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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Single-colony MALDI mass spectrometry imaging reveals spatial differences in metabolite abundance between natural and cultured Trichodesmium morphotypes

Trichodesmium, a globally significant N 2 -fixing marine cyanobacterium, forms extensive surface blooms in nutrient-poor ocean regions. These blooms consist of a dynamic assemblage of Trichodesmium species that form distinct colony morphotypes and are inhabited by diverse microorganisms. Trichodesmium colony morphotypes vary in ecological niche, nutrient uptake, and organic molecule release, differentially impacting ocean carbon and nitrogen biogeochemical cycles. Here, we assessed the poorly studied spatial abundance of metabolites within and between three morphologically distinct Trichodesmium colonies collected from the Red Sea. We also compared these results with two morphotypes of the cultivable Trichodesmium strain IMS101. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) coupled with liquid extraction surface analysis (LESA) tandem mass spectrometry (MS2), we identified and localized a wide range of small metabolites associated with single-colony Trichodesmium morphotypes. Our untargeted MALDI-MSI approach revealed 80 unique features (metabolites) shared between Trichodesmium morphotypes. Discrimination analysis showed spatial variations in 57 shared metabolites, accounting for 62% of the observed variation between morphotypes. The greatest variations in metabolite abundance were observed between the cultured morphotypes compared to the natural colony morphotypes, suggesting substantial differences in metabolite production between the cultivable strain IMS101 and the naturally occurring colony morphotypes that the cultivable strain is meant to represent. This study highlights the variations in metabolite abundance between natural and cultured Trichodesmium morphotypes and provides valuable insights into metabolites common to morphologically distinct Trichodesmium colonies, offering a foundation for future targeted metabolomic investigations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Data and Scripts associated with “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling.”

This data package is associated with the publication “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling” submitted to Geoscientific Model Development (Muller et al., 2024). In this manuscript, organic matter chemistry and thermodynamics are directly connected to reactive transport simulators through the newly developed Lambda-PFLOTRAN (Parallel Reactive Flow and Transport model) workflow tool that succinctly incorporates organic matter chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate aerobic respiration of the organic matter and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow, executed through a Jupyter Notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow, and transport code PFLOTRAN. This data package contains Jupyter Notebook based workflows for two test cases for running biogeochemical simulations of organic matter oxidation identified by FTICR-MS. It contains four primary folders (workflow, data, src, and analysis), a file-level metadata file (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_flmd.csv) that lists all the files contained in this data package with a short description of each, and a data dictionary (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_dd.csv) file that describes the tabular column headers. The ‘workflow’ folder contains the Jupyter Notebook based workflows for running the lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘data’ folder contains the FTICR-MS data, initial conditions, and incubation data for test cases 1 and 2 in folders titled ‘WHONDRS’ and ‘Colloids’, respectively. The data folder also has a ‘Database’ folder containing a reaction network for bulk organic matter (assumed to be CH2O) and a general database for PFLOTRAN (hanford_rxn_network). The CH2O reaction network defines bulk organic matter oxidation. Biogeochemical simulations are completed for both the lambda binned organic matter and bulk organic matter reaction networks. The ‘hanford_rxn_network’ database includes information required for PFLTORAN simulations including ion size, molar mass, and charge of the aqueous species, gases, and minerals phases. The ‘src’ folder contains python source codes for performing lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘analysis’ folder contains outputs from the test cases 1 and 2 including lambda analysis, PFLOTRAN runs and the calibration results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ultrahigh-resolution mass spectrometry data associated with the manuscript “A functional microbiome catalog crowdsourced from North American rivers"

This data package is associated with the publication “A functional microbiome catalog crowdsourced from North American rivers” submitted to Nature (Borton et al., 2024); (https://www.biorxiv.org/content/10.1101/2023.07.22.550117v1). Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial determinants governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb is a publicly available resource that paves the way for watershed predictive modeling and microbiome-based management practices. This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. We identified the most cosmopolitan microbiome members, while also revealing local drivers of strain endemism across ecological dimensions. We provide the first evidence that microbial functional trait expression followed the tenets of the River Continuum Concept, suggesting the structure and function of river microbiomes is predictable. The Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data were one of many different data types used in establishing the ecological dimensions along which different microbes were detected .This data package only contains the processed FTICR-MS data associated with this manuscript; all other data is accessible via Zenodo (https://zenodo.org/records/8173287), GitHub (https://github.com/jmikayla1991/Genome-Resolved-Open-Watersheds-database-GROWdb), KBase (https://doi.org/10.25982/109073.30/1895615), and NCBI via Bioproject PRJNA946291.This dataset consists of (1) a file-level metadata (flmd) file; (2) a data dictionary (dd) file; (3) a readme; (4) three Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) processed data files (a ‘data’ file containing peak-by-sample observations, a ‘mol’ file containing peak metadata, and a transformation profile containing transformation-by-sample observations). All files are .csv or .pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Preliminary Investigation for the Use of Digital Gamma-Gamma Coincidence Spectrometry to Determine 239 Pu

