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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

System and method for structural characterization of materials by supervised machine learning-based analysis of their spectra

A method of supervised machine learning-based spectrum analysis information, using a neural network trained with spectrum information, to identify a specified feature of a given material, a system for supervised machine learning-based spectrum analysis, and a method of training a neural network to analyze spectrum data. The method of supervised machine learning-base spectrum analysis comprises inputting into the neural network spectrum data obtained from a sample of the given material; and the neural network processing the spectrum data, in accordance with the training of the neural network, and outputting one or more values for the specified feature of the sample of the material. In an embodiment, the training set of data includes x-ray absorption spectroscopy data for the given material. In an embodiment, the training set of data includes electron energy loss spectra (EELS) data.

Frenkel, Anatoly↗
DOE OSTI2018

Magnetic Barkhausen noise characterization of two pipeline steels with unknown history

Highlights: • The hardness, microstructure, texture and MBN of two pipeline steels were analyzed. • The angular MBN results revealed possible manufacturing histories of the two pipelines. • The MBN is closely related to the processing history, microstructure and stress state. • The use of MBN technique can help address the integrity issues in the pipeline industry. Steel samples cut from two line pipes with unknown processing history were analyzed using magnetic Barkhausen noise (MBN), electron backscatter diffraction (EBSD) and Vickers hardness techniques on the pipe surface and on sections through the wall thickness. The results show that the MBN responses vary significantly not only between the two pipe steels, but also among different thickness layers of each steel. Both steels show considerable variations in MBN at different locations on the surfaces. For one steel, the surface MBN illustrates an inverse linear relationship with respect to the hardness, while the other does not depict such a relation since the variation in hardness at different locations is very small. Across the thickness, the microstructure (phase and grain size) of both steels is quite similar, but the texture shows significant differences. Again, there is a large difference in hardness across the thickness for one steel, while the other only shows very small variation in hardness across the thickness. The variations in average MBN across the wall thickness for both steels are quite large. Angular MBN measurements on the sectioned samples revealed significant discrepancies in the magnetic anisotropy in the two steels. Based on the analysis of the angular MBN data with respect to the single and dual easy axis models, one pipe can be determined to have been manufactured through a seam welding process, while the other may have been formed by spiral welding. Due to the residual stresses in the steel samples, the effect of the crystallographic texture on the anisotropy in MBN response has essentially been suppressed.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Squeezing Every Last 'Bit' of Information from Enceladus Mass Spectrometry

Potential opportunities to return to Enceladus in Discovery and Flagship class missions inspire development of next-generation instruments and creative approaches to sample collection, sample analysis, and data analysis and transmission strategies. Mass spectrometers (MS) are ideally suited to future Enceladus missions due to their analytical power in identifying a range of molecular and ionic compositions – including complex organics – and potentially astrobiologically-important features such as isotope ratios, chirality, and enantiomeric excess. However, long communication delays from Enceladus and limited bandwidth limits the data transmission from these higher-data-volume instruments, likely delaying mission-related response to new data. We explore the utility of data science and machine learning (ML) on isotope ratio (IR)MS data collected from laboratory analogs of Enceladus to: 1) process data quickly for rapid ground-based analyses, 2) understand if compositional and biosignature information could be extracted from IRMS data, and 3) evaluate whether onboard ML techniques could improve sample analysis, cadence, and transmission prioritization. Laboratory analogs analyzed isotopes of volatile CO2 that interacted with seawaters of varying composition, and include both abiotic and biotic (microbially-influenced) experiments. Enceladus’s alkaline oceans promote speciation of carbon into multiple forms (e.g., H2CO3 / CO2, HCO3-, and CO32-), each of which could be isotopically fractionated by abiotic or biotic reactions. Large (>2‰) changes in carbon isotopes (δ13C) are observed from some biotic experiments inoculated with complex microbial ecosystems relative to the abiotic seawaters. ML training and classification suggests that microbial samples can be distinguished from abiotic samples, yet that a broad range of microbial experiments are necessary to train ML models to cover a range of complexities including disequilibria, and isotopic and compositional fractionation.

