Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Process Sample Analysis”

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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

The Role of (Delta)C-13 in the Search for Reduced Organics on the Surface of Mars

The capabilities of the Sample Analysis at Mars (SAM) instrument suite on the Mars Science Laboratory (MSL) to detect trace amounts of organic carbon compounds are unprecedented, and MSL may be the first mission to reveal the presence of organic carbon on Mars. The search for reduced organic carbon on Mars is inextricably tied to: a) the preservation potential of the environment from which we take a solid sample, and b) the evolved gas analysis (EGA) techniques used by SAM to release volatiles from this solid sample. Several prospective targets have been identified for sample analysis at Gale Crater. Stratigraphic sequences of phyllosilicates and sulfates at Gale are thought to represent a period of global climate transition from a moderate pH lacustrine environment to an evaporitic environment, both of which could sequester organic carbon (Thomson et al. 2011). The sediment mound in Gale Crater contains a range of lithologies suggesting changes in redox conditions, and evidence of both lacustrine and fluvial depositional processes, which may have transported organic carbon from the layer in which it formed and resulted in its preservation elsewhere within the crater (Anderson and Bell, 2010). Inverted channel fills suggest erosion resistant material that could serve to preserve organics originally deposited in a low energy aqueous environment. The lithology sampled will affect not only the preservation of organics, but also our ability to detect organics during our evolved gas analysis, based on the sample matrix. For example, reduced organics may be trapped in the mineral structure, and thermal evolution of these organics will occur during thermal decomposition of the host mineral. If organics are occluded in minerals that have very high thermal decomposition temperatures, they may be, in effect, "too well preserved," and difficult to detect during EGA. Alternatively, the possible presence of perchlorate, or other strong oxidants in surface regolith, may result in destruction of structural information identifying organic molecules before reaching the QMS on SAM via oxidation to C02 during heating. If this is the case, the stable carbon isotopic composition (delta 13C) of the C02 evolved and measured by the Tunable Laser Spectrometer (TLS) on SAM may help identify the presence of organics. On Earth, biological activity can cause large fractionations of 13C/12C, which can preserved in sedimentary deposits and distinguish the organic products of biotic processes from inorganic atmospheric and geological reservoirs. It is plausible that similar fractionations could occur on Mars and be preserved in reduced organic matter in sediments. Bulk delta 13C measurements alone may not reveal a signature of trace organic carbon that may be present along with inorganic carbon. If both organic and inorganic carbon compounds are present, it may be possible to detect the organic carbon by comparing the 013C of pyrolysis and combustion experiments. The TLS on SAM is capable of obtaining high precision measurements of delta13C from C02 evolved during pyrolysis and combustion of solid regolith samples. Because carbonates are expected to be present at abundances of 0.1-1 % in Martian soil, and organics in the ppb range (Webster and Mahaffy, 2011), analog samples must represent this mix of reduced organic carbon and carbonate. The work presented here will examine the use of delta13C of C02 produced during combustion of bulk Mars analog samples as a proxy for detection of reduced organic carbon.

Stern, J. C.↗
DOE OSTI2015

Magnetic Properties of Electroformed Ni and Ni-Fe for Micromagnetic MEMS Applications

This paper reports a new technique which is based on electroforming process for high permeability Ni and Ni-Fe alloy. The magnetic properties of Ni and Ni-Fe alloy are investigated as a function of plating current density via scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), and vibrating sample magnetometer (VSM). Concentration-dependent kinetics is used to formulate the deposition rate and also the same is verified by using finite element analysis tool COMSOL Multiphysics. Several experiments are performed to derive the relation between electroplating parameters and magnetic properties. The process conditions are optimized to develop high permeability (∼16000) Ni-Fe alloy (85.71–14.29 %). The higher current density shows a monotonically increasing behavior of relative permeability (μ{sub r}). In addition, the B-H curves indicate that the saturation magnetization (B{sub sat}) increases and coercivity decreases with increasing plating current density. Our experimental data confirms that the higher current density increase the softness of Ni. The observed properties of Ni and Ni-Fe based on experimental results can be used to study the magnetic behavior of micromagnetic sensors and large force actuators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Conversion kinetics of container glass batch melting

