Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sample identifier”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Paired Neural Network for Matching Experimental and Predicted Infrared Spectra

Here, we present a novel machine learning (ML)-based scoring technique for determining the similarity between experimental and predicted infrared (IR) spectra for identification purposes. IR spectroscopy is a powerful technique used to identify the molecular structure and composition of a sample by measuring the unique vibrational frequency pattern of the molecule’s functional groups. Molecular identifications are often made by comparing experimental and reference spectra. However, the limited number of reference spectra available in spectral libraries can confound the identification process. Alternative identification procedures rely on in silico techniques to simulate spectra for a wide range of molecules. However, scoring spectral similarity between an experimental query and computationally predicted reference remains a significant challenge. Our proposed ML-based scoring technique overcomes these barriers by accurately and efficiently determining spectral similarity.

Neural Network↗
DOE OSTI2024

High-Resolution Tandem Mass Spectrometry-Based Analysis of Model Lignin–Iron Complexes: Novel Pipeline and Complex Structures

Understanding the chemical nature of soil organic carbon (SOC) with great potential to bind iron (Fe) minerals is critical for predicting the stability of SOC. Organic ligands of Fe are among the top candidates for SOCs able to strongly sorb on Fe minerals, but most of them are still molecularly uncharacterized. To shed insights into the chemical nature of organic ligands in soil and their fate, this study developed a protocol for identifying organic ligands using ultrahigh-performance liquid chromatography-high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) and metabolomic tools. The protocol was used for investigating the Fe complexes formed by model compounds of lignin-derived organic ligands, namely, caffeic acid (CA), p-coumaric acid (CMA), vanillin (VNL), and cinnamic acid (CNA). Isotopologue analysis of 54/56 Fe was used to screen out the potential UHPLC-HRMS (m/z) features for complexes formed between organic ligands and Fe, with multiple features captured for CA, CMA, VNL, and CNA when 35/37 Cl isotopologue analysis was used as supplementary evidence for the complexes with Cl. MS/MS spectra, fragment analysis, and structure prediction with SIRIUS were used to annotate the structures of mono/bidentate mono/biligand complexes. The analysis determined the structures of monodentate and bidentate complexes of FeL x Cl y (L: organic ligand, x = 1–4, y = 0–3) formed by model compounds. The protocol developed in this study can be used to identify unknown organic ligands occurring in complex environmental samples and shed light on the molecular-level processes governing the stability of the SOC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Toward nanoscale molecular mass spectrometry imaging via physically constrained machine learning on co-registered multimodal data

Mass spectrometry imaging (MSI) plays a pivotal role in investigating the chemical nature of complex systems that underly our understanding in biology and medicine. Multiple fields of life science such as proteomics, lipidomics and metabolomics benefit from the ability to simultaneously identify molecules and pinpoint their distribution across a sample. However, achieving the necessary submicron spatial resolution to distinguish chemical differences between individual cells and generating intact molecular spectra is still a challenge with any single imaging approach. Here, we developed an approach that combines two MSI techniques, matrix-assisted laser desorption/ionization (MALDI) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The known relationships between the two MSI channels of information are enforced via a physically constrained machine-learning approach and directly incorporated in the data processing. We demonstrate the robustness of this method by generating intact molecular MALDI-type spectra and chemical maps at ToF-SIMS resolution when imaging mouse brain thin tissue sections. This approach can be readily adopted for other types of bioimaging where physical relationships between methods have to be considered to boost the confidence in the reconstruction product.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Trap characterization of high-growth-rate laser-assisted MOCVD GaN

A detailed study comparing defect incorporation between laser-assisted metal-organic chemical vapor deposition (MOCVD)-grown GaN and conventional low- and high-growth-rate MOCVD GaN was conducted. Using deep-level transient and optical spectroscopy, traps throughout the bandgap were characterized where traps were found at EC-0.25 eV, EC-0.57 eV, EC-0.72 eV, EC-0.9 eV, EC-1.35 eV, EC-2.6 eV, and EC-3.28 eV in all three samples. This indicates no new traps were observed in the laser-assisted MOCVD GaN sample. Overall, the trap concentrations in the laser-assisted MOCVD sample were ∼2× higher than the optimal low-growth-rate sample, but this is primarily due to the increase in gallium vacancy EC-2.6 eV and carbon-related EC-3.28 eV trap concentrations. The EC-0.9 eV trap concentration was ∼2× higher in the laser-assisted sample, so proton irradiation experiments were conducted to identify the physical source of this level. The results indicated this was a native point defect likely related to gallium interstitials. Overall, this study shows that the laser-assisted MOCVD growth method is promising for future thick, high-quality GaN epilayers after further growth optimizations.