geochemistry↗
NASA NTRSDate not supplied

Processing Frozen Apollo Samples in a Nitrogen Environment

A few weeks after their return to Earth, several Apollo 17 regolith sample splits and one Apollo 17 basalt were frozen at -20˚C (under dry gaseous N2 like all other pristine Apollo samples), and have remained essentially unstudied within the Apollo sample collection at NASA’s Johnson Space Center (JSC). As part of the Apollo Next Generation Sample Analysis (ANGSA) project, these frozen samples were selected for consortium study in 2019. Although the samples themselves were kept at -20˚C for nearly 50 years, the JSC Curation office has lacked a facility for processing frozen samples under pristine Apollo processing conditions. A temporary lab for this work was designed, built, and tested. Procedures were then developed for working in this unique environment, and the facility was sucessfully used to process the frozen Apollo samples for scientific allocation.

ANGSA↗
DOE OSTI2022

Improved uranium isotopic ratio determinations for the liquid sampling-atmospheric pressure glow discharge orbitrap mass spectrometer by use of moving average processing

The liquid sampling-atmospheric pressure glow discharge (LS-APGD) is a versatile combined atomic and molecular (CAM) ionization source capable of ionizing elemental species, small polar compounds, low-polarity polycyclic aromatic hydrocarbons, and proteins. While the LS-APGD has been proven capable of determining the 235U/238U isotope ratio in enriched and natural uranium, recent efforts have strived to reduce the analysis time of individual measurements by employing higher-order data processing techniques, specifically, moving average methods. Additionally, the use of a moving average (of data windows of various widths) improves the precision of the ratio measurements and reduces the number of scans needed to be collected to generate high-precision results. Additionally, use of the moving average minimizes the quantity of sample that needs to be analyzed while reducing the measurement time. These reductions have allowed isotope ratio (IR) determinations to be made using injections instead of direct infusion of the analyte. For example, employing a 40-point window width in the moving average to direct infusion data reduced the percent relative standard deviation (% RSD) of the 235U/238U values from 3.4% to 0.5%. For the injection of a 100 μL aliquot, the % RSD was reduced from 5.3% to 0.7%.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Raman Spectroscopy for the On Line Analysis of Oxidation States of Oxygen Carrier Particles

The need for cleaner energy systems, including CO 2 capture technologies, is driving the current development of new combustion approaches such as chemical looping combustion (CLC). This process is based on using oxygen carrier particles (OCPs) such as iron oxides, copper oxides, calcium sulfates, etc. to provide the oxygen for the combustion process. In order to optimize the overall process performance, it is critical that the properties of the oxygen carriers are well-defined and maintained for their specific purpose during the different stages of the CLC process. One of the critical properties of the oxygen carrier is its oxidation state (e.g., content of Fe 2 O 3 vs. Fe 3 O 4 ) as it affects the fundamental operation of the CLC process. Unfortunately, the ability to make on-line measurements of the oxidation state of oxygen carriers is lacking and new sensors need to be developed. Our goal is to develop a sensor for the on-line analysis of the oxidation state of oxygen carrier particles and to demonstrate its feasibility. Oxygen carrier particles (OCPs) of interest include iron oxides, copper oxides, and calcium sulfate, with particle sizes typically less than 0.5 mm diameter. The expected operating conditions of the sensor include OCP temperatures in the range of 800 °C to 1000 °C, and pressures of about 10 atm. The expected results are to be of a statistical nature, providing relative concentrations of the different oxidation states. These requirements make a strong case for using non-contact, stand-off, pulsed Raman spectroscopy as a sensor for the high-temperature on-line analysis of oxygen carrier particles. In order to achieve our goal, we have set up and tested a pulsed Raman spectroscopy system in combination with a pressurized high-temperature sample chamber, and have taking initial Raman spectra of various materials at high temperature. We are now in the process of optimizing the operating parameters such as laser wavelength, laser intensity, collection optic design, focal spot size, data acquisition, etc. We will also develop an analysis procedure for the interpretation of the Raman spectra. Typical Raman spectra consist of a convolution of background signal and multiple individual spectra. In order to extract relevant information such as the concentration ratio of a material in different oxidation states, we need to process (background subtraction, deconvolution, fitting, etc.) the measured data. In addition, statistical modeling and multivariate calibration need to be performed to correctly analyze the Raman spectra.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2018

