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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An approach to nearest neighbor analysis of pigment-protein complexes using chemical cross-linking in combination with mass spectrometry

Herein, protein cross-linking is the process of chemically joining two amino acids in a protein or protein complex by a covalent bond. When combined with mass spectrometry, it becomes one of the structural mass spectrometry techniques gaining in importance for deriving valuable three-dimensional structural information on proteins and protein complexes. This platform complements existing structural methods, such as NMR spectroscopy, X-ray crystallography, and cryo-EM. Photosynthetic pigment protein complexes serve as light-energy harvesting systems and perform photochemical conversion as part of the “early events” of photosynthesis. This chapter outlines how to prepare cross-linking pigment protein complex samples for LC-MS/MS analysis, including identification of the cross-linked species, network analysis in a protein complex, and structural modeling and justification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Atmospheric Solid Analysis Probe Coupled to Ion Mobility Spectrometry-Mass Spectrometry, a Fast and Simple Method for Polyalphaolefin Characterization

Polyalphaolefins (PAOs) are polymers produced from linear alpha olefins through catalytic oligomerization processes. The PAOs are known as synthetic high-performance base stock fluids used to improve the efficiency of many other synthetic products. In this study, we report the direct characterization of PAOs using atmospheric solid analysis probe (ASAP) coupled with ion mobility spectrometry-mass spectrometry (IMS-MS). We studied different PAOs grades exhibiting low- and high-viscosity index. Specific adjustments of the ASAP source parameters permitted the monitoring of ionization processes as three mechanisms could occur for these compounds: hydride abstraction, nitrogen addition, and/or the formation of [M−2H]{sup +•} ions. Several series of fragment ions were obtained, which allowed the identification of the alpha olefin used to synthesize the PAO. The use of the ion mobility separation dimension provides information on isomeric species. In addition, the drift time versus m/z plots permitted rapid comparison between PAO samples and to evidence their complexity. These 2D plots appear as fingerprints of PAO samples. To conclude, the resort to ASAP-IMS-MS provides a rapid characterization of the PAO samples in a direct analysis approach, without any sample preparation. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Near-infrared spectroscopy as a green analytical tool for sustainable biomass characterization for biofuels and bioproducts: An overview

Biomass, a widely used renewable energy source, requires characterization to optimize biofuel and bioproduct processes, customize feedstocks, and ensure economic and environmental sustainability. Conventional wet-chemistry methods for biomass analysis are slow, expensive, and require significant reagents and skilled personnel. In contrast, near-infrared (NIR) spectroscopy, a faster, cost-effective, and reagent-free green technology, enables non-destructive biomass analysis with minimal sample preparation. This study provides an overview of the fundamentals of NIR spectroscopy and explores its recent applications for analyzing various biomass properties important to the biofuel and bioproduct industry. The study also critically evaluates the challenges and opportunities of using NIR spectroscopy for biomass analysis. This review aims to guide future research for rapid and high throughput characterization of biomass in the biomass industry, supporting the United Nations’ sustainable development goal (SDG) 7: producing affordable and sustainable energy.

Biofuels↗
DOE OSTI2024

Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra

A machine learning framework was developed for predicting uranium enrichments from M400 CZT gamma spectra. This framework leverages the availability of a large amount of measured M400 gamma spectra and uses a recently updated version of Gamma Detector Response and Analysis Software (GADRAS) for gamma spectrum analysis and generation. It also leverages the existing machine learning modules in Python for gamma spectrum data processing, curation, model training, benchmarking, and optimization of the deep machine learning models. The framework is used to develop a deep learning model to analyze gamma spectra from a set of U 3 O 8 samples with enrichments ranging from 0.31 to 93.17% and UF 6 cylinders with enrichments ranging from 0.2 to 4.95%, and the model performance is tested using a set of measured spectra and the respective declared enrichment values. Results show that the model can correctly classify 99.35% of the U 3 O 8 sample enrichments, and can predict the samples’ enrichments within an average absolute error of 0.099% (in percentage points of enrichment). For the UF 6 cylinders, the average absolute error was approximately 0.03%, with an accuracy of 98% in classifying discrete enrichment values of UF 6 samples. Finally, the results also show that the model has performed significantly better in terms of predicting enrichments in UF 6 cylinders based on measured gamma spectra than the GEM code, with a standard deviation (of the relative errors) of 2.23% (compared with the 11.51% value for the GEM code) based on results from a set of test data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Acquisition of STEM Images by Adaptive Compressive Sensing