Gamma-ray spectrometry is one of the most effective ways to determine the activity of 239 Pu, depending on activity levels. However, often high backgrounds in complex spectra with low amounts of 239 Pu can increase detection limits. The effectiveness of the use of gamma-gamma spectrometry in the characterization of 239 Pu was studied for the first time. Using the XIA Pixie-16 digital pulse processor, the gamma-gamma system was studied to establish unshielded background radiation, source to detector distances, Poisson statistics and gating of several gamma-rays from 239 Pu. The results clearly show that the distance between gamma ray spectrometers has a much bigger effort in counting statistics for the gamma-gamma coincidence detectors than a single detector. In addition, measurements demonstrated the background radiation to be virtually negligible, meaning gammagamma spectroscopy can still be very effective without requiring the usual lead shielding. Other measurements were taken to assure Poisson statistics were attained in the digital system. Preliminary measurements revealed 3 orders of magnitude background reduction for the measurement of 239 Pu using gated gamma-rays.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

NWAL Validation Report for U Assay by Potentiometric Titration (Modified Davies and Gray Technique) and U and PU Assay by Isotope Dilution Mass Spectrometry

SRNL Sensing & Metrology, previously Analytical Laboratory, is a member of the IAEA Network of Analytical Laboratories for Nuclear Material Measurement that is qualified to provide Uranium and Plutonium isotopic analysis of nuclear materials by Thermal Ionization Mass Spectrometry. As part of the membership, SRNL participated in the 2019 Nuclear Material Round Robin to maintain the qualification to provide isotopic analysis. SRNL also participated with the additional intent to qualify Uranium Assay by Potentiometric Titration (Davies and Gray method) and Uranium and Plutonium Isotope Dilution by Thermal Ionization Mass Spectrometry as part of the International Atomic Energy Agency’s Network of Analytical Laboratories. The proficiency test exercise was conducted by the Office of Safeguards Analytical Services, Department of Safeguards.

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

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data

High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as molecular beam mass spectrometry (py-MBMS) analyses are becoming increasingly popular for the rapid analysis of biomass cell wall composition and typically require the use of different data analysis tools depending on the need and application. Here, the authors report the py-MBMS analysis of several types of lignocellulosic biomass to gain an understanding of spectral patterns and variation with associated biomass composition and use machine learning approaches to classify, differentiate, and predict biomass types on the basis of py-MBMS spectra. Py-MBMS spectra were also corrected for instrumental variance using generalized linear modeling (GLM) based on the use of select ions relative abundances as spike-in controls. Machine learning classification algorithms e.g., random forest, k-nearest neighbor, decision tree, Gaussian Naïve Bayes, gradient boosting, and multilayer perceptron classifiers were used. The k-nearest neighbors (k-NN) classifier generally performed the best for classifications using raw spectral data, and the decision tree classifier performed the worst. After normalization of spectra to account for instrumental variance, all the classifiers had comparable and generally acceptable performance for predicting the biomass types, although the k-NN and decision tree classifiers were not as accurate for prediction of specific sample types. Gaussian Naïve Bayes (GNB) and extreme gradient boosting (XGB) classifiers performed better than the k-NN and the decision tree classifiers for the prediction of biomass mixtures. The data analysis workflow reported here could be applied and extended for comparison of biomass samples of varying types, species, phenotypes, and/or genotypes or subjected to different treatments, environments, etc. to further elucidate the sources of spectral variance, patterns, and to infer compositional information based on spectral analysis, particularly for analysis of data without a priori knowledge of the feedstock composition or identity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

133Xe Noble Gas Mass Spectrometry Measurement for High Purity Germanium Detector Performance Verification