Physics↗
DOE OSTI2022

Multiarea Distribution System State Estimation via Distributed Tensor Completion

Here, this paper proposes a model-free distribution system state estimation method based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A three-way tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A distributed closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. The convergence properties of the distributed algorithm and the sufficient conditions on the number of samples for each smaller network that guarantee the identifiability of the factors of the state tensor are presented. To demonstrate the efficacy of the proposed algorithm and to check the identifiability conditions, numerical simulations are carried out using the IEEE 123-bus system and a large-scale real utility feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Nondestructive Evaluation of Stress Corrosion Cracking in a Welded Steel Plate Using Guided Ultrasonic Waves

Stress corrosion cracking (SCC) had occurred in early-generation high-level nuclear waste tanks constructed by welding carbon steel. This paper describes an ultrasonic inspection system and its fundamental ability to detect and quantify the length of SCC on thick welded steel plates. The finite element method (FEM) was applied to simulate the welding process to estimate the welding residual stress field. Growth of stress corrosion cracks is driven by crack stress intensities exceeding the subcritical cracking threshold intensity. The subject plate was experimentally inspected with ultrasonic nondestructive evaluation (NDE) techniques to characterize the extent of SCC. The NDE system uses a piezoelectric transducer to generate guided waves in the thick steel plate, and a scanning laser Doppler vibrometer (SLDV) to measure multidimensional time–space wavefield data over a user-defined scanning area in the plate surface. The measured wavefield data can show wave interactions in a localized area in the plate due to the presence of the discontinuities of the SCC. To generate an inspection image that can precisely show the crack’s location and/or the dimension, the wavefield data are further processed to generate inspection image that maps the entire sample plate so the crack can be clearly identified in the plate while its length can be readily estimated. In conclusion, the ultrasonic test results for crack length agree well with the visually estimated length and are close to that predicted by the FEM for cracks in the weld residual stress field.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Classification of Semiconductors Using Photoluminescence Spectroscopy and Machine Learning

Photoluminescence spectroscopy is a nondestructive optical method that is widely used to characterize semiconductors. In the photoluminescence process, a substance absorbs photons and emits light with longer wavelengths via electronic transitions. This paper discusses a method for identifying substances from their photoluminescence spectra using machine learning, a technique that is efficient in making classifications. Neural networks were constructed by taking simulated photoluminescence spectra as the input and the identity of the substance as the output. Here, six different semiconductors were chosen as categories: gallium oxide (Ga 2 O 3 ), zinc oxide (ZnO), gallium nitride (GaN), cadmium sulfide (CdS), tungsten disulfide (WS 2 ), and cesium lead bromide (CsPbBr 3 ). The developed algorithm has a high accuracy (>90%) for assigning a substance to one of these six categories from its photoluminescence spectrum and correctly identified a mixed Ga 2 O 3 /ZnO sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Review of Landscaping Equipment Vibration Risk Exposure, LLNL Site 200 (Various Locations), Whole Body Vibration Seated and Standing Mowers