An Efficient Algorithm for Automatic Structure Optimization in X-ray Standing-Wave Experiments

We present that x-ray standing-wave photoemission experiments involving multilayered samples are emerging as unique probes of the buried interfaces that are ubiquitous in current device and materials research. Such data require for their analysis a structure optimization process comparing experiment to theory that is not straightforward. In this work, we present a new computer program for optimizing the analysis of standing-wave data, called SWOPT, that automates this trial-and-error optimization process. The program includes an algorithm that has been developed for computationally expensive problems: so-called black-box simulation optimizations. It also includes a more efficient version of the Yang X-ray Optics Program (YXRO) [Yang, S.-H., Gray, A.X., Kaiser, A.M., Mun, B.S., Sell, B.C., Kortright, J.B., Fadley, C.S., J. Appl. Phys. 113, 1 (2013)] which is about an order of magnitude faster than the original version. Human interaction is not required during optimization. We tested our optimization algorithm on real and hypothetical problems and show that it finds better solutions significantly faster than a random search approach. The total optimization time ranges, depending on the sample structure, from minutes to a few hours on a modern laptop computer, and can be up to 100x faster than a corresponding manual optimization. Finally, these speeds make the SWOPT program a valuable tool for realtime analyses of data during synchrotron experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Rapid processing of 85 Kr/Kr ratios using Atom Trap Trace Analysis

In this paper, we report a methodology for measuring 85 Kr/Kr isotopic abundances using Atom Trap Trace Analysis (ATTA) that increases sample measurement throughput by over an order of magnitude to six samples per 24 h. The noble gas isotope 85 Kr (half-life = 10.7 years) is a useful tracer for young groundwater in the age range of 5–50 years. ATTA, an efficient and selective laser-based atom counting method, has recently been applied to 85 Kr/Kr isotopic abundance measurements, requiring 5–10 μL of krypton gas at STP extracted from 50 to 100 L of water. Previously, a single such measurement required 48 h. In conclusion, our new method demonstrates that we can measure 85 Kr/Kr ratios with 3–5% relative uncertainty every 4 h, on average, with the same sample requirements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Robust Solar Receivers Using MAX Phase Materials

This work was supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Solar Energy Technologies Office Award Number 35928. The objective of the proposed effort was to develop and optimize additive manufacturing technologies for low-cost fabrication of high-temperature receivers using MAX phase-based materials (Ti 3 SiC 2 and Ti 3 AlC 2 ). MAX phase materials are a group of ternary metal carbides and nitrides where M stands for an early transition metal element, A is a group 13–16 element, and X is C and/or N. In Phase 1, the binder jetting additive manufacturing process was used to synthesize and characterize the Ti 3 SiC 2 MAX phase material. The typical process involved first producing a TiC preform using binder jetting followed by infiltration of the preform with silicon melt to form Ti 3 SiC 2 in situ. The reaction-infiltrated samples showed formation of MAX phase in the sample core; however, the surface showed cracking. Various process conditions—cooling rates, hold times, Si proportion, etc.—were varied to minimize the surface cracking. The fabricated MAX phase core was characterized by microstructure analysis and evaluations of mechanical properties such as hardness and thermal shock. In Phase 2, the focus included fabrication of Ti 3 SiC 2 MAX phase materials by spark plasma sintering (SPS) and synthesis of Ti 3 AlC 2 MAX phase materials by the Al melt infiltration process. It is expected that Al infiltration will not cause sample cracking, since Al does not expand during solidification. In addition, other processing approaches were investigated to fabricate the MAX phase materials, such as SPS with a graphite bedding approach for producing short-length Ti 3 AlC 2 MAX phase tubes for demonstration of prototypical Concentrating Solar Power receiver tubes. Fabricated samples underwent thermo-mechanical testing to validate the materials for the solar receiver application at temperatures >1000°C. In Phase 3, the effort focused on the development and optimization of the Ti-Al-C MAX phase composite material using the Al melt infiltration approach. We started with optimization of precursor powders and making preform structures by either pressing them in a die or using the binder jetting additive manufacturing process followed by Al melt infiltration. In addition, we investigated the formation of preform structures by cold isostatic pressing followed by Al melt infiltration for making Ti-Al-C MAX phase composite. Thermo-mechanical characterizations, such as creep, strength, and thermal shock, were conducted to establish the structures’ performance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Distribution Development for Residual Inventory at the New York West Valley Site - 20400

