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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development of a direct-sampling RF receiver for precision beam charge measurements in the MOLLER experiment

Here, we have developed and tested a direct-sampling RF receiver capable of measuring the amplitude of a 1497 MHz sinusoidal beam signal in 0.5 ms integration windows with a relative uncertainty of better than 10 parts per million. The receiver is intended for measuring signals from beam current monitoring cavities on the beamline of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The beam signal strength, frequency, and integration window fulfill the thus far unmet requirements of the upcoming MOLLER experiment to measure the beam charge for different helicity states.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Search for stealth supersymmetry in final states with two photons, jets, and low missing transverse momentum in proton-proton collisions at s = 13 TeV

The results of a search for stealth supersymmetry in final states with two photons and jets, targeting a phase space region with low missing transverse momentum ( p T miss ), are reported. The study is based on a sample of proton-proton collisions at s = 13 TeV collected by the CMS experiment, corresponding to an integrated luminosity of 138 fb - 1 . As LHC results continue to constrain the parameter space of the minimal supersymmetric standard model, the low p T miss regime is increasingly valuable to explore. To estimate the backgrounds due to standard model processes in such events, we apply corrections derived from simulation to an estimate based on a control selection in data. The results are interpreted in the context of simplified stealth supersymmetry models with gluino and squark pair production. The observed data are consistent with the standard model predictions, and gluino (squark) masses of up to 2150 (1850) GeV are excluded at the 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement of Energy Correlators inside Jets and Determination of the Strong Coupling α S ( m Z )

Energy correlators that describe energy-weighted distances between two or three particles in a hadronic jet are measured using an event sample of s = 13 TeV proton-proton collisions collected by the CMS experiment and corresponding to an integrated luminosity of 36.3 fb − 1 . The measured distributions are consistent with the trends in the simulation that reveal two key features of the strong interaction: confinement and asymptotic freedom. By comparing the ratio of the measured three- and two-particle energy correlator distributions with theoretical calculations that resum collinear emissions at approximate next-to-next-to-leading-logarithmic accuracy matched to a next-to-leading-order calculation, the strong coupling is determined at the Z boson mass: α S ( m Z ) = 0.122 9 − 0.0050 + 0.0040 , the most precise α S ( m Z ) value obtained using jet substructure observables. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

GRinding Automated Classification Engine

This work is an ML-driven framework for automated surface analysis of microscopy images. We create a training dataset by imaging stainless steel samples to benchmark four developed deep neural network architectures. These models, based on a YOLOv8n-cls backend, integrate image features and process metadata using various fusion methods to distinguish between acceptable and unacceptable surface finishes. This code is associated with publication "Classifying Alloy Surface Preparation Quality with Metadata-Infused Machine Learning for Rapid Alloy Discovery" for project APEX LDRD-ER (25-ERD-039)

Gongora, AldairE [Lawrence Livermore National Labo↗
DOE OSTI2026

2019 California Vehicle Survey

The 2019 California Vehicle Survey of residential and commercial light-duty fleet owners in California assessed consumer preferences for vehicles and included a targeted sample of plug-in electric vehicle (PEV) owners. In addition to economic and demographic data, the survey integrated light-duty vehicle holding and use information with vehicle choice data, which was collected via a set of eight exercises on vehicle and fuel type choice. The PEV owner survey participants provided additional data on charging behavior, electricity rates, and their main motivations for purchasing PEVs.

1Hz data↗
DOE OSTI2022

Small Punch Testing of Molybdenum-99 Targets

Northstar Medical Radioisotopes is developing an accelerator-based method to produce 99 Mo, which is a parent isotope of the commonly used 99m Tc medical isotope. The Mo targets being designed for the accelerator will be produced from enriched 100 Mo, also known as aMo . Pressed and sintered powder feedstock is used to fabricate aMo targets, producing 29 mm disk-shaped targets. The targets are subjected to 1–6 days in line of an electron beam with subsequent dissolution of the disk to retain the 99 Mo, which decays to 99m Tc at radio-pharmacies. The press and sinter method is advantageous because the inherent porosity produced by this method enables increased surface area and therefore increased flow of dissolution media, decreasing the dissolution time and reducing the need for a highly acidic media. Although porosity aids in dissolution, it reduces the mechanical strength and ductility. Targets require good mechanical integrity when subjected to the conditions in the accelerator. Therefore, Northstar is seeking methods to rapidly test disk samples after fabrication to assure mechanical performance metrics are achieved. This report details the design and testing of a small punch test (SPT) that accommodates the 29 mm disk. Initial data were used to relate the SPT data to tensile properties, such as the yield strength (YS), ultimate tensile strength (UTS), and total elongation to failure. Although the SPT has been established as a somewhat reliable method for testing metallic materials, few studies have applied the SPT to refractory materials such as Mo. Based on tensile testing performed at Oak Ridge National Laboratory on different Mo samples, correlation between the Mo tensile and SPT properties could be performed, establishing a standard calibration that could be applied to other Mo samples. To test the efficacy of the SPT with Mo, multiple different disk batches were fabricated under different conditions (e.g., pressure, lubricant) with commercially available pure Mo powder. Generally, only a UTS could be well defined because the press and sinter disks failed under brittle fracture, making it difficult to determine the YS and elongation. Compared with disks fabricated with aMo powder, the aMo samples underperformed their pure nat Mo counterparts. This report summarizes the current status of the SPT, but further evaluation is needed before it can be applied as a reliable quality assurance tool.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Pull Force Evaluation of CCS Insulated End Caps