Compressive Sensing (CS) allows a signal to be sparsely measured first and accurately recovered later in software [1]. In scanning transmission electron microscopy (STEM), it is possible to compress an image spatially by reducing the number of measured pixels, which decreases electron dose and increases sensing speed [2,3,4]. The two requirements for CS to work are: (1) sparsity of basis coefficients and (2) incoherence of the sensing system and the representation system. However, when pixels are missing from the image, it is difficult to have an incoherent sensing matrix. Nevertheless, dictionary learning techniques such as Beta-Process Factor Analysis (BPFA) [5] are able to simultaneously discover a basis and the sparse coefficients in the case of missing pixels. On top of CS, we would like to apply active learning [6,7] to further reduce the proportion of pixels being measured, while maintaining image reconstruction quality. Suppose we initially sample 10% of random pixels. We wish to select the next 1% of pixels that are most useful in recovering the image. Now, we have 11% of pixels, and we want to decide the next 1% of “most informative” pixels. Active learning methods are online and sequential in nature. Our goal is to adaptively discover the best sensing mask during acquisition using feedback about the structures in the image. In the end, we hope to recover a high quality reconstruction with a dose reduction relative to the non-adaptive (random) sensing scheme. In doing this, we try three metrics applied to the partial reconstructions for selecting the new set of pixels: (1) variance, (2) Kullback-Leibler (KL) divergence using a Radial Basis Function (RBF) kernel, and (3) entropy. Figs. 1 and 2 display the comparison of Peak Signal-to-Noise (PSNR) using these three different active learning methods at different percentages of sampled pixels. At 20% level, all the three active learning methods underperform the original CS without active learning. However, they all beat the original CS as more of the “most informative” pixels are sampled. One can also argue that CS equipped with active learning requires less sampled pixels to achieve the same value of PSNR than CS with pixels randomly sampled, since all the three PSNR curves with active learning grow at a faster pace than that without active learning. For this particular STEM image, by observing the reconstructed images and the sensing masks, we find that while the method based on RBF kernel acquires samples more uniformly, the one on entropy samples more areas of significant change, thus less uniformly. The KL-divergence method performs the best in terms of reconstruction error (PSNR) for this example [8].

Xie, Weiyi↗
DOE OSTI2016

Gradient elution moving boundary electrophoresis enables rapid analysis of acids in complex biomass-derived streams

Biomass conversion processes such as pretreatment, liquefaction, and pyrolysis often produce complex mixtures of intermediates that are a substantial challenge to analyze rapidly and reliably. To characterize these streams more comprehensively and efficiently, new techniques are needed to track species through biomass deconstruction and conversion processes. Here, we present the application of an emerging analytical method, gradient elution moving boundary electrophoresis (GEMBE), to quantify a suite of acids in a complex, biomass-derived streams from alkaline pretreatment of corn stover. GEMBE offers distinct advantages over common chromatography-spectrometry analytical approaches in terms of analysis time, sample preparation requirements, and cost of equipment. As demonstrated here, GEMBE is able to track 17 distinct compounds (oxalate, formate, succinate, malate, acetate, glycolate, protocatechuate, 3-hydroxypropanoate, lactate, glycerate, 2-hydroxybutanoate, 4-hydroxybenzoate, vanillate, p-coumarate, ferulate, sinapate, and acetovanillone). The lower limit of detection was compound dependent and ranged between 0.9 and 3.5 umol/L. Results from GEMBE were similar to recent results from an orthogonal method based on GCxGC-TOF/MS. Altogether, GEMBE offers a rapid, robust approach to analyze complex biomass-derived samples, and given the ease and convenience of deployment, may offer an analytical solution for online tracking of multiple types of biomass streams.