WBV (Whole-Body Vibration) for operators of seated and standing lawn mowers was conducted during landscape activities from April 2019 through August 2019 at various locations around LLNL Site 200. Mowing is generally performed by each landscaper for 2-3 days every other week with a maximum duration of 3-5 hours each day. On mowing days, other tasks are performed for the remainder of the day that do not expose the worker to WBV such as irrigation, blowing, or sweeping. The mowing terrain at LLNL is variable with typical reported conditions such as gopher holes, exposed tree roots, quick turns, normal and high growth, weeds, and mushy/wet ground that can result in jolts to the mower operator. The Larson Davis HVM200 seat pad with tri-axial accelerometer was used for monitoring workers. For the seated mowers, the HVM200 seat pad with tri-axial accelerometer was placed on the seat between the user and seat pan of the mower. For standing mowers, the seat pad with tri-axial accelerometer was wrapped with Dycem (for seat pad protection) and placed directly on top of the mower deck and underneath the end-user’s right foot. Monitoring for WBV was conducted while operators used different types, makes, and models of mowers. A total of sixteen samples were collected from the operators of seated mower and 6 samples were collected from operators of standing mower. This initial data sampling was part of a discovery phase to identify if WBV exposure met the 2016 ACGIH TLVs (Threshold Limit Values). This initial data identified that workers operating the mowers do not exceed either the TLV or Action Level (AL) for Weighted Acceleration Levels (A(8)) but typically exceed the Vibration Dose Value (VDV) lower boundary for the standing mowers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evaluation of Naturally Occurring Be-7 Activity on LANL Stack Filter Clumps

Los Alamos National Laboratory (LANL) is responsible for providing solutions to challenging issues through multidisciplinary science, engineering, and technology that impact national security. As part of the Radioactive Air Emissions Management (RAEM) Team, it is our responsibility to ensure LANL operates within the requirements of the Code of Federal Regulations 40 CFR 61, Subpart H, National Emission Standards for Emissions of Radionuclides Other Than Radon From Department of Energy Facilities (Rad-NESHAP). The standard states, “Emissions of radionuclides to the ambient air from Department of Energy facilities shall not exceed those amounts that would cause any member of the public to receive in any year an effective dose equivalent of 10 mrem/yr” (EPA, 2002) During a routine assessment of LANL’s Rad-NESHAP compliance program, an opportunity for improvement was identified that addresses the evaluation of routine stack samples which potentially have naturally occurring radioactive materials (NORM) on the filter media. In the past and based on professional judgment, detections of NORM such as K-40 and Be-7 typically were rejected from the analytical results. The assessment finding suggested developing a technical criterion to ensure that such rejections were justified, comparing actual measured values with anticipated NORM concentrations for various stacks located at LANL. The significance of accepting or rejecting samples as “true” or “NORM” and its impact on the RAEM’s mission and compliance to the regulations is explained later in the document. Additionally, this document will describe the process and calculations for how such results are to be accepted as actual samples “true positive” or rejected as NORM.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Compositing and Characterization of SE Quadrant Waste Exemplars

This report outlines the experimental investigation and characterization of transport properties in Hanford SE quadrant High-Level Waste (HLW). The goal of the study was to establish baseline behaviors of bulk composite rheology and settling characteristics to facilitate waste treatment process design for the Waste Treatment and Immobilization Plant (WTP) and avoid waste conditions and properties favorable to bubble cascade gas release events. The study focused on two major objectives: 1) identifying, obtaining, and preparing relevant Hanford tank waste samples for evaluation and 2) quantifying the “as-received” rheology and transport properties of the samples. Twenty-three centrifuged core segments originating from tanks AN-101, AN-106, and AW-105 were selected based on compositional relevance to SE quadrant PUREX cladding waste. These materials were composited into five waste composites enriched with target analytes: aluminum (Al), iron (Fe), phosphate (PO 4 ), uranium (U), and zirconium (Zr). Physical property and transport testing examined particle size distributions, bulk densities, settling behaviors, rheological properties, shear strengths, and just-suspended mixing speeds (NJS). Testing revealed two distinct composite classifications based on rheological characteristics: non-Newtonian composites (Fe and PO 4 ) and Newtonian composites (Al, U, and Zr). The Fe and PO 4 composites exhibited slow settling rates and reduced mobilization proclivity, attributable to strong particle-particle interactions and the formation of yield structures within non-Newtonian slurries. In contrast, the Al, U, and Zr composites displayed rapid settling and dense compaction behaviors, indicative of minimal structuring and interactions. Shear strengths for all composites were generally low relative to prior studies of SE quadrant waste, with only the U composite showing elevated strength approaching values reported in previous literature. Repeat shear strength measurements revealed contributions from dense granular material in the U composite and stronger cohesive properties in the Al composite. Settling data highlighted hindered settling behavior, with rates falling more than one order of magnitude below estimates based on Stokes’ law and rate decreasing as composite UDS content increased. NJS testing demonstrated different mobilization behaviors between cohesive and granular composites. The Fe composite required the highest mixing rate for resuspension, while the Al composite was the easiest to resuspend. Comparison of measured NJS against predictions made using the Zwietering correlation suggests non-Newtonian behavior alters resuspension mechanics, rendering non-Newtonian systems more stable against resuspension lift forces relative to their granular counterparts.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Extremely Metal-poor Galaxies in DESI DR1: Connections to Galaxies in the Early Universe