Insulated end caps installed on DC pins of Combined Charging System (CCS) inlets have been identified as potential debris sources within electric vehicle supply equipment (EVSE) connectors, increasing the risk of electric shock and fire hazards. Although standards such as IEC 62196-1:2022 specify mechanical pull-force requirements for these end caps, it remains unclear whether these requirements provide adequate robustness under real-world conditions. To address this concern, the National Charging Experience (ChargeX) Consortium's Hardware Task Force conducted evaluations of insulated end caps used in OEM CCS inlets. This study assesses the performance of insulated end caps used in OEM CCS inlets, specifically those installed on DC pins, using the procedures defined in IEC 62196-1:2022 (Section Sign) 26.7 and SAE J3400, supplemented by additional experimental conditioning. To ensure relevance to real-world conditions, NLR collaborated with charging network operators (CNOs) to guide the selection of charging inlet samples. Material analyses of the insulated end cap samples were conducted to confirm that the tested materials reflected the types and properties commonly observed in the field. The selected samples underwent temperature and humidity conditioning followed by pull-force testing to evaluate the end-cap integrity. Although SAE J3400 inlets were not directly tested due to limited diversity in available field data, the underlying end-cap principles between CCS and SAE J3400 are comparable, allowing the study's insights to be relevant to both technologies. Overall, this study provides a structured evaluation framework to inform potential refinements to mechanical pull-force requirements in charging standards.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Source apportionment of aerosols at the White River IMPROVE site near the SAIL site

This data set contains source apportionment results at the White River IMPROVE site (39.1536, -106.8209), which is about 30 km north of the Surface Atmosphere Integrated Field Laboratory (SAIL) Campaign site. The IMPROVE network (Malm et al. 1994) collected 24-hour aerosol filter samples every three days over several decades at this site. Chemical concentrations in the PM2.5 fraction of 19 elements (Al, As, Br, Ca, Cl, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Se, Si, Ti, V, and Zn), along with nitrate, sulfate, elemental carbon (EC), organic carbon (OC), and calculated coarse mass concentrations (PM10−PM2.5 mass concentrations), from 2014 to 2023, were used as input for the PMF analysis. PMF was performed using EPA PMF 5.0 (Norris et al. 2014). A five-factor solution was chosen as the optimal solution. These factors were identified as coarse dust, fine dust, biomass burning, sulfate-dominated, and nitrate-dominated sources. This data set is useful for understanding aerosol sources and their long-term variability near this region.

biomass burning↗
DOE OSTI2021

Measurement of the top quark mass using events with a single reconstructed top quark in pp collisions at $$ \sqrt{s} $$ = 13 TeV

A measurement of the top quark mass is performed using a data sample enriched with single top quark events produced in the t channel. The study is based on proton- proton collision data, corresponding to an integrated luminosity of 35.9 fb -1 , recorded at √s = 13 TeV by the CMS experiment at the LHC in 2016. Candidate events are selected by requiring an isolated high-momentum lepton (muon or electron) and exactly two jets, of which one is identified as originating from a bottom quark. Multivariate discriminants are designed to separate the signal from the background. Optimized thresholds are placed on the discriminant outputs to obtain an event sample with high signal purity. The top quark mass is found to be $172.13^{+0.76}_{-0.77}$ GeV, where the uncertainty includes both the statistical and systematic components, reaching sub-GeV precision for the first time in this event topology. The masses of the top quark and antiquark are also determined separately using the lepton charge in the final state, from which the mass ratio and difference are determined to be $0.9952^{+0.0079}_{-0.0104}$ and $0.83^{+1.79}_{-1.35}$ GeV, respectively. The results are consistent with CPT invariance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Förster Resonance Energy Transfer and Enhanced Emission in Cs 4 PbBr 6 Nanocrystals Encapsulated in Silicon Nano-Sheets for Perovskite Light Emitting Diode Applications