The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351 ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into Agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States. NFS, a private company, built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations ended in 1972 and never reopened, leaving behind radioactive and chemical wastes. Operations led to contamination in a number of facilities and locations. Some of that contamination has migrated from waste disposal zones to other layers, formations, and features on and off the WNYNSC. Phase I decommissioning activities are ongoing and involve the removal of a number of areas and structures that have been associated with contamination. The purpose of this work is to outline the approach for characterizing contamination not associated with disposed wastes, contaminated structures, or specific releases. In this work, the term, residual radiological activity, is used to describe environmental contamination that exists subsequent to the completion of Phase I decommissioning activities, that is not associated with disposed wastes, contaminated structures, or specific releases. Contamination from the Site was quantified relative to data that characterize the concentrations of radionuclides that exist in background. Background concentrations are those present in the area but having no influence from Site related activities. The existence of residual radiological activity that is elevated relative to background has the potential to contribute to future risks to human health and the environment. As a consequence, the residual inventory information is used to inform the West Valley Probabilistic Performance Assessment (PPA) model to characterize potential future risks to human health and the environment. The centralized West Valley Data Management System (DMS) was the source of information for the data assembled in this analysis. The DMS is a fairly large compilation consisting of thousands of records from investigation studies, with sample dates ranging from 1990 to present. Samples from monitoring wells, boreholes, geoprobe studies, surface water, surface soils, storm water outfalls, ventilation stack filters, plant and animal tissues, and more are included in the DMS. Results are typically reported in units of activity per unit volume. For the purpose of the analyses presented here, all results were converted into consistent units of pCi per unit volume. Since 1990, data have been collected from various locations across the WNYNSC at different times with varying frequency over the course of several decades. As a consequence, a number of potential issues can arise with respect to the assembly of a dataset that is deemed adequate for the characterization of residual radiological activity. These issues were assessed and resolved to the extent possible through careful consideration of the properties of the distributions. The intent was to use data which characterize the current state of the Site. Radionuclides can be designated to one of several groups depending on their origin. In this work the groups considered were 1) Naturally Occurring Radioactive Material (NORM), 2) fallout, and 3) Other (including power plant, medical research, etc). This grouping is a useful construct with respect to the interpretation of fixed laboratory results. For example, NORM radionuclides that exist within a decay chain should have approximately equivalent distributions of concentrations if they are representative of background conditions. Insights such as these can be used as a check to identify sample results that need to be further investigated or omitted due to issues associated with reported results from fixed laboratory analyses. This type of analysis provided a foundation for the assessment of the adequacy of sample results for use in subsequent components of an assessment. The general process for the assessment of residual radiological contamination at the Site consists of a sequence of several steps. First, for each analyte, several statistical tests were performed to assess the weight of evidence against the null hypothesis that the mean of the distribution of concentrations was equal to zero. If the mean of the distribution of concentrations for a given radionuclide was not found to be greater than zero, then it was removed from consideration as a component of the residual radiological contamination. If there was significant evidence to reject the hypothesis of the mean being equal to zero, the second step was to compare the distribution of the data from the Site to that of the corresponding background. A suite of tests was used to compare the distributions of the site and background data. The results of these tests were collectively used to determine if site data are elevated relative to background. The third step was to develop distributions using a Bayesian framework to characterize the distribution of mean of the increment present above background for each of the radionuclides. The Bayesian model implemented allowed for the comparison of site-specific records to background concentrations to better approximate contamination attributed to the Site. A final screening step was employed for radionuclides that exceed background. This screening step compared 95% upper confidence limits (UCLs) from the increment distribution developed in the previous step to the risk screening levels. This approach yields a list of analytes that were determined to be elevated relative to background.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

