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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Identification of process related trace level impurities in the actinide decorporation agent 3,4,3-LI(1,2-HOPO): Nozzle–skimmer fragmentation via ESI LC–QTOFMS

We report that 3,4,3-LI(1,2-HOPO) is a chelating ligand and decorporation agent that can remove radioactive lanthanides and actinides from the body. Identification of trace impurities in drug samples is gaining much interest due to their significant influence on drug activity. In this study, trace impurities were detected in manufactured lots of 3,4,3-LI(1,2-HOPO) by a developed method of Liquid Chromatography coupled with photo-diode array UV detection and Electrospray Ionization-Quadrupole Time of Flight Mass spectrometry (LC-QTOFMS), via induced-in-source or collision-induced mass fragmentation (Nozzle-Skimmer Fragmentation). Molecular ions were fragmented within the nozzle-skimmer region of electrospray ionization (ESI) mass spectrometer equipped with a Time of Flight detector. Eight major (detected at levels higher than a 0.1% threshold) and seven minor trace impurities were identified. The respective structures of these impurities were elucidated via analysis of the generated fragment ions using mass fragmentation and elemental composition software. Proposed structures of impurities were further confirmed via isotopic modeling.

3,4,3-LI(1,2-HOPO) ligand↗
DOE OSTI2022

Identification and demonstration of roGFP2 as an environmental sensor for cryogenic correlative light and electron microscopy

Cryogenic correlative light and electron microscopy (cryo-CLEM) seeks to leverage orthogonal information present in two powerful imaging modalities. While recent advances in cryogenic electron microscopy (cryo-EM) allow for the visualization and identification of structures within cells at the nanometer scale, information regarding the cellular environment, such as pH, membrane potential, ionic strength, etc., which influences the observed structures remains absent. Fluorescence microscopy can potentially be used to reveal this information when specific labels, known as fluorescent biosensors, are used, but there has been minimal use of such biosensors in cryo-CLEM to date. Here we demonstrate the applicability of one such biosensor, the fluorescent protein roGFP2, for cryo-CLEM experiments. At room temperature, the ratio of roGFP2 emission brightness when excited at 425 nm or 488 nm is known to report on the local redox potential. When samples containing roGFP2 are rapidly cooled to 77 K in a manner compatible with cryo-EM, the ratio of excitation peaks remains a faithful indicator of the redox potential at the time of freezing. Using purified protein in different oxidizing/reducing environments, we generate a calibration curve which can be used to analyze in situ measurements. As a proof-of-principle demonstration, we investigate the oxidation/reduction state within vitrified Caulobacter crescentus cells. The polar organizing protein Z (PopZ) localizes to the polar regions of C. crescentus where it is known to form a distinct microdomain. Finally, by expressing an inducible roGFP2-PopZ fusion we visualize individual microdomains in the context of their redox environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Identification of sub-grains and low angle boundaries beyond the angular resolution of EBSD maps

A new method called ALGrId (Anti-Leak GRain IDentification) is proposed for the detection of sub-grains beyond the relative angular resolution of Electron Backscatter Diffraction maps. It does not use any additional information such as Kikuchi Pattern Quality map nor need data filtering. It uses a modified Dijkstra algorithm which seeks the continuous set of boundaries having the highest average disorientation angle. - Highlights: • ALGrId is a new method to identify sub-grains and low angle boundaries in EBSD maps. • Unlike classical methods, ALGrId works even beyond the relative angular resolution. • If the orientation noise peaks at 0.7°, ALGrid detects 0.4°-boundaries correctly. • In the same example, the classical algorithm identifies 1.1°-boundaries only.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Identification of the mechanism that confers superhydrophobicity on 316L stainless steel

This study develops a rapid method to confer superhydrophobicity on 316L stainless steel surfaces with an amphiphilic reagent such as dodecanoic acid. The highest contact angle (approaching 173°) was obtained after forming hierarchical structures with a non-aqueous electrolyte by an electrolytic process. Our goal was to induce superhydrophobicity directly on 316L stainless steel substrates and to establish which molecules cause the effect. The superhydrophobic behaviour is analysed by contact angle measurements, scanning electron microscopy (SEM), IR spectroscopy and atomic force microscopy (AFM). The growth mechanism is analysed using FE-SEM, TOF-SIMS and XPS in order to determine the molecules involved in the reaction and the growth. The TOF-SIMS analysis revealed that the Ni{sup 2+} ions react with lauric acid to create an ester on the stainless steel surface. - Highlights: • This study develops a rapid and facile approach to impart superhydrophobicity properties to 316L stainless steel surfaces with an amphiphilic reagent such as dodecanoic acid. Surface character changes from superhydrophilicity to superhydrophobicity. • This process changes the surface character from superhydrophilicity to superhydrophobicity. • The process based on electrolysis of a nickel salt in lauric acid provides superhydrophobic behaviour in 316L stainless steel. • The growth mechanism is proposed as a mode island (Volmert- Weber mode). • TOF-SIMS and XPS provided the identification of the molecules involved in the surface modification reaction on AISI 316L inducing superhydrophobicity.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Identification of sigma and chi phases in duplex stainless steels