09 BIOMASS FUELS↗
DOE OSTI2016

Expanding Lorentz and spectrum corrections to large volumes of reciprocal space for single-crystal time-of-flight neutron diffraction

Evidence is mounting that potentially exploitable properties of technologically and chemically interesting crystalline materials are often attributable to local structure effects, which can be observed as modulated diffuse scattering (mDS) next to Bragg diffraction (BD). BD forms a regular sparse grid of intense discrete points in reciprocal space. Traditionally, the intensity of each Bragg peak is extracted by integration of each individual reflection first, followed by application of the required corrections. In contrast, mDS is weak and covers expansive volumes of reciprocal space close to, or between, Bragg reflections. For a representative measurement of the diffuse scattering, multiple sample orientations are generally required, where many points in reciprocal space are measured multiple times and the resulting data are combined. The common post-integration data reduction method is not optimal with regard to counting statistics. A general and inclusive data processing method is needed. In this contribution, a comprehensive data analysis approach is introduced to correct and merge the full volume of scattering data in a single step, while correctly accounting for the statistical weight of the individual measurements. Development of this new approach required the exploration of a data treatment and correction protocol that includes the entire collected reciprocal space volume, using neutron time-of-flight or wavelength-resolved data collected at TOPAZ at the Spallation Neutron Source at Oak Ridge National Laboratory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-T-258: Development of a New Patient Set-Up Monitoring System Using Force Sensing Resistor (FSR) Sensor for the Radiation Therapy

Purpose: The purpose of this work is to develop a new patient set-up monitoring system using force sensing resistor (FSR) sensors that can confirm pressure of contact surface and evaluate its feasibility. Methods: In this study, we focused on develop the patient set-up monitoring system to compensate for the limitation of existing optical based monitoring system, so the developed system can inform motion in the radiation therapy. The set-up monitoring system was designed consisting of sensor units (FSR sensor), signal conditioning devices (USB cable/interface electronics), a control PC, and a developed analysis software. The sensor unit was made by attaching FSR sensor and dispersing pressure sponge to prevent error which is caused by concentrating specific point. Measured signal from the FSR sensor was sampled to arduino mega 2560 microcontroller, transferred to control PC by using serial communication. The measured data went through normalization process. The normalized data was displayed through the developed graphic user interface (GUI) software. The software was designed to display a single sensor unit intensity (maximum 16 sensors) and display 2D pressure distribution (using 16 sensors) according to the purpose. Results: Changes of pressure value according to motion was confirmed by the developed set-up monitoring system. Very small movement such as little physical change in appearance can be confirmed using a single unit and using 2D pressure distribution. Also, the set-up monitoring system can observe in real time. Conclusion: In this study, we developed the new set-up monitoring system using FSR sensor. Especially, we expect that the new set-up monitoring system is suitable for motion monitoring of blind area that is hard to confirm existing optical system and compensate existing optical based monitoring system. As a further study, an integrated system will be constructed through correlation of existing optical monitoring system. This work was supported by the Industrial R&D program of MOTIE/KEIT. [10048997, Development of the core technology for integrated therapy devices based on real-time MRI guided tumor tracking] and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Constraining Cross Section and Beam Systematics for Future NOvA Sterile Neutrino Search