A Microchannel Heat Exchanger Produced From a Metal Matrix Composite by Hybrid Laser Powder Bed Fusion and Inkjet Printing

Abstract This paper explores the production of an oxide dispersion strengthened (ODS) 304L stainless steel microchannel heat exchanger (HX) using a hybrid additive manufacturing process of laser powder bed fusion and inkjet printing. The study investigates the capabilities and economics of the hybrid inkjet-laser powder bed fusion (LPBF) process and evaluates the dimensional accuracy, functionality, and mechanical properties of the resulting ODS alloy. The effectiveness and pressure drop of the ODS heat exchangers produced by the hybrid LPBF tool are also determined. Results show that the inkjet-doped samples have a lower mean channel height with higher standard deviation than samples produced by LPBF alone. This is attributed to greater absorption of laser energy for the powder coated with the oxide precursor. The economic analysis shows that the hybrid process has a potential for reducing the unit cost of the heat exchanger based on cost modeling assumptions.

Engineering↗
NASA NTRS1985

A preliminary analysis of a comet coma sample-return mission

It is pointed out that the exploration and characterization of comets can play a fundamental role in solar system science. Comets are probably primitive products of processes which occurred in the preplanetary solar nebula. The impending return of Halley's comet in 1986 provides an opportunity for a study of comets, and five spacecraft will be launched to intercept Halley. These spacecraft include two sent by the USSR, two by Japan, and one by the European Space Agency (ESA). NASA has recommended two programs for the exploration and characterization of comets. The first mission considered would be a rendezvous with a short-period comet, while the second mission would provide for the return to earth of a sample of the volatile and nonvolatile constituents of the coma of a comet. Developments related to these plans are discussed.

Swenson, B. L.↗
DOE OSTI2020

Estimation of Sorption Behavior of Europium to Calcium Silicate Hydrate by Thermal Analysis - 20172

High-level radioactive waste generated from reprocessing processes will be disposed in a geological disposal that is deep underground. Calcium silicate hydrate is formed as a secondary mineral in the repository via the reaction of calcium ions leaching from the cement and the silicic acid dissolved from the host rocks. In this study, the sorption behavior of europium, which is also known as a chemical analog of americium, on calcium silicate hydrate was examined. The solid phase was analyzed via thermogravimetry- differential thermal analysis, differential scanning calorimetry, Raman spectroscopy, fluorescence spectroscopy, and fluorescence lifetime analysis. To understand the behavior of calcium silicate hydrate under conditions saturated with groundwater, the study samples were analyzed using the above methods, except for deferential scanning calorimetry, without a drying process. The results of the differential scanning calorimetry analyses showed that the temperatures for the endothermic peaks of calcium silicate hydrate for the lower Ca/Si ratios were larger than those for the higher Ca/Si ratios for coexistent conditions of europium ions. Hence, the relationships of the temperatures of the endothermic peaks and the Ca/Si ratios were reversed by the addition of europium ions. These study results suggest that calcium silicate hydrate can immobilize europium ions, thus preventing the production of colloidal forms. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Omics-Lethal Human Viruses, MERS-CoV Experiment MCL003

The purpose of this experiment was to evaluate the human host response to wild-type icMERS-CoV virus infection and mockulum. Sample data was obtained from human lung adenocarcinoma cells (Calu-3) for proteome, metabolome, and lipidome expression analysis. Resulting quantitative data profiles were evaluated for extreme outlier behavior using MPLEX protocol. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, and lipidomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Extrusion Parameters for Foaming of a β-Glucan Concentrate