Extremely metal-poor galaxies (XMPGs), defined as having metallicities below 10% of the solar value, are considered possible local analogs to primordial systems and offer a unique window into early galaxy evolution. This study presents a large-scale search for XMPGs using data from the Dark Energy Spectroscopic Instrument Data Release 1, systematically evaluating their resemblance to high-redshift galaxies. From a parent sample of more than 14 million galaxies, we identify 662 (556 new) confirmed XMPGs and 763 (666 new) high-quality candidates via the direct T$_{e}$ method. Our results reveal that XMPGs follow a distinct star-forming main sequence (SFMS) that is elevated and shallower than that of the comparing star-forming galaxies. Notably, at higher stellar masses (M$_{⋆}$ > 10$^{7.5}$M$_{⊙}$), the XMPG SFMS converges with the sequence observed in high-redshift galaxies by the James Webb Space Telescope, indicating that mature XMPGs sustain star formation rates comparable to their primordial counterparts. Furthermore, XMPGs consistently deviate below the local fundamental metallicity relation, mirroring high-redshift galaxy behavior. These findings demonstrate that XMPGs not only exhibit low metallicities but also preserve scaling relations characteristic of the early Universe, confirming their potential value as local laboratories for studying early galaxy formation processes.

Sui, Jipeng [Beijing Observ.; Beijing, GUCAS] (ORC↗
DOE OSTI2022

Variable Active Galactic Nuclei in the Galaxy Evolution Explorer Time Domain Survey

We searched the northern hemisphere fields of the Galaxy Evolution Explorer Time Domain Survey for galaxies with UV variability indicative of active galactic nuclei (AGNs). We identified 48 high-probability candidate AGNs from a parent sample of 1819 galaxies in the NASA Sloan Atlas catalog. We further characterized these systems using optical spectroscopic diagnostics, Wide-field Infrared Survey Explorer IR color selection criteria, and spectral energy distribution modeling. Of the 48 candidates, eight were identified as AGNs from optical emission lines, two were identified by their IR colors, and 28 were identified through spectral energy decomposition. Observational biases of each selection method are discussed in connecting these AGN subsamples to another. By selecting AGNs based on UV variability, we also identified six low-mass AGN candidates, all of which would have been missed by spectroscopic selection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Role of Intra-Domain Heterogeneity on Ion and Polymer Dynamics in Block Polymer Electrolytes: An Approach for Spatially Resolving Dynamics and Ion Transport

The design of safe and high-performance, nanostructured, block polymer (BP) electrolytes for lithium-ion batteries requires a thorough understanding of the key parameters that govern local structure and dynamics. Yet, the interfaces between microphase separated domains can introduce complexities in this local behavior that can be challenging to quantify. Herein, the local polymer, cation (Li + ), and anion dynamics were described in salt-doped polystyrene block poly(oligo-oxyethylene methyl ether methacrylate) (PS-b-POEM) through a quantitative framework that considered the effects of polymer architecture, segmental mixing, chain stretching, and confinement on polymer mobility and ion transport. This framework was validated through nuclear magnetic resonance (NMR) spectroscopy measurements on solid (dry) polymer electrolyte samples. Notably, a mobility transition temperature (T mobility ) was identified through NMR spectroscopy that captured the local dynamics more accurately than the thermal glass transition temperature. Additionally, the approach quantitatively described the mobility gradient across a domain when segmental mixing effects were combined with chain stretching and confinement information, especially at higher segregation strengths – facilitating the assessment of local ion diffusion and conductivity. As a result, spatially averaged local ion diffusion predictions quantitatively matched NMR-measured ion diffusivities in the BP samples, while spatially summed ionic conductivity predictions across a domain qualitatively captured trends in the measured ionic conductivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Validation of Scale-Derived Ages in Wild Juvenile and Adult Steelhead Using Parental-Based Tagging