The aim of this work is to find out the most suitable method for detecting and analyzing accurately the formation conditions of secondary phases, particularly Sigma-phase (σ-phase) and Chi-phase (χ-phase) in duplex stainless steels (UNS S32205 and UNS S32750). The microstructure was characterized after a solution annealing at 1080 °C followed by an isothermal heating at 830 °C for different time ranges, ranging from 1 min to 9 h, in order to enlighten the controversial point concerning the mechanism of χ-phase nucleation in relation with the σ-phase. Etched samples were observed using optical microscopy (MO), and scanning electron microscopy (FESEM) with a backscattered electron detector (BSE) was used on unetched samples. Compositional microanalysis (EDS) was carried out for identifying the different phases present in the steels. Sigma phase was easily observed using different etching procedures, whereas χ-phase was only clearly detected with FESEM–BSE on unetched samples. The compositional analyses showed that the molybdenum content in χ-phase almost doubles the content of this element in σ-phase, and as a result the kinetics of nucleation and growth were also found to be remarkably faster when the alloy content in the steel is higher. In addition, chromium nitrides and carbides were also observed to precipitate as a result of the heat treatments and, in the case of the chromium nitrides, they act as a favorable site for the nucleation of σ-phase and χ-phase. - Highlights: • Microscopy was used on heat treated duplex steels for microstructure identification. • FESEM–BSE observation on unetched samples provided the best contrast between phases. • Analyses of carbides, nitrides, chi and sigma phases were possible by EDS and WDS. • Chromium nitrides act as favorable site for the nucleation of chi and sigma phases. • Secondary phases nucleation kinetics are faster in superduplex than in duplex steels.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Ghost microstructure evolution and identification in the coarse grain heat affected zone of 2.25Cr-1Mo-V-Ti steel using tint etching

Microstructural characteristics of the CGHAZ (coarse grained heat affected zone) made of the 2.25Cr-1Mo-V-Ti material for the thermal power plant boiler tube were discussed using the technique of tint etching. To conduct the micro structural characterization, the sample on which CGHAZ was produced by using a high temperature thermal cycle simulator, Gleeble 3500 equipment was used for comparative analyses using the existing Nital etching (ASTM E407-74) and the alkaline etching (ASTM E40785). The latter was used to observe a specific phase. For the microstructure on which the alkaline etching was experimented, the shape of a black strip (Ghost microstructure) in a few microns was observed, which was not observed from the Nital etching. It was found from the phase identifications based EPMA, EBSD and TEM experiments that the image of the black strip in a few microns represented the alpha phase in which C, Cr and Mo became segregated. In addition, it was verified that austenite and M{sub 23}C{sub 6} phase were present around the segregated zone. Based on such results, the mechanism by which the image of the black strip in a few microns was formed at the CGHAZ. In this study, we have investigated the mechanism of the appeared black strip in the CGHAZ. - Highlights: •Ghost microstructure was observed which was not observed from the nital etching. •Ghost microstructure has high concentrations of carbon and molybdenum than matrix. •Schematic illustration proposed of why Ghost microstructure was generated. •Ghost microstructure caused by partial dissolution of M{sub 23}C{sub 6} precipitation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The optimal use of silicon pixel charge information for particle identification

Particle identification using the energy loss in silicon detectors is a powerful technique for probing the Standard Model (SM) as well as searching for new particles beyond the SM. Traditionally, such techniques use the truncated mean of the energy loss on multiple layers, in order to mitigate heavy tails in the charge fluctuation distribution. We show that the optimal scheme using the charge in multiple layers significantly outperforms the truncated mean. Furthermore, truncation itself does not significantly degrade performance and the optimal classifier is well-approximated by a linear combination of the truncated mean and truncated variance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Assessment of the associated particle technique with high-resolution gamma-ray spectroscopy for in-field identification of chemical warfare agents and explosives