he NOvA (NuMI Off-axis $\nu_e$ Appearance) experiment measures neutrino oscillations in a nearly pure muon (anti)neutrino beam over a 810 km baseline. We search for sterile neutrino driven oscillations in both neutral current (NC) and charged current (CC) muon neutrino samples. A deficit of NC interactions at the Far Detector could occur since sterile neutrinos do not couple to the Z boson. A modulation of the muon neutrino disappearance probability is possible due to a new mass splitting. The NuMI beam line is capable of running in forward or reverse horn current modes, which creates a neutrino or antineutrino beam, respectively. Samples collected in forward horn current (FHC) or reverse horn current (RHC) modes are subject to beam optics uncertainties, in addition to cross section and hadron production uncertainties. We explore the ategories. To tackle reduction of cross section uncertainties, we study how splitting the neutral current (NC) samples can impact the systematic reduction and its implications on oscillation parameters, leveraging results from Monte Carlo simulations. Additionally, we look at the possibility of using a $\nu$-on-e scattering sample. The $\nu$-on-e scattering process has minimal cross section uncertainties compared to that of neutrino-nucleus interactions, which can help constrain the overall flux normalizations. Using both the ZHC sample, NC split sample, and $\nu$-on-e scattering sample jointly with FHC samples would reduce the focusing uncertainties and the hadron production uncertainties in the future sterile analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Human Lung Cellular Response to HCoV-229E Infection, Post-Translational Modification Proteomics Time Course (ACS-TZ-DP6)

The purpose of this experiment was to evaluate the human lung cellular response to wild type human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock-infected and HCoV-229E infected immortalized human lung epithelial cells (A549) (MOI 3) and immortalized human lung fibroblasts (MRC-5) (MOI 3). Whole cell lysates were collected at 8, 16, and 24 hours post infection and were processed for post translational modification (PTM) proteomics analysis to determine the HCoV-229E phosphoproteome, redox proteome, and acetylation proteome.

Sims, Amy C [Pacific Northwest National Laboratory↗
DOE OSTI2024

Development of a New Aggregation Method to Remove Nanoplastics from the Ocean: Proof of Concept Using Mussel Exposure Tests

The overproduction and mismanagement of plastics has led to the accumulation of these materials in the environment, particularly in the marine ecosystem. Once in the environment, plastics break down and can acquire microscopic or even nanoscopic sizes. Given their sizes, microplastics (MPs) and nanoplastics (NPs) are hard to detect and remove from the aquatic environment, eventually interacting with marine organisms. This research mainly aimed to achieve the aggregation of micro- and nanoplastics (MNPs) to ease their removal from the marine environment. To this end, the size and stability of polystyrene (PS) MNPs were measured in synthetic seawater with the different components of the technology (ionic liquid and chitosan). The MPs were purchased in their plain form, while the NPs displayed amines on their surface (PS NP-NH2). The results showed that this technology promoted a significant aggregation of the PS NP-NH2, whereas, for the PS MPs, no conclusive results were found, indicating that the surface charge plays an essential role in the MNP aggregation process. Moreover, to investigate the toxicological potential of MNPs, a mussel species (M. galloprovincialis) was exposed to different concentrations of MPs and NPs, separately, with and without the technology. In this context, mussels were sampled after 7, 14, and 21 days of exposure, and the gills and digestive glands were collected for analysis of oxidative stress biomarkers and histological observations. In general, the results indicate that MNPs trigger the production of reactive oxygen species (ROS) in mussels and induce oxidative stress, making gills the most affected organ. Yet, when the technology was applied in moderate concentrations, NPs showed adverse effects in mussels. The histological analysis showed no evidence of MNPs in the gill’s tissues.

Cid-Samamed, Antonio (ORCID:0000000205073394)↗
DOE OSTI2017

Constraining Formation Models of Binary Black Holes with Gravitational-wave Observations

Gravitational waves (GWs) from binary black hole (BBH) mergers provide a new probe of massive-star evolution and the formation channels of binary compact objects. By coupling the growing sample of BBH systems with population synthesis models, we can begin to constrain the parameters of such models and glean unprecedented knowledge about the inherent physical processes that underpin binary stellar evolution. In this study, we apply a hierarchical Bayesian model to mass measurements from a synthetic GW sample to constrain the physical prescriptions in population models and the relative fraction of systems generated from various channels. We employ population models of two canonical formation scenarios in our analysis—isolated binary evolution involving a common-envelope phase and dynamical formation within globular clusters—with model variations for different black hole natal kick prescriptions. We show that solely with chirp mass measurements, it is possible to constrain natal kick prescriptions and the relative fraction of systems originating from each formation channel with O(100) of confident detections. This framework can be extended to include additional formation scenarios, model parameters, and measured properties of the compact binary.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins

This repository of global hydrogeologic datasets contains aquifer properties on 0.5° scale, including depth to groundwater (Fan et al., 2013), aquifer thickness (de Graaf et al., 2015), WHYMap aquifer classes (Richts et al., 2011), porosity and permeability (Gleeson et al., 2014), digitized and geo-processed from their respective sources. Globally gridded aquifer properties could be used independently to estimate global groundwater availability or used as critical inputs to the superwell model to simulate groundwater extraction and provide estimates of pumped volumes and unit costs under user-specific scenarios. Key resources related to this data are: Niazi, H., Ferencz, S., Graham, N., Yoon, J., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024; In-prep). Long-term Hydro-economic Assessment Tool for Evaluating Global Groundwater Cost and Supply: Superwell v1. Geoscientific Model Development. superwell model repository which uses this data to simulate groundwater extraction and provides estimates of the global extractable volumes and unit-costs ($/km3) of accessible groundwater production under user-specified extraction scenarios. Repository Overview Main output: aquifer_properties.csv contains all processed outputs, including aquifer properties like porosity, permeability, aquifer thickness, and depth to groundwater. shapefiles.zip: contains all digitized GIS databases and shapefile for all aquifer properties prep_inputs.R: R script that processes the shapefiles to produce the aquifer_properties file plot_inputs.R: R script for plotting the maps and conducting preliminary analysis on the available groundwater volume basin_to_country_mapping.csv, basin_country_region_mapping.csv and continent_county_mapping.csv provide the mapping between continents, 32 energy-economic macro regions, countries, and water basins for post-processing aquifer_properties.csv Maps: Each map visualizes the spatial distribution of one of the aquifer properties across the globe map_in_Porosity.png map_in_Permeability.png map_in_Aquifer_thickness.png map_in_Depth_to_water.png map_in_Grid_area_km.png map_in_WHYClass.png Sample inputs sample_inputs.py: this script samples inputs from the aquifer_properties dataset, ensuring the sampled and original inputs maintain the same distributions sampled_data_100.csv contains 100 sampled data points and sampled_data_100.png compares their distributions Dataset Overview The main outputs are consolidated in a comprehensive aquifer_properties.csv file and include the following fields: GridCellID: Unique identifier for each (roughly 0.5°) grid cell Continent: Continent name Country: Country name GCAM_basin_ID: Identifier for GCAM hydrologic basin Basin_long_name: Full name of the basin WHYClass: Hydrogeologic classification based on WHYMap aquifer classes (Richts et al., 2011) Porosity: Soil porosity (%) (Gleeson et al., 2014) Permeability: Soil permeability (in square meters; Gleeson et al., 2014) Aquifer_thickness: Thickness of the aquifer (in meters; de Graaf et al., 2015) Depth_to_water: Depth to groundwater (in meters; Fan et al., 2013) Grid_area: Area of the grid cell (in square meters) Key References The datasets are digitized versions of global hydrogeologic properties from the following key literature sources: Depth to Groundwater: Fan, Y., Li, H., & Miguez-Macho, G. (2013). Global Patterns of Groundwater Table Depth. Science, 339(6122), 940-943. https://doi.org/10.1126/science.1229881 Aquifer Thickness: de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., & Bierkens, M. F. P. (2015). A high-resolution global-scale groundwater model. Hydrol. Earth Syst. Sci., 19(2), 823-837. https://doi.org/10.5194/hess-19-823-2015 Porosity and Permeability: Gleeson, T., Moosdorf, N., Hartmann, J., & van Beek, L. P. H. (2014). A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891-3898. https://doi.org/10.1002/2014GL059856 Aquifer classes: Richts, A., Struckmeier, W. F., & Zaepke, M. (2011). WHYMAP and the Groundwater Resources Map of the World 1:25,000,000. In J. A. A. Jones (Ed.), Sustaining Groundwater Resources: A Critical Element in the Global Water Crisis (pp. 159-173). Springer Netherlands. https://doi.org/10.1007/978-90-481-3426-7_10 Cite as Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MSD-LIVE Data Repository. https://doi.org/10.57931/2307831 Contact Reach out to Hassan Niazi or open an issue in superwell repository for questions or suggestions.