Encapsulating Cs 4 PbBr 6 quantum dots in silicon nano-sheets not only stabilizes the halide perovskite, but also takes advantage of the nano-sheet for a compatible integration with the traditional silicon semiconductor. Here, we report the preparation of un-passivated Cs 4 PbBr 6 ellipsoidal nanocrystals and pseudo-spherical quantum dots in silicon nano-sheets and their enhanced photoluminescence (PL). For a sample with low concentrations of quantum dots in silicon nano-sheets, the emission from Cs 4 PbBr 6 pseudo-spherical quantum dots is quenched and is dominated with Pb 2+ ion/silicene emission, which is very stable during the whole measurement period. For a high concentration of Cs 4 PbBr 6 ellipsoidal nanocrystals in silicon nano-sheets, we have observed Förster resonance energy transfer with up to 87% efficiency through the oscillation of two PL peaks when UV excitation switches between on and off, using recorded video and PL lifetime measurements. In an area of a non-uniform sample containing both ellipsoidal nanocrystals and pseudo-spherical quantum dots, where Pb 2+ ion/silicene emissions, broadband emissions from quantum dots, and bandgap edge emissions (515 nm) appear, the 515 nm peak intensity increases five times over 30 min of UV excitation, probably due to a photon recycling effect. This irradiated sample has been stable for one year of ambient storage. Cs 4 PbBr 6 quantum dots encapsulated in silicon nano-sheets can lead to applications of halide perovskite light emitting diodes (PeLEDs) and integration with traditional semiconductor materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Design and analysis of actively-cooled, edge-transport diagnostic for long-pulsed operation in WEST

Next step fusion devices that will operate in steady-state will require complex plasma-facing components (PFCs) that can survive the harsh environment over long timescales not common in current devices. This will require robust plasma facing surfaces that are integrated with active cooling systems. In a collaboration between CEA and ORNL, a plasma-interacting diagnostic is being designed for the W Environment in Steady-state Tokamak (WEST) in Cadarache, France which requires plasma-facing protection like those needed for steady-state PFCs. This integrated diagnostic studies edge transport and impurity migration within WEST, and is planned to include imbedded temperature Langmuir probe sensors, as well as removeable sample slots for ex-situ surface analysis of plasma-material interactions. The entire assembly is expected to move into the plasma edge for periods up to 1000 s having an energy removeable capability of ∼6 kW and seeing a peak heat flux of more than 7 MW/m2. The assembly compliments WEST high fluence campaigns that plan for multiple 1000 s pulses. Within these specifications, the assembly will require a refractory metal plasma facing surface and integral cooling in order to function within the limited space allotted for such diagnostics. Because of the limited space and linear actuator needs, additive manufacturing of the high heat flux working end of the assembly is being considered which could allow for precision cooling-channels and lighter weight designs. Conceptual design along with simulation and analysis results will be presented for this complex diagnostic with novel PFCs.

Lumsdaine, Arnold↗
DOE OSTI2026

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗
DOE OSTI2024

A Framework to Demonstrate a DNP3 Interface With a CIM-Based Data Integration Platform: Preprint

The contemporary electrical grid is characterized by its complexity and abundance of data. A control-rich environment supported by information and communication technologies within an Advanced Distribution Management System (ADMS) presents a viable and cost-effective option for utility companies aiming to implement advanced real-time analytical schemes for monitoring and remotely controlling distribution feeders. Modular platform-based approaches to distribution operations require a structured framework for acquiring field device measurements, performing analytics, converting the setpoint to the correct protocol, and sending it on the appropriate communications network to the field devices. We present the development and deployment of an application service to integrate an open-source standardsbased platform with an ADMS test bed with field devices using the Distributed Network Protocol (DNP3) for data exchange. The step-by-step procedure for establishing the DNP3-Master service on an open-source distribution platform is outlined, comprehensively explaining the Master setup process. Moreover, sample use case results highlight the capabilities of the DNP3- Master service setup. Results demonstrate the scalability and configurability of the DNP3-Master service, making it adaptable for integration with other relevant applications, thus providing potential opportunities for real-world field trials and real-time assessments.