Abstract Accurate age information is a critical component in fisheries monitoring, management, and research. The ability to assign accurate ages to fish by using nonlethal structures is vital in calculating cohort productivity for fish species with low abundances and variable life histories. A common nonlethal method to assign ages is by interpretation of patterns in scales. Validation of ages is not easily obtained for free-ranging fishes; however, the development of genetic “tags” has expanded age validation opportunities. In this study, we used parental-based genetic tagging to validate ages determined from scales collected from juvenile and adult steelhead Oncorhynchus mykiss in two streams within the Snake River basin. Juvenile scale ages were in agreement with 93% of the known ages. Adult scale ages were in agreement with 89% of the known ages. Although overall bias in juvenile ages was very low, we saw a slight positive bias in younger fish (young of the year and age 1) and a small negative bias in older juveniles (ages 2–4). A small negative bias in ages of adults was a consequence of errors in freshwater age. The errors observed did not significantly bias age compositions because the 90% confidence intervals about the age proportions based on scales contained the known proportions; therefore, scale analysis is an acceptable method for assigning ages to Snake River steelhead. We discuss the value of validated known-age scales as a reference collection, and as an illustrative use, we constructed a circulus count guide to aid technicians in identifying missing annuli and distinguishing true from false annuli. To demonstrate the use of the circulus guidelines, we reanalyzed samples with age discrepancies, applying the circulus count data and the known age to identify mistakes.

Reinhardt, Leslie↗
DOE OSTI2020

Forensic species identification of elasmobranchs landed in Costa Rican artisanal fisheries

Elasmobranchs represent one of the most imperiled taxa, yet few nations have developed catch limits and no international or bilateral catch limits exist. One barrier to establishing catch limits is a lack of accurate species-specific extraction rates due to many species looking similar, distinguishing characteristics (fins and head) being removed, or grouping of all elasmobranchs together in fisheries data. To better understand the species-specific impacts fisheries are having on elasmobranchs we used forensic genetic techniques to identify the types and quantities of shark species landed in Costa Rican artisanal small-scale and mid-scale fisheries. We collected elasmobranch tissue samples from fishermen in three locations along Costa Rica’s Pacific Coast: Coyote, Bejuco, and Ojochal, from April 2013 to September 2014. We used DNA barcoding techniques, utilizing a 1044 base pair region of the NADH dehydrogenase subunit 2 gene, to identify to species 275 of the 416 samples collected. Within these fisheries, seven species of shark and one ray were identified, with the scalloped hammerhead shark (Sphyrna lewini) accounting for ~750-80% of all sharks landed. Observed total lengths (TL) for the scalloped hammerhead shark (10.9–99 cm) in these fisheries suggests the sharks sampled were all either juveniles or neonates. Based on these data it is likely that the areas from which these samples were collected represent nursery grounds for the scalloped hammerhead shark. The quantity of young scalloped hammerhead sharks removed from these areas, and ones similar to them, by these artisanal fisheries could be of great importance when determining future conservation measures for this species. We conclude our findings also indicate that sharks caught in these artisanal fisheries do not appear to represent those sold in markets around San Jose.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Case Study in Assessing a Potential Severity Framework for Incidents from a Decadal Sample

In this study, the primary objective of this case study is to determine the applicability and feasibility of a framework that leverages occupational incident details to prospectively identify “potential Serious Injury or Fatality” (pSIF) cases. This study comprehensively reviewed a random sample of 1,081 injury and illness cases across 21 generalized incident types spanning over a decade at Lawrence Livermore National Laboratory (LLNL), a U.S. Department of Energy research and development facility with more than 9,000 employees. The review applied a general framework that classified each case on information suitability, potential severity, and future incident mitigation. The findings from the study indicate that 86.6% of the cases had sufficient information to make a high-confidence determination on potential severity, underscoring the feasibility of applying this general framework. Additionally, cases with a higher pSIF score had, on average, a higher level of institutional response. Implementing a simplified methodology for incident classification that emphasizes incidents that pose high potential severity, regardless of incident type, can help LLNL prioritize resources and tailor responses to such incidents using a graded approach. LLNL has recognized the value of this capability and is integrating the framework into their injury and illness process in the 2024 calendar year.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