aquifer thickness↗
DOE OSTI2025

Evaluation of a high-throughput method for processing sponge-stick samples to detect viable, non-spore-forming biothreat agents

After a bioterrorism incident, surface sampling is often used to determine the extent of contamination and exposure, guiding decontamination efforts and decisions for re-occupancy of affected sites. The sponge-stick (SS) is a preferred and commonly used device for sample collection to detect both spore-forming and non-spore-forming biothreat agents from non-porous surfaces. Here, in this study, a recently developed high-throughput method (HTM) for processing SS samples to detect viable Bacillus anthracis spores was adapted for detection of non-spore-forming biothreat agents, Yersinia pestis and Francisella tularensis. The scalable HTM was used to process up to 20 SS samples simultaneously, compared to the current stomacher-based method which processes one SS at a time. Comparisons of the HTM and the stomacher-based method were statistically indistinguishable for most experiments (P > 0.05) with HTM recoveries of 37–60 % for Y. pestis inoculated at 102–103 cells/SS and held 48 h at 4 °C to mimic sample transport/storage. The HTM was integrated with Rapid Viability-Polymerase Chain Reaction (RV-PCR) analysis to detect viable Y. pestis in the presence of particulate contamination (Arizona Test Dust, ATD). This approach detected Y. pestis inoculated at 20 cells/SS and ATD did not impact detection (P > 0.05). F. tularensis showed significantly lower recoveries between no-hold time and 48-h hold time (4 °C, P < 0.05) using the HTM, which further testing showed could be due to toxicity of the neutralizing buffer used for SS pre-wetting. With modifications, this method could enhance throughput capacity while maintaining similar recovery efficiencies to current methods for other non-spore-forming bacterial pathogens.

Biological and medical sciences↗
DOE OSTI2019

Hydrogen Generation Rates for Saltstone Related Samples with Tank 50 Waste Grout and Glycoate Using Sealed Reactors

This report documents the results of sealed reactor tests to measure the hydrogen generation rate (HGR) from Tank 50 waste, which may be on the order of 3 x 10 -9 (ft 3 /h)/gal. Because the estimated HGR limit of detection (LOD) for an open, continuous flow system is approximately 6 x 10 -8 (ft 3 /h)/gal a more sensitive method was needed. By accumulating generated gases in a sealed system without a continuous purge gas, the resulting concentrations can increase the sensitivity of measurement, which is based on duration of heating. Prior sealed-reactor testing demonstrated measurements down to 7 x 10 -10 (ft 3 /h)/gal. In 2017, Savannah River Remediation, LLC (SRR) declared a Potential Inadequacy in the Safety Analysis (PISA) for the Saltstone Production Facility (SPF), among other facilities. The research for this report concerns waste from Tank 50 which is processed through SPF to produce saltstone. Previous studies examined the thermolysis of Tank 50 waste mixed with small individual amounts of saltstone grout premix additives, as well as glycolate. In contrast, the current study evaluated the impact of Tank 50 waste containing glycolate and stabilized within saltstone, on the generation of flammable gases, specifically hydrogen. The task included holding at target temperatures Tank 50 samples of salt solution in grout and spiked with 350 mg/L of glycolate to determine if the glycolate decomposes into H 2 . The measured hydrogen generation rates for radioactive saltstone monoliths over 28 days are: 2.0 x 10 -7 (ft 3 /h)/gal at 64-68°C, 1.4 x 10 -7 (ft 3 /h)/gal at 80-82°C, and 4.5 x 10 -7 (ft 3 /h)/gal at 112°C. Testing also included a non-radioactive salt simulant of Tank 50 waste, which was spiked with a concentration of glycolate expected in Savannah River Site (SRS) low-level waste, after the waste is solidified in grout. Included in the simulant tests was using grout made with two different surface areas, a monolith form with only the upper surface exposed and a pellet, or cube, form to increase the exposed surface area, to demonstrate the importance of exposed area in H 2 generation.

