evaluated for their density and viscosity. The oils were then ranked based on physical characteristics and analyzed for molecular composition using high-temperature comprehensive two-dimensional gas chromatography with high-resolution time-of-flight mass spectrometry (HT-GC × GC-HRMS). Further, the HT-GC × GC-HRMS chromatograms of the top 10 most similar VGOs to HyVac Oil 93050, according to density, were compared utilizing the Pearson correlation coefficient. Three of the oils with densities similar to those of HyVac Oil 93050 had a Pearson correlation within the lot-to-lot variation of HyVac Oil 93050. For the top 3 candidates, Pearson correlation was then utilized as a feature selection technique to discover significant chemical differences. Positive chemical ionization (PCI) and negative chemical ionization (NCI) HT-GC × GC-HRMS chromatograms were also evaluated and aided in the discovery and identification of several key compounds including additives that acted as stabilizers for the VGOs. After this further chemical analysis, two of the original 17 potential VGOs were determined to be physically and chemically similar to HyVac Oil 93050.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗

Toward electron temperature profiles in hot-dense plasmas from x-ray spectral ensembles

High repetition rate laser systems enable new strategies for diagnosing plasma behavior with large datasets. Here, we define an ensemble technique that relies on randomized targeting of x-ray tracer micro-stripes. On each shot, a high-intensity laser pulse is focused on a solid target with Ti tracer stripes embedded in an Al foil, randomly targeting a micro-stripe, a portion of a stripe, or a gap between stripes. High-resolution, time-integrated x-ray spectrometers capture line emission from the portion of the micro-stripe that is heated to sufficiently high electron temperatures. Accumulation of many such cases is used to construct ensemble distributions of x-ray line intensities that encompass all relative offsets of the laser focus to the micro-stripe centers. Synthetic intensity distributions are likewise generated using collisional-radiative modeling. Bayesian fitting of modeled to measured intensity distributions establishes the most likely radial temperature profiles, enabling comparison to hydrodynamic models and calling into question the cylindrical symmetry of these micro-stripe-embedded systems. Ensemble techniques have significant potential for high-energy-density plasma diagnostics, especially with the advent of high repetition rate experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Geant4 Simulation of Cherenkov Photons in Perovskite CsPbBr 3 Gamma-Ray Detectors

Perovskite materials have recently attracted significant attention for hard X-ray and gamma-ray detection. Cherenkov light generated by fast electrons due to gamma-ray interaction with the material can be used to provide fast timing information. Here, in this study, we report Geant4 simulation results of Cherenkov photon generation, transport, and detection within perovskite CsPbBr3. The Cherenkov photon yield, energy spectrum and temporal distribution are investigated under different gamma-ray energy deposition within CsPbBr3. CsPbBr 3 has a similar Cherenkov photon yield as of TlBr that has demonstrated fast-timing capability based on Cherenkov light. The effect of crystal volume, surface finish and SiPM photon detection efficiency on the Cherenkov detection is also discussed. This work provides insights into Cherenkov processes of CsPbBr3.

Cherenkov photon↗

C-HER Metadata Overview: Approach, Standards, and Rigor for the Centralized Health and Exposomic Resource

The Centralized Health and Exposomic Resource (C-HER) unifies environmental, demographic, geographic, and health-related data for exposomic research. The source data differ in format, geographic coverage, time period, resolution, terminology, and documentation. We use a common metadata framework to describe those differences and to record how each data resource has been processed, documented, and ingested. This document relates only to the C-HER metadata framework. It explains the information that is recorded for each resource, the standards used to organize that information, the conditions for metadata completeness, and the relationship between metadata and quality review. It is intended for those who need to understand what C-HER metadata communicates and how it supports appropriate use of the data. It is not an implementation specification or procedure. It does not document the database schema, source code, deployment configuration, transformation algorithms, or dataset-specific QA/QC thresholds. Those materials are maintained separately.

MacFarland, Midgie [ORNL] (ORCID:0009000807354078)↗

Characterization of Digital Silicon Photomultipliers

Digital Silicon photomultipliers (Digital SiPMs) have become an increasingly viable option for single-photon detection due to their compact size and precise timing and resolution. The following work characterizes the noise performance of a diSiPM designed and tested in-house at Fermilab. The SiPM consists of a 26x32 array of single-photon avalanche diode (SPAD) cells. Through the implementation of a shift register masking circuit, individual SPAD cells can be enabled and disabled at will, allowing for precise detection measurements of single columns (accumulator channels) and cells. The provided circuit design operates on voltage clock pulses and collects data on clock edges allowing for precise tuning of the data collection process by varying the clock frequency, pulse width, and integration period.