Plastics is a group of materials commonly encountered on a daily basis by many people. They have enabled rapid, low-cost manufacturing of products with complicated geometries and have contributed to the weight reduction of heavy components, especially when produced into a foamed structure. Despite the many advantages of plastics, some drawbacks such as the often fossil-based raw-material and the extensive littering of the material in nature, where it is not degraded for a very long time, needs to be dealt with. One way to address at least one of the issues could be to use polymers from nature instead of fossil-based ones. Here, a β-glucan concentrate originating from barley was investigated. The concentrate was processed into a foam by hot-melt extrusion, and the processing window was established. The effect of different blowing agents was also investigated. Water or a combination of water and sodium bicarbonate were used as blowing agents, the latter apparently giving a more uniform pore structure. The porous structure of the foamed materials was characterized mainly by using a combination of confocal laser scanning microscope and image analysis. The density of the samples was estimated and found to be in a similar range as some polyurethane foams. A set of 3D parameters were also quantified on two selected samples using X-ray microtomography in combination with image analysis, where it was indicated that the porous structure had a pre-determined direction, which followed the direction of the extrusion process.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Data Science and the Knowledge Discovery Adventure

This talk will cover the important steps involved in the data science and knowledge discovery process: • Initial fact gathering (interview domain experts, review reports, articles, state-of-the-art) • Identify the problem (prediction, classification, statistical analysis, etc.) • Survey supporting data sources • Understand the data (numerical, categorical, text, sampling rate, data quality issues, etc.) • Selecting relevant features and sources • Acquire the data (set up agreements with the data stewards, APIs to download, etc.) • Merge data sources (temporal, spatial, common key, other ontologies...) • Feature Engineering (non linear domain knowledge or physics-based relationships) • Build data processing pipeline (may need to tap into data stream, develop parallel processing algorithm, federated learning etc.) • Build model and test (tune hyper-parameters, cross validation.) • Analyze/Validate results (do the results make sense. Does it answer the original question). • Deploy/Publish (Monitor and assess benefits)

Data science↗
DOE OSTI2025

An In Situ , Automated High-Explosives Aging Method Utilizing Two-Dimensional Gas Chromatography–Mass Spectrometry

Understanding chemical changes that occur in high explosives as they age is of great importance to the safe employment and storage of these compounds. Traditional methods of aging high explosives even under accelerated aging conditions are time intensive with durations on the order of months to years. The nature of traditional aging analyses reduces each sample to a snapshot data point often separated widely in time, requiring many assumptions as to how the degradation products develop. Further complicating matters, several analytical techniques are typically employed for each sample analysis in order to ascertain an entire picture of the decomposition pathways. To address these shortcomings with existing methods, a new method of accelerated aging of high explosives utilizing comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry (GC × GC-HRMS) was developed using 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20) as a model compound for method development. This in situ automated method reduces the time scale of aging to a matter of hours using the inlet of the GC × GC as the aging vessel. GC × GC in combination with HRMS allowed for the collection of both evolved gases and other decomposition products produced during the entire aging process in real time with HRMS providing far greater certainty in identification of explosives aging products. Additionally, this method allowed for a higher throughput of samples with greatly simplified sample preparation. Chemometric analysis of the GC × GC-HRMS data set via the alteration analysis (ALA) enabled discovery of statistically significant chemical changes providing insight into the variation of decomposition pathways with varying aging temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

An iterative method to deblend AGN-Host contributions for Integral Field spectroscopic observations

ABSTRACT We present a new iterative deblending method to separate the host galaxy (HG) and their Active Galactic Nuclei (AGNs) emission with the use of Integral Field spectroscopic (IFS) data. The method decomposes the resolved HG emission from the unresolved AGN emission by modelling the two-dimensional surface brightness (SB) profile of the point-spread function (PSF) and the two-dimensional SB HG continuum simultaneously per each monochromatic slide. Our method does not require any prior information about the observed SB profile or a detailed fitting of the PSF, making it ideal for the automatic analysis of large galaxy samples. In this work, we test the quality of our method, its advantages, and its disadvantages. We test our method by using a set of IFS mock data cubes to quantify the reliability of our deblending process and further compare our method with the qdblend3d analysis tool. Furthermore, we applied our method to three data cubes selected from the MaNGA survey according to the dominance of either its HG or its AGN. We show that our deblending method is capable of disengaging the bright, non-resolved AGN emission from the HG continuum and its narrow emission lines. However, the decoupling depends on how well the IFS spatially resolves the PSF, and on the relative flux intensity of the HG-AGN. Therefore, the method is ideal for disentangling the bright-flux contribution from AGN-dominated spectra.

Ibarra-Medel, H. (ORCID:0000000297906313)↗