ADMS↗
DOE OSTI2022

Integration of Large-Scale Electrical Imaging into Geological Framework Development and Refinement

Geologic framework models (GFMs) are critical to the construction of reliable simulation models of groundwater flow and contaminant transport. To support GFM development, direct information (e.g., core samples, fluid samples, hydraulic testing) tends to be sparse and separated by large distances relative to the spatial scales of aquifer heterogeneity. There are additional challenges associated with highly contaminated legacy waste sites, where drilling is particularly costly, and invasive sampling requires specialized handling and disposal of hazardous materials. At these sites in particular, non-invasive geophysical imaging can play an important role in filling spatial gaps between boreholes and reducing characterization costs by optimizing and minimizing the number of necessary boreholes. Here this paper presents a case study demonstrating the use of large-scale (> 30 km 2 ) electrical mapping to identify hydrostratigraphy and potential paleochannels at the Hanford Site, located in Washington State, USA. In two field campaigns, over 36 line-kilometers of electrical resistivity tomography (ERT) data were collected along 14 transects. ERT surveys were sited and performed to image critical aspects (e.g., paleochannels, stratigraphic contacts) of the subsurface, demonstrating a general workflow for integrating ERT with GFM development. Inconsistencies between the GFM and ERT were catalogued to provide a basis for future site characterization using complementary geophysical methods and (or) direct sampling.

58 GEOSCIENCES↗
DOE OSTI2024

Identification of integrated proteomics and transcriptomics signature of alcohol-associated liver disease using machine learning

Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Raman Spectroscopic In Situ Monitoring of Highly Turbid Media

The ability to run chemical processing more efficiently and cost effectively is a need that spans critical materials recovery and legacy nuclear waste cleanup. Sensors integrated to provide online monitoring are essential to addressing this need by providing near-real time feedback on process conditions, which can improve efficiency, aid in decision making, and reduce the need for grab sample measurements. Optical spectroscopy is well-suited for providing online chemical composition information and has been widely applied in varied chemical systems. However, applications in turbid matrices continue to represent substantial challenges to sensor performance, where absorption or scattering of excitation light can cause significant signal interference. Here, in this study, close-focus Raman probes are investigated for use in turbid media as a way to overcome the signal loss from the scattering of the Raman excitation source. This, paired with advanced data science techniques, allowed for the development of chemometric models for the accurate quantification of several analytes of interest (NO 3 – , NO 2 – , and PO 4 3– ) in highly turbid solutions with solids loadings of up to 20 wt %. This work focuses on offline sample measurement and characterization as an initial step toward the development of online monitoring capabilities. Chemical systems of interest were focused on nuclear waste at the Hanford Site, which represents highly complex matrices that could realize significant processing benefits through the integration of online monitoring.

Felmy, Heather M. [Pacific Northwest National Labo↗
DOE OSTI2025

Luminosity measurement for lead-lead collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV in 2015 and 2018 at CMS

Measurements of the luminosity delivered to the CMS experiment during the lead-lead data-taking periods in 2015 and 2018 are presented for the first time. The collisions were recorded at a nucleon-nucleon center-of-mass energy of 5.02 TeV; the 2018 data sample is three times larger than the 2015 data sample. Three subdetectors are used: the pixel luminosity telescope, the forward hadron calorimeters, and the fast beam conditions monitor. The absolute luminosity calibration is determined using the van der Meer technique that relies on transverse beam separation scans. The dominant sources of uncertainty are the transverse factorizability of the bunch density profiles and, in 2015, the difference between the results obtained using various detectors. The total uncertainty in the integrated luminosity, including the stability of the calibrated subdetector response over time, amounts to 3.0% for 2015, 1.7% for 2018, and 1.6% for the combined data sample.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quantifying electron temperature distributions from time-integrated x-ray emission spectra

K-shell x-ray emission spectroscopy is a standard tool used to diagnose the plasma conditions created in high-energy-density physics experiments. In the simplest approach, the emissivity-weighted average temperature of the plasma can be extracted by fitting an emission spectrum to a single temperature condition. It is known, however, that a range of plasma conditions can contribute to the measured spectra due to a combination of the evolution of the sample and spatial gradients. In this work, we define a parameterized model of the temperature distribution and use Markov Chain Monte Carlo sampling of the input parameters, yielding uncertainties in the fit parameters to assess the uniqueness of the inferred temperature distribution. Here we present the analysis of time-integrated S and Fe x-ray spectroscopic data from the Orion laser facility and demonstrate that while fitting each spectral region to a single temperature yields two different temperatures, both spectra can be fit simultaneously with a single temperature distribution. We find that fitting both spectral regions together requires a maximum temperature of $1310^{+90}_{-70}$ eV with significant contributions from temperatures down to 200 eV.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