Shoemaker, Oliver [U. Chicago (main)]↗

Crystal Calorimetry for Charged Lepton Flavor Violation Searches

The Mu2e experiment at Fermilab aims to search for Charged Lepton Flavor Violation (CLFV) through the coherent conversion of a muon into an electron in the field of an aluminum nucleus. This process, highly suppressed in the Standard Model, would clearly indicate new physics if observed. A crucial component of Mu2e is its electromagnetic calorimeter, which enhances the identification and measurement of conversion electrons. The calorimeter consists of two disks of undoped CsI crystals read out by custom-designed SiPMs and fast front-end electronics. This paper presents an overview of the calorimeter’s design, its custom SiPM technology, the readout and data acquisition system, and the results from commissioning tests.Building on the experience from Mu2e, the proposed Mu2e-II upgrade aims to enhance further the experiment’s sensitivity by an order of magnitude. This requires significant advancements in calorimeter technology, particularly in crystal materials and photodetector performance. Studies on BaF$_2$ and LYSO crystals, as well as the development of radiation-hard Silicon Photomultipliers (SiPMs), are currently underway. Test beam results demonstrate promising improvements in energy resolution and timing capabilities, ensuring the feasibility of next-generation calorimetry solutions for Mu2e-II.

Atanov, N. [Dubna, JINR]↗

Aerosol Microphysics and Chemical Measurements at Mt. Soledad and Scripps Pier during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) from February 2023 to February 2024 UCSD Library Collection

This dataset includes guest instrument measurements and other PI products for aerosol microphysics and chemical measurements collected at Mt. Soledad and Scripps Pier during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) from February 2023 to February 2024. The measurements include the following instruments at Mt. Soledad: High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS, Aerodyne), Scanning Electrical Mobility Spectrometer (SEMS, Brechtel Manufacturing Inc.), Aerodynamic Particle Sizer (APS, Droplet Measurements Technologies), Single Particle Soot Photometer (SP2, Drople Measurements Technologies), Meteorological Station (WXT520, Vaisala), Ozone (Teco), and trace gas proxies (Teledyne). In addition, the analyses of particle filters collected at Mt. Soledad for three dry-diameter size cuts (<1 micron, <0.5 micron, <0.18 micron) and at Scripps Pier for one dry-diameter size cut (<1 micron) by Fourier Transform Infrared (FTIR) and X-ray Fluorescence (XRF) are reported. A differential mobility analyzer operated as a scanning mobility particle sizer (SMPS, TSI Inc.), a printed particle optical spectrometer (POPS, Grimm), and a continuous flow diffusion cloud condensation nuclei (CCN, DMT) counter provide the mobility aerosol size distribution (30-360 nm), optical size distribution (150 - 6000 nm), size-resolved CCN distribution (30-360 nm) at 0.2, 0.4, 0.6, 0.8, and 1.0% supersaturation. Measurements are reported for both sampling from an isokinetic aerosol inlet and from a Counterflow Virtual Impactor (CVI, Brechtel Manufacturing Inc.). The data are available at the following link: https://library.ucsd.edu/dc/collection/bb0898306q

54 ENVIRONMENTAL SCIENCES↗

Data analytics for intermodal freight transportation applications

With the growth of intermodal freight transportation, it is important that transportation planners and decision-makers are knowledgeable about freight flow data to make informed decisions. This is particularly true with Intelligent Transportation Systems (ITS) offering new capabilities for intermodal freight transportation. Specifically, ITS enables access to multiple different data sources, but they have different formats, resolutions, and time scales. Thus, knowledge of data science is essential to be successful in future ITS-enabled intermodal freight transportation systems. This chapter discusses the commonly used descriptive and predictive data analytic techniques in intermodal freight transportation applications. These techniques cover the entire spectrum of univariate, bivariate, and multivariate analyses. In addition to illustrating how to apply these techniques manually, this chapter will also show how to apply them using the statistical software R. Additional exercises are provided for those who wish to apply the described techniques to more complex problems.

Huynh, Nathan↗