Abstract Understanding the batch‐to‐glass conversion process is fundamental to optimizing the performance of glass‐melting furnaces and ensuring that furnace modeling can correctly predict the observed outcome when batch materials or furnace conditions change. To investigate the kinetics of silica dissolution, gas evolution, and primary foam formation and collapse, we performed X‐ray diffraction, thermal gravimetry, feed expansion tests, and evolved gas analysis of batch samples heated at several constant heating rates. We found that gas evolving reactions, foaming, and silica dissolution depend on the thermal history of the batch in a similar manner: the kinetic parameters of each process were linear functions of the square root of the heating rate. This kinetic similarity reflects the stronger‐than‐expected interdependence of these processes. On the basis of our results, we suggest that changes in furnace operating conditions, such as firing or boosting, influence the melting rate less than what one would expect without consideration of batch conversion kinetics.

Ueda, Nanako↗
DOE OSTI2018

Application of X-ray computed tomography for the characterization of graphite morphology in compact-graphite iron

Highlights: • X-ray Tomography is a powerful technique for graphite morphology characterization. • 3D characterization reveals true nodularity and spatial connectivity of graphite. • Tri-modal distribution of SG suggests a multi-stage graphite nucleation process. - Abstract: In the present study, high-energy X-ray tomography technique was used to characterize the graphite morphology of compact graphite iron. The size, shape, spatial connectivity and structure of different graphite morphologies were examined in 3D using computer-aided image analysis. In addition, nodularity analysis was performed in 3D and the results are compared to the traditional 2D technique. It is found that the variation of nodularity within 2 × 2 × 1.2 mm{sup 3} of the sample can be as high as 20 (%) from 2D analysis and the averaged nodularity (2D) is higher than that from 3D analysis. The size distribution of spheroidal graphite shows a tri-modal distribution, which suggests a multi-step nucleation process during solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Measuring Muon Antineutrino Charged-Current Interactions Without Mesons in the Final State, in the NOvA Near Detector

NOvA is a long-baseline neutrino experiment based at Fermilab in the US, with the primary aim of measuring neutrino and antineutrino oscillations. This will enhance our understanding of electroweak interactions by measuring the neutrino mixing angles, CP-violating phase and neutrino mass ordering. To measure these oscillations, we first need to have a deep understanding of how neutrinos and antineutrinos interact with matter. Antineutrino interaction cross sections are, at present, particularly poorly constrained, and processes such as meson exchange currents are not well understood in the antineutrino sector. This analysis will develop a cross-section measurement of muon antineutrino interactions without mesons (e.g. pions or kaons) in the final state, in the NOvA near detector. A high-statistics, high-purity sample is obtained through a cut-based selection process implementing machine learning techniques. The sample is dominated by quasi-elastic and meson exchange current interactions which are sensitive to nuclear effects such as Final-State Interactions. The cross section will be extracted as a function of the incoming neutrino energy and the kinematics of the outgoing particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1988

Symbolic derivation of material property matrices in finite element analysis

The principles and operation of MMAX, a symbolic-computation program which automates the process of generating property matrices for structural materials, are briefly described and illustrated with sample analyses of a rubberlike material and an elastoplastic material. MMAX is written in LISP under the symbolic finite-element generator FINGER and the general symbolic manipulator MACSYMA; it first derives the formulas required by mathematical manipulation, and then translates the formulas into FORTRAN code, adapted to the particular type of machine to be used for the numerical calculations. This approach is shown to combine efficiently the advantages of symbolic and numerical computation for engineering applications.