Idaho National Laboratory produces quality control standards for laboratories that operate xenon radionuclide monitoring systems. Activities reported with each quality control standard are quantified using high purity germanium detectors. A collection of measurement capabilities are being set up at Idaho National Laboratory to establish an in-house high purity germanium detector performance verification system, with noble gas mass spectrometry being one of these measurement capabilities. The first noble gas mass spectrometry and high purity germanium measurement comparison is presented here. A Xe-133 gas sample was prepared and the activity was quantified with high purity germanium detectors. The Xe-133 sample was diluted with a known quantity of isotopically enriched Xe-126 gas; the resulting Xe-133 : Xe-126 atom ratio was calculated to be 1.15x10-4 +/- 2% at reference time t. An aliquot of this gas sample containing approximately 10 million Xe-133 atoms was introduced into a ThermoFisher Scientific Helix MC Plus noble gas mass spectrometer for analysis. The measured Xe-133 : Xe-126 atom ratio was determined to be 1.10x10-4 +/- 2% (1-sigma uncertainty) at reference time t, about 4.3% lower than the atom ratio determined with the measured high purity germanium activity.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2021

Optimization of In-Field Alpha Spectrometry for Uranium Enrichment Determination in Uranium Hexafluoride

In response to needs identified by the International Atomic Energy Agency (IAEA) research is underway to develop In-Field Alpha Spectrometry (IFAS) as a method to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF6) at processing facilities to assess and verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (UO2F2). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the past year optimization work has significantly increased the diameter of useful SUDA samples (from 12.7 mm to 48 mm), improved the manufacturability and reproducibility of SUDA samples, increased the area of the IFAS alpha spectrometer sensor from 1.2 cm to 3.1 cm, and improved source positioning within the IFAS. This paper will report on this optimization work, its impacts on IFAS performance, and future plans for IFAS miniaturization, improvements, and testing.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2021

Mass Spectrometry Imaging of Bio‐oligomer Polydispersity in Plant Tissues by Laser Desorption Ionization from Silicon Nanopost Arrays

Abstract Mass spectrometry imaging (MSI) enables simultaneous spatial mapping for diverse molecules in biological tissues. Matrix‐assisted laser desorption ionization (MALDI) mass spectrometry (MS) has been a mainstream MSI method for a wide range of biomolecules. However, MALDI‐MSI of biological homopolymers used for energy storage and molecular feedstock is limited by, e.g., preferential ionization for certain molecular classes. Matrix‐free nanophotonic ionization from silicon nanopost arrays (NAPAs) is an emerging laser desorption ionization (LDI) platform with ultra‐trace sensitivity and molecular imaging capabilities. Here, we show complementary analysis and MSI of polyhydroxybutyric acid (PHB), polyglutamic acid (PGA), and polysaccharide oligomers in soybean root nodule sections by NAPA‐LDI and MALDI. For PHB, number and weight average molar mass, polydispersity, and oligomer size distributions across the tissue section and in regions of interest were characterized by NAPA‐LDI‐MSI.

Samarah, Laith Z.↗
DOE OSTI2022

Energy-resolved mass spectrometry as a tool for identification of lignin depolymerization products

Lignin is the largest source of bio-based aromatic compounds in nature, and its valorization is essential to the sustainability of lignocellulosic biorefining. Characterizing lignin-derived compounds remains challenging due to the heterogeneity of this biopolymer. Tandem mass spectrometry is a promising tool for lignin structural analytics, as fragmentation patterns of model compounds can be extrapolated to identify characteristic moieties in complex samples. This work extends previous resonance excitation type collision-induced dissociation (CID) methods that identified lignin oligomers containing β-Ο-4, β-5, and β-β bonds, to also identify characteristics of 5-5, β-1, and 4-Ο-5 dimers, enabled by quadrupole time-of-flight (QTOF) CID with energy-resolved mass spectrometry (ERMS). Overall, beam type ERMS offers in-depth structural information and could ultimately contribute to tools for high-throughput lignin dimer identification.