08 HYDROGEN↗
DOE OSTI2018

Semi-Targeted Analysis of Complex Matrices by ESI FT-ICR MS or How an Experimental Bias may be Used as an Analytical Tool

Ammonia is well suited to favor deprotonation process in electrospray ionization mass spectrometry (ESI-MS) to increase the formation of [M – H]{sup –}. Nevertheless, NH{sub 3} may react with carbonyl compounds (aldehyde, ketone) and bias the composition description of the investigated sample. This is of significant importance in the study of complex mixture such as oil or bio-oil. To assess the ability of primary amines to form imines with carbonyl compounds during the ESI-MS process, two aldehydes (vanillin and cinnamaldehyde) and two ketones (butyrophenone and trihydroxyacetophenone) have been infused in an ESI source with ammonia and two different amines (aniline and 3-chloronaniline). The (+) ESI-MS analyses have demonstrated the formation of imine whatever the considered carbonyl compound and the used primary amine, the structure of which was extensively studied by tandem mass spectrometry. Thus, it has been established that the addition of ammonia, in the solution infused in an ESI source, may alter the composition description of a complex mixture and leads to misinterpretations due to the formation of imines. Nevertheless, this experimental bias can be used to identify the carbonyl compounds in a pyrolysis bio-oil. As we demonstrated, infusion of the bio-oil with 3-chloroaniline in ESI source leads to specifically derivatized carbonyl compounds. Thanks to their chlorine isotopic pattern and the high mass measurement accuracy, (+) ESI Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) unambiguously highlighted them from the numerous C{sub x}H{sub y}O{sub z} bio-oil components. These results offer a new perspective into the detailed molecular structure of complex mixtures such as bio-oils. .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Analysis of cathode geometry to minimize cathode erosion in direct current microplasma jet

Microplasma jets are now widely used for deposition, etching, and materials processing. The present study focuses on the investigation of the influence of cathode geometry on deposition quality, for microplasma jet deposition systems in low vacuum. The interest here is understanding the influence of hydrogen on sputtering and/or evaporation of the electrodes. Samples obtained with two cathode geometries with tapered and rectangular cross-sections have been investigated experimentally by scanning electron microscopy and energy dispersion X-ray spectroscopy. Samples obtained with a tapered-geometry cathode present heavy contamination, demonstrating cathode erosion, while samples obtained with a rectangular-cross-section cathode are free from contamination. These experimental characteristics were explained by modelling results showing a larger radial component of the electric field at the cathode inner wall of the tapered cathode. As a result, ion acceleration is larger, explaining the observed cathode erosion in this case. Results from the present investigation also show that the ratio of radial to axial field components is larger for the rectangular geometry case, thus, qualitatively explaining the presence of micro-hollow cathode discharge over a wide range of currents observed in this case. In the light of the above findings, the rectangular cathode geometry is considered to be more effective to achieve cleaner deposition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

An Analysis of Statewide Adoption Rates of Building Energy Code by Local Jurisdictions

The purpose of this study is to generally inform the U.S. Department of Energy’s Building Energy Codes Program of the local, effective energy code adoption rate for a sample set of 21 states, some which have adopted statewide codes and some that have not. Information related to the residential energy code adoption process and status at the local jurisdiction was examined for each of the states. Energy code status information was gathered for approximately 2,800 jurisdictions, which effectively covered approximately 80 percent of the new residential building construction in the 21 states included in the study.

Building Energy Codes↗