Tan, H. Q.↗
DOE OSTI2016

Sludge batch 9 (SB9) acceptance evaluation. Radionuclide concentrations in tank 51 SB9 qualification sample prepared at SRNL

Presented in this report are radionuclide concentrations required as part of the program of qualifying Sludge Batch 9 (SB9) for processing in the Defense Waste Processing Facility (DWPF). The SB9 material is currently in Tank 51 and has been washed and prepared for transfer to Tank 40. The acceptance evaluation needs to be completed prior to the transfer of the material in Tank 51 to Tank 40. The sludge slurry in Tank 40 has already been qualified for DWPF processing and is currently being processed as Sludge Batch 8 (SB8). The radionuclide concentrations were measured or estimated in the Tank 51 SB9 Washed Qualification Sample prepared at Savannah River National Laboratory (SRNL). This sample was prepared from a three liter sample of Tank 51 sludge slurry (HTF-51-15-81) taken on July 23, 2015. The sample was delivered to SRNL where it was initially characterized in the Shielded Cells. Under the direction of Savannah River Remediation (SRR) it was then adjusted per the Tank Farm washing strategy as of October 20, 2015. This final slurry now has a composition expected to be similar to that of the slurry in Tank 51 after final preparations have been made for transfer of that slurry to Tank 40.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Managing Sn-Supply to Tune Surface Characteristics of Vapor-Diffusion Coating of Nb₃Sn

Nb₃Sn promises better RF performance (Q and E_{acc}) than niobium at any given temperature because of superior superconducting properties. Nb₃Sn-coated SRF cavities are now produced routinely by growing a few microns thick Nb₃Sn films inside Nb cavities via the tin vapor diffusion technique. Sn evaporation and consumption during the growth process notably affect the quality of the coating. Aiming at favorable surface characteristics that could enhance the RF performance, many coatings were produced by varying Sn sources and temperature profiles. Coupon samples were examined using different material characterization techniques, and a selected few sets of coating parameters were used to coat 1.3 GHz single-cell cavities for RF testing. The Sn supply’s careful tuning is essential to manage the microstructure, roughness, and overall surface characteristics of the coating. We summarize the material analysis of witness samples and discuss the performance of several Nb₃Sn-coated single-cell cavities linked to Sn-source characteristics and observed Sn consumption during the film growth process.

Pudasaini, U.↗
DOE OSTI2021

Managing Sn-supply to tune surface characteristics of vapor-diffusion coating of Nb3Sn

Nb₃Sn promises better RF performance (Q and E_{acc}) than niobium at any given temperature because of superior superconducting properties. Nb₃Sn-coated SRF cavities are now produced routinely by growing a few microns thick Nb₃Sn films inside Nb cavities via the tin vapor diffusion technique. Sn evaporation and consumption during the growth process notably affect the quality of the coating. Aiming at favorable surface characteristics that could enhance the RF performance, many coatings were produced by varying Sn sources and temperature profiles. Coupon samples were examined using different material characterization techniques, and a selected few sets of coating parameters were used to coat 1.3 GHz single-cell cavities for RF testing. The Sn supply’s careful tuning is essential to manage the microstructure, roughness, and overall surface characteristics of the coating. We summarize the material analysis of witness samples and discuss the performance of several Nb₃Sn-coated single-cell cavities linked to Sn-source characteristics and observed Sn consumption during the film growth process.

Pudasaini, U.↗
NASA NTRS1987

The case for planetary sample return missions. I - Origin of the solar system

The scientific aims and proposed scenarios of sample-return missions (SRMs) to Mars, Venus, comets, and asteroids are reviewed. SRMs are currently being evaluated as natural follow-ons to the NASA remote-sensing orbiter missions of the 1990s. The technological advantages of ground laboratory analysis of returned samples are discussed; and it is argued that SRMs to large evolved bodies can provide a record of (1) the composition of the solar system at different heliocentric distances and (2) the nature of the processes that led to the accretion of small objects (preserved as comets and asteroids) into large planetary bodies. Also considered are NASA research and analysis programs needed to support studies of solar-system origin. It is recommended that planning of SRMs be begun immediately, although they may not be feasible before the year 2000.