09 BIOMASS FUELS↗
DOE OSTI2024

Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high‐resolution mass spectrometry data across a freshwater stream network

Abstract Advancing our understanding of dissolved organic matter (DOM) chemistry in aquatic systems necessitates the integration of data streams from multiple analytical platforms. Some measurements require pretreatment with solid phase extraction (SPE), while others are performed directly on whole water samples. Evidence has suggested that SPE will be biased against select DOM fractions, leading to concerns over the ability to establish data linkages across platforms with variable needs for SPE pretreatment, such as those from optical measurements and those that provide high‐resolution molecular information. Here, we directly addressed this concern by assessing the impact of SPE on DOM optical properties through excitation–emission matrices with parallel factor analysis (PARAFAC) for 47 samples across a stream network within a single watershed reflective of variable DOM sources. PARAFAC data was further paired with molecular information obtained by Fourier transform ion cyclotron resonance mass spectrometry (FTICR‐MS). A comparison of PARAFAC models first revealed no systematic qualitative differences in major components between whole water DOM and DOM isolated by SPE (SPE‐DOM); however, quantitative biases against select components were observed. Further linkages with FTICR‐MS data revealed that the molecular fingerprint associated with each PARAFAC component was consistent between the whole water DOM and SPE‐DOM. Our results suggest that bulk scale linkages across these analytical platforms could be inferred irrespective of the observed quantitative biases resulting from SPE for samples within this example watershed. This work represents a key step toward the systematic evaluation of linkages between optical and high‐resolution mass spectrometry datasets in freshwater lotic environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Identification of Blue Discoloration in PBX 9404 using Ultrahigh Pressure Liquid Chromatography with Quadrupole Time-of-Flight Mass Spectrometry

PBX 9404, composed of 94 wt% HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazoctane), 3 wt% NC (nitrocellulose), 2.9 wt% CEF (tris(beta-chloroethyl) phosphate) and 0.1 wt% DPA (diphenylamine), has often been observed with a slight to entire blue discoloration of the manufactured prills. This blue discoloration has been observed since the formulation development of PBX 9404 in the late 1950s. In order to determine the source of the blue discoloration in PBX 9404, ultraviolet/visible (UV/Vis) absorbance of PBX 9404 and two potential candidates for the discoloration, p-nitrosodiphenylamine (p-NDPA) and N-nitrosodiphenylamine (N-NDPA) were evaluated. An absorbance band at 590 nm in PBX 9404 sample was attributed to the blue discoloration while p-NDPA and N-NPDA had different absorbance bands. Using the knowledge gained from the UV/Vis analysis, a semi-targeted approach using ultrahigh pressure liquid chromatography coupled to UV/Vis detector and quadrupole time of flight mass spectrometry (UHPLC-UV/Vis-QTOF) was implemented. Investigating the UHPLC-UV/Vis-QTOF chromatograms at a wavelength of 590 nm, a single compound was tentatively identified as being the source of the blue discoloration. Targeted tandem mass spectrometry (MS/MS) on the compound and subsequent analysis indicated that 4,4 -{[4-(Phenylimino)-2,5-cyclohexadien-1-ylidene]methylene}bis(N-phenylaniline), also known as Spirit Blue Base, was the source of the blue discoloration, which was confirmed using a standard. Here, a theory on the formation of Spirit Blue Base in PBX 9404 involving DPA, nitric acid (HNO 3 ) / nitrogen oxide(s) NO x , and formaldehyde is proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Implementation of Ion Mobility Spectrometry-Based Separations in Structures for Lossless Ion Manipulations (SLIM)

Structures for Lossless Ion Manipulations (SLIM) is a powerful variant of traveling wave ion mobility spectrometry (TW-IMS) that uses a serpentine pattern of microelectrodes deposited onto printed circuit boards to achieve ultralong ion path lengths (13.5 m). Ions are propelled through SLIM platforms via arrays of TW electrodes while RF and DC electrodes provide radial confinement, establishing near lossless transmission. The recent ability to cycle ions multiple times through a SLIM has allowed ion path lengths to exceed 1000 m, providing unprecedented separation power and the ability to observe ion structural conformations unobtainable with other IMS technologies. The combination of high separation power, high signal intensity, and the ability to couple with mass spectrometry places SLIM in the unique position of being able to address longstanding proteomics and metabolomics challenges by allowing the characterization of isomeric mixtures containing low abundance analytes.