In this work, high-resolution prompt γ-ray neutron activation analysis (PGNAA) is performed using the associated particle (AP) technique with a deuterium-tritium neutron generator and high-purity germanium detector. Although the time resolution is inferior compared to similar systems employing fast scintillation γ-ray detectors, the strong background suppression combined with the high γ-ray energy resolution provides an important boost in sensitivity to certain key elements, especially relevant to field measurements of complex chemicals encased within thick layers of metal, such as in the case of recovered chemical warfare (CW) munitions. Results for various CW and explosive simulants contained within mock munitions are presented and compared with results obtained from traditional PGNAA measurements without the aid of the AP technique. Significant improvements in identification and discrimination between certain chemicals are achieved with the high energy resolution AP technique.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Noise signal identification in time projection chamber data using deep learning model

Deep learning has been employed in various scientific fields and has provided promising results. Here, in this study, a deep learning classifier was implemented to improve the quality of data obtained from a time projection chamber. Digital waveforms of the detected signals were classified into the following three categories: particles, noises, and particles piled up with noises. A simple 1-dimensional convolutional neural network was developed for the classification. The model demonstrated an excellent performance on the test dataset. Its practical performance was also examined using track images and particle identification plots by comparing the original and clean data without the noise signals. The comparison clearly showed that the deep learning model improved the quality of data. The current study presents an effective application of the deep learning model for the time projection chamber data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Characterization of a platform for the gas transport, collection, and identification of fission products in the high-intensity laser environment

Recent progress in the production of laser accelerated high flux proton beams opens new possibilities for the study of fission in unique environments. To this end, we are currently pursuing the development of a platform for the swift gas transport, collection, and identification of fission products. Fission is induced in targets fixed inside a sealed chamber through which a carrier gas flows, transporting fission products to a carbon filter for collection and online spectroscopy. This has been recently demonstrated using target normal sheath accelerated protons at the PHELIX laser facility. There were large discrepancies between measured rates and those expected based on established fission yields and measured beam parameters. These discrepancies prompted a large number of tests at the Idaho Accelerator Center (IAC), where fission in uranium is induced by bremsstrahlung photons generated by 21 MeV electrons from a linear electron accelerator. Here, the results are compared to a series of models that account for the slowing of energetic fission fragments in the carrier gas and the fluid dynamics of the gas flow that transports fission products to the collection filter. Characterization of the apparatus reveals a few mechanisms that together account for a portion of the previously observed discrepancies at the PHELIX laser facility. However, additional research is necessary before high-accuracy experiments can be performed with the apparatus. Work performed under the auspices of the U.S. Department of Energy by LLNL under contract DE-AC52-07NA27344.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Simulation studies related to the particle identification by the forward and backward RICH detectors at Electron Ion Collider

The Electron-Ion collider (EIC) will be the ultimate facility to study the dynamics played by colored quarks and gluons in the phenomenology of nucleons and nuclei, described by Quantum Chromodynamics. The physics programs will greatly rely on efficient particle identification (PID) in both the forward and the backward regions. The forward and the backward RICHes of the EIC have to be able to cover wide acceptance and momentum ranges; in the forward region a dual radiator RICH (dRICH) is foreseen and in the backward region a proximity-focusing RICH can be foreseen to be employed. The geometry and the performance studies of the dRICH have been performed as prescribed in the EIC Yellow Report using the ATHENA software framework. Furthermore, this part of our work reports the effort following the call for EIC detector proposal and the studies related to the forward and the backward RICH performance. In the forward region, the dRICH performance showed a pion- kaon separation from around 1 GeV/c to 50 GeV/c at a three sigma level; the proximity focusing RICH (pfRICH) foreseen for the backward region can reach three sigma separation up to 3 GeV/c for e/$π$ and up to 10 GeV/c for $π$/K mass hypotheses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A virtual Frisch-grid geometry-based CZT gamma detector for in-field radioisotope identification

Here, we present a Virtual Frisch-Grid geometry-based CZT gamma detector developed for identifying different radioisotopes over an energy range from a few keV up to 2 MeV, and useful for efficient characterization of CZT crystals. The detector is built with a 3 x 3 matrix of CZT crystals, each measuring approximately 6 mm x 6 mm x 15 mm. The charge generated within the sensor’s active volume is read out via an anode connected directly to the AVG3_Dev integrated circuit. A current signal induced by charge drift is collected on side pads of the crystals, enabling reconstruction of a 3D interaction position. This paper discusses the design, development, and performance of the standalone, mobile detector system, which integrates the AVG3_Dev readout IC developed at Brookhaven National Laboratory, a high-speed FPGA-based with per-channel digital signal processing, and embedded system capabilities. The device is compact, battery-powered, and supports wireless data streaming, making it suitable for field operations for radioisotope identification.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Simulation study for particle identification with the dRICH of the ePIC experiment at the EIC