Drake, Michael J.↗
DOE OSTI2014

Microstructure and thermomechanical properties relationship of segmented thermoplastic polyurethane (TPU)

Thermoplastic polyurethanes (TPU) are important polymeric materials for seals. In competition with Acrylonitrile butadiene rubbers (NBR), TPU exhibits higher strength and a considerable better abrasion resistance. The advantage of NBR over TPU is a smaller compression set but however TPU excels in its much shorter processing cycle times. Generally a TPU is a block copolymer composed of hard and soft segments, which plays an important role in determining the material properties. TPU can be processed either to ready moulded parts or can be incorporated by multi component moulding, in both cases it shows decent mechanical properties. In the present work, the relationship between melt-process induced TPU morphology and resultant thermo mechanical properties were examined and determined by means of quasi-static tensile test, creep experiment, tension test and dynamical mechanical analysis (DMA). Scanning electron beam microscope (SEM) and differential scanning calorimeter (DSC) were used to study the morphology of the samples. A significant mathematical description of the stress-strain behaviour of TPU was found using a 3 term approach. Moreover it became evident that processing conditions such as processing temperature have crucial influence on morphology as well as short and long-term performance. To be more precise, samples processed at higher temperatures showed a lack of large hard segment agglomerates, a smaller strength for strains up to 250% and higher creep compliance.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Structural and photocatalytic examination of CoMoO4 nanopowders synthesized by GNP method

Highlights: • Synthesis of CoMoO{sub 4} nanoparticles in a simple, quick, and inexpensive way, by using a glycine nitrate procedure (GNP). • Two different crystal structures of CoMoO{sub 4}, α and β, was confirmed by X-ray diffraction. • BET analysis confirmed significant specific surface areas of CoMoO{sub 4} nanopowder. • CoMoO{sub 4} nanopowders can be promising solutions in photocatalytic processes toward green chemistry and sustainable development. - Abstract: The synthesis route by solution combustion, a glycine nitrate procedure (GNP) of CoMoO{sub 4} nanopowders by a glycine as a fuel and as a complexant was examined concerning the photocatalytic aspects and powder characteristics. The synthesized samples were investigated by differential thermal analysis (DTA), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), Ultraviolet-Visible (UV/Vis) spectroscopy and nitrogen adsorption method. In this work, we presented a simple and effective method for controlling the composition and morphology of CoMoO{sub 4}. A single-phase α and β crystalline form of CoMoO{sub 4} compound was confirmed by X-ray diffraction (XRD). The photocatalytic activity of CoMoO{sub 4} nanopowders was estimated by the photocatalytic degradation of crystal violet in aqueous solution. In addition, the obtained specific CoMoO{sub 4} nanopowder demonstrated acceptable specific surface area, which can be of particular importance for the photocatalytic processes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

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↗
DOE OSTI2026

Data and scripts associated with “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments”

This data package is associated with the publication “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments” published in Scientific Reports (Garayburu-Caruso et al., 2026). The package contains processed data products and scripts used to quantify how drying and re-inundation of riverbed sediments influence dissolved organic matter (DOM) thermodynamic properties and their relationship with sediment oxygen (O₂) consumption across 33 stream sites in the contiguous United States. The data package contains DOM thermodynamic metrics (e.g., Gibbs free energy of carbon oxidation and thermodynamic efficiency), and O₂ consumption along with watershed-scale climate and land-cover metrics used as explanatory variables in the analyses. Underlying unprocessed and processed ultrahigh-resolution mass spectrometry data, oxygen consumption rates from laboratory moisture-manipulation experiments, within-sample environmental properties, sediment moisture content and contextual field measurements are archived separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2428003 (Laan et al., 2024) and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689 (Forbes et al.,2023). A preliminary version of this data package was published in February 2026 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include the finalized data and additional metadata (readme, data dictionary, and file level metadata). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. At the top level, the data package is organized into five main folders: (1) Data, (2)Figures, (3) Map, (4) GAM_Reulsts, and (5) src. The Data folder contains analysis-ready tabular files with oxygen consumption rates, DOM thermodynamic properties by site and treatment, site-level environmental variables, watershed-scale metrics, and other derived variables referenced in the manuscript. The Figures folder contains static image files associated with the main text and supplemental figures, while the Map folder includes spatial data and map-layer files used to create the sampling-location map. The GAM results folder contains the results for each of the general additive model (GAM).The src folder contains R scripts used to perform data processing, statistical analyses (including clustering, generalized additive models, and threshold analysis), and figure generation. This data package is associated with a GitHub repository found at https://github.com/WHONDRS-Hub/ECA_DOM_Thermodynamics.