Hollerbach, Adam L.↗
DOE OSTI2022

Development and Application of DropletProbe Mass Spectrometry for Examining Biodistribution of Therapeutics

dropletProbe mass spectrometry is a novel technique for molecular characterization of surfaces. It can be used for rapid ex vivo analysis of therapeutics from thin animal tissue sections and has been shown to improve understanding of a drug’s absorption, distribution, metabolism and excretion (ADME) properties. Here, we describe the tissue distribution analysis of diclofenac from a dosed whole-body mouse thin tissue section using a dropletProbe mass spectrometry system.

Chen, Bingming↗
DOE OSTI2022

Discovery of unknown posttranslational modifications by top-down mass spectrometry

Post-translational modifications can be important biomarkers of function within biological systems. Top-down mass spectrometry is a valuable tool for the characterization of combinatorial modifications on proteins such as histones that have a range of complex modifications. In this chapter, we present a top-down liquid chromatography-mass spectrometry experimental and data analysis workflow for the identification of novel modifications on proteins. The data analysis workflow presented here is reliant on the combination of proteoform searching using TopPIC and data visualization and fragment ion spectral confirmation using LcMsSpectator, part of the Informed-Proteomics package of software.

Wilson, Jesse W.↗
DOE OSTI2022

Rapid quantification of alcohol production in microorganisms based on nanostructure-initiator mass spectrometry (NIMS)

We described a mass spectrometry-based assay to rapidly quantify the production of primary alcohols directly from cell cultures. This novel assay used the combination of TEMPO-based oxidation chemistry and oxime ligation, followed by product analysis based on Nanostructure-Initiator Mass Spectrometry. This assay enables quantitative monitor both C5 to C18 alcohols as well as glucose and gluconate in the growth medium to support strain characterization and optimization. We find that this assay yields similar results to gas chromatography for isoprenol production but required much less acquisition time per sample. We applied this assay to gain new insights into P. Putida's utilization of alcohols and find that this strain largely could not grow on heptanol and octanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Comparison and validation of the QuEChERSER mega-method for determination of per- and polyfluoroalkyl substances in foods by liquid chromatography with high-resolution and triple quadrupole mass spectrometry

Instances of food contamination with per- and polyfluoroalkyl substances (PFAS) continue to occur globally, but sample preparation and analytical methods are quite limited and often monitor for a small percentage of known PFAS. This study aimed to evaluate, validate, and compare performance of two instruments with the recently developed “quick, easy, cheap, effective, rugged, safe, efficient, and robust” (QuEChERSER) sample preparation mega-method – a method developed to monitor chemicals over a broad range of physicochemical properties. Initial evaluation of the QuEChERSER mega-method for determination of PFAS in food demonstrated recoveries, matrix interferences, and co-extractive removal comparable to (or better than) US Food and Drug Administration (FDA) and USDA Food Safety and Inspection Service (FSIS) methods. Subsequent validation of QuEChERSER in beef, catfish, chicken, pork, liquid eggs, and powdered eggs on a high-resolution mass spectrometer achieved acceptable recoveries (70–120%) and precision (RSDs ≤20%) for all 33 target analytes at the 1 and 5 ng g –1 levels and 67–88% of analytes at the 0.1 ng g –1 level, depending on the matrix. Additional validation was performed by tandem mass spectrometry on a triple quadrupole instrument. This approach provided no non-detects and better recoveries at the 0.1 ng g –1 level than the HRMS method but exhibited more variability at 1 and 5 ng g –1 spiking levels. Analysis of NIST SRMs 1946 and 1947 gave accuracies of 70–117%. Furthermore, these results demonstrate the capability of combining PFAS analysis with a mega-method previously validated for 350 analytes, while collecting non-target data for future retrospective analysis of emerging alternatives with a high-resolution mass spectrometry method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Use of Compton suppression gamma ray spectrometry to determine 239 Pu

We report 239 Pu has been characterized by gamma-ray spectroscopy for a level higher than the usual environmental ones typically needing alpha spectrometry, ICP-MS or TIMS. The higher activities typically have applications in reprocessing, safeguards verification, and nuclear forensics. For activities of hundreds of Bq/g, it is possible to use gamma ray spectrometry for 239 Pu characterization. A soil reference standard of 185 Bq/g (75 ng/g) was measured on a 79% efficient HPGe with a digital Compton suppression system. The ratios of the counting statistics for suppressed and unsuppressed uncertainties for various 239 Pu photopeaks were determined. The effects of self-attenuation on the low energy gamma rays were evaluated, and it was determined that Compton suppression was an effective characterization method of 239 Pu after accounting for self-attenuation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