The dual-radiator Imaging Cherenkov detector (dRICH), employing an aerogel and a gas radiator, is a key component of the forward particle identification system for the ePIC experiment at the Electron-Ion Collider (EIC). This study evaluates the dRICH performance using Geant4 simulations in the context of the global ePIC simulation stack, focusing on the optimization of the aerogel radiator and the impact of sensor noise. We compare two aerogel configurations: the initial design (n = 1.019) and the current default (n = 1.026). The latter, characterized by improved optical properties and a higher refractive index, demonstrates enhanced π/K separation at high momenta, effectively extending the operational overlap with the C 2 F 6 gas radiator (n = 1.00076 at 25 °C, as implemented in the simulation software). Additionally, the study investigates the impact of Silicon Photomultiplier (SiPM) dark noise, showing that a 300 kHz noise rate per 3mm x 3mm channel leads to a moderate reduction (approximately 1.5 GeV/c) in the 3σ separation threshold. These results validate the current dRICH design and quantify the purity levels achievable for both radiators under expected experimental conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Unsupervised domain adaptation for radioisotope identification in gamma spectroscopy

Training machine learning models for radioisotope identification using gamma spectroscopy remains an elusive challenge for many practical applications, largely stemming from the difficulty of acquiring and labeling large, diverse experimental datasets. Simulations can mitigate this challenge, but the accuracy of models trained on simulated data can deteriorate substantially when deployed to an out-of-distribution operational environment. In this study, we demonstrate that unsupervised domain adaptation (UDA) can improve the ability of a model trained on synthetic data to generalize to a new testing domain, provided unlabeled data from the target domain are available. Conventional supervised techniques are unable to utilize this data because the absence of isotope labels precludes defining a supervised classification loss. Instead, we first pretrain a spectral classifier using labeled synthetic data and subsequently leverage unlabeled target data to align the learned feature representations between the source and target domains. We compare a range of different UDA techniques, finding that minimizing the maximum mean discrepancy (MMD) between source and target feature vectors yields the most consistent improvement to testing scores. For instance, using a custom transformer-based neural network, we achieved a testing accuracy of $0.904 \pm 0.022$ on an experimental LaBr test set after performing unsupervised feature alignment via MMD minimization, compared to $0.754 \pm 0.014$ before alignment. Overall, our results highlight the potential of using UDA to adapt a radioisotope classifier trained on synthetic data for real-world deployment.

Lalor, Peter W.↗
DOE OSTI2026

Identification of Common Types of Plastics by Vibrational Spectroscopic Techniques

Polyethylene Terephthalate (PET), High-Density Polyethylene (HDPE), Polyvinyl Chloride (PVC), Low-Density Polyethylene (LDPE), Polypropylene (PP), and Polystyrene (PS) account for most plastic use worldwide, with production nearing 380 million tons annually. A considerable portion enters municipal solid waste and landfills, creating long-term environmental concerns. Scaling recycling operations requires automated sorting technologies, with spectroscopy and machine learning offering promising solutions. In this study, a six-class convolutional neural network (CNN) was developed for plastic identification using vibrational spectroscopies. Raman Scattering (RS) spectra collected from recycling samples enabled accurate chemical differentiation while assessing the influence of visible features such as color. A CNN trained on RS data achieved 100% classification accuracy. To strengthen field applicability, Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy was incorporated, achieving 95% accuracy with a similar CNN model. These findings demonstrate the potential of integrating spectroscopy with deep learning for reliable plastic classification, advancing development of scalable, field-ready recycling technologies.

Garcia Tovar, Maria P.↗
DOE OSTI2017

Identification and Analysis of Partial Shading Breakdown Sites in CuIn x Ga (1-x) Se 2 Modules

In this paper, CuIn x Ga (1-x) (CIGS) mini-modules are stressed under reverse bias, resembling partial shading conditions, to predict and characterize where failures occur. Partial shading can cause permanent damage in the form of 'wormlike' defects on thin-film modules due to thermal runaway. This results in module-scale power losses. We have used dark lock-in thermography (DLIT) to spatially observe localized heating when reverse-bias breakdown occurs on various CIGS mini-modules. For better understanding of how and where these defects originated and propagated, we have developed techniques where the current is limited during reverse-bias stressing. This allows for DLIT-based detection and detailed studying of the region where breakdown is initiated before thermal runaway leads to permanent damage. Statistics of breakdown sites using current-limited conditions has allowed for reasonable identification of the as-grown defects where permanent breakdown will likely originate. Scanning electron microscope results and wormlike defect analysis show that breakdown originates in defects such as small pits, craters, or cracks in the CIGS layer, and the wormlike defects propagate near the top CIGS interface.

14 SOLAR ENERGY↗