Dissolved organic matter↗
DOE OSTI2018

Stable-carbon isotope ratios for sourcing the nerve-agent precursor methylphosphonic dichloride and its products

The ability to connect a chemical threat agent to a specific batch of a synthetic precursor can provide a fingerprint to contribute to effective forensic investigations. Stable isotope analysis can leverage intrinsic, natural isotopic variability within the molecules of a threat agent to unlock embedded chemical fingerprints in the material. Methylphosphonic dichloride (DC) is a chemical precursor to the nerve agent sarin. It is converted to methylphosphonic difluoride (DF) as part of the sarin synthesis process. We used a suite of commercially available DC stocks to both evaluate the potential for δ13C analysis to be used as a fingerprinting tool in sarin-related investigations and to develop sample preparation techniques (using chemical hydrolysis) that can simplify isotopic analysis of DC and its synthetic products. We demonstrate that natural isotopic variability in DC results in at least three distinct, isotope-resolved clusters within the thirteen stocks we analyzed. Isotopic variability in the carbon feedstock (i.e., methanol) used for DC synthesis is likely inherited by the DC samples we measured. We demonstrate that the hydrolysis of DC and DF to methylphosphonic acid (MPA) can be used as a preparative step for isotopic analysis because the reaction does not impart a measureable isotopic fractionation. MPA is more chemically stable, less toxic, and easier to handle than DC or DF. Further, the hydrolysis method we demonstrated can be applied to a suite of other precursors or to sarin itself, thereby providing a potentially valuable forensic tool.

Moran, James J.↗
NASA NTRS1985

Technical support for creating an artificial intelligence system for feature extraction and experimental design

Techniques for classifying objects into groups or clases go under many different names including, most commonly, cluster analysis. Mathematically, the general problem is to find a best mapping of objects into an index set consisting of class identifiers. When an a priori grouping of objects exists, the process of deriving the classification rules from samples of classified objects is known as discrimination. When such rules are applied to objects of unknown class, the process is denoted classification. The specific problem addressed involves the group classification of a set of objects that are each associated with a series of measurements (ratio, interval, ordinal, or nominal levels of measurement). Each measurement produces one variable in a multidimensional variable space. Cluster analysis techniques are reviewed and methods for incuding geographic location, distance measures, and spatial pattern (distribution) as parameters in clustering are examined. For the case of patterning, measures of spatial autocorrelation are discussed in terms of the kind of data (nominal, ordinal, or interval scaled) to which they may be applied.

Glick, B. J.↗
DOE OSTI2013

BENCHMARK TESTS FOR MARKOV CHAIN MONTE CARLO FITTING OF EXOPLANET ECLIPSE OBSERVATIONS

Ground-based observations of exoplanet eclipses provide important clues to the planets' atmospheric physics, yet systematics in light curve analyses are not fully understood. It is unknown if measurements suggesting near-infrared flux densities brighter than models predict are real, or artifacts of the analysis processes. We created a large suite of model light curves, using both synthetic and real noise, and tested the common process of light curve modeling and parameter optimization with a Markov Chain Monte Carlo algorithm. With synthetic white noise models, we find that input eclipse signals are generally recovered within 10% accuracy for eclipse depths greater than the noise amplitude, and to smaller depths for higher sampling rates and longer baselines. Red noise models see greater discrepancies between input and measured eclipse signals, often biased in one direction. Finally, we find that in real data, systematic biases result even with a complex model to account for trends, and significant false eclipse signals may appear in a non-Gaussian distribution. To quantify the bias and validate an eclipse measurement, we compare both the planet-hosting star and several of its neighbors to a separately chosen control sample of field stars. Re-examining the Rogers et al. Ks-band measurement of CoRoT-1b finds an eclipse 3190{sup +370}{sub -440} ppm deep centered at {phi}{sub me} = 0.50418{sup +0.00197}{sub -0.00203}. Finally, we provide and recommend the use of selected data sets we generated as a benchmark test for eclipse modeling and analysis routines, and propose criteria to verify eclipse detections.

79 ASTRONOMY AND ASTROPHYSICS↗