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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Spectroscopic Signatures of MQ-Resins in Silicone Elastomers

Polysiloxane elastomers have a large application space due to their versatile cross-linking chemistry and highly tunable physical and mechanical properties. One approach for improving the mechanical integrity of commercial polysiloxane “silicone” elastomers while maintaining their optical transparency is the addition of small, silicone-resin molecules to the network. However, both the poly(dimethylsiloxane) (PDMS) network and the silicone-resin particles have an amorphous structure and complex chemistry, which makes the characterization of their structural properties and segmental network dynamics difficult. Here, we report the synthesis and characterization of a series of model silicone networks modified with a specific class of silicone-resin known as MQ-resin using Raman and advanced nuclear magnetic resonance (NMR) spectroscopy methods. Raman spectroscopy was successfully used to quantify the contribution of the MQ-resin to the network, to determine the type of MQ-resin present in the network, and to investigate the completeness of the network cross-linking reaction. Furthermore, solid-state and 1H double-quantum (DQ) NMR spectroscopies were used not only as a detection method for the MQ-resins but also to quantify changes in the segmental dynamics of the network as a function of MQ-resin concentration. The combination of Raman and NMR spectroscopies describes a series of samples where the MQ-resin particles and PDMS chains maintain their independent segmental dynamics up to high concentrations of MQ-resins (40–50% MQ), where the physical properties of the resin dominate the physical properties of the overall network. The results from our spectroscopic analyses are consistent with the results from macroscopic characterization techniques such as solvent uptake and mechanical testing. The spectroscopic insights into the structure–property relationships of PDMS-MQ composites presented in this study are a valuable tool not only for the synthesis and reverse engineering of future generations of commercial silicone elastomers but also for understanding the mechanisms of aging and degradation over the material lifetime.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Influence of ambient gas on self-reversal in Li transitions relevant to isotopic analysis

Laser induced breakdown spectroscopy is a promising, rapid analysis method for the detection and quantification of Li and its isotopes needed in geochemical, nuclear, and energy storage applications. However, spectral broadening in laser produced plasmas, presence of fine and hyperfine structures, and self-reversal effects make Li isotopic analysis via laser induced breakdown spectroscopy challenging. The present study explores the influence of Ar, N 2 , and He ambient gases over the pressure range of 0.05 - 100 Torr on line broadening and self-reversal of the Li I transition with the greatest isotopic shift in the VIS spectral region (i.e., ≈670.8 nm, ≈15.8 pm isotopic shift). We perform spatially and temporally resolved optical emission spectroscopy of plasmas produced via laser ablation of LiAlO 2 substrates. Our results show that the self-reversal and linewidth is reduced at lower pressures for all gases, and using optimized plasma conditions with chemometric methods, the 6 Li/ 7 Li isotopic ratios can be predicted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

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

Predissociation-based measurements of bond dissociation energies: US 2 , OUS, and USe

The uranium-containing molecules US 2 , OUS, and USe have been investigated using a pulsed laser ablation supersonic beam molecular source with time-of-flight mass spectrometric detection. Spectra have been recorded using the resonant two-photon ionization method over the spectroscopic range from 277 to 238 nm. These species have a myriad of excited electronic states in this spectroscopic region, leading to spectra that are highly congested and appear quasicontinuous. Sharp predissociation thresholds are observed, allowing precise bond dissociation energies to be measured. In the case of the triatomic molecules, it was necessary to use one laser for excitation and a delayed laser for ionization in order to observe a sharp predissociation threshold that allowed a precise bond dissociation energy to be measured. The resulting thermochemical values are D 0 (SU-S) = 4.910 ± 0.003 eV, D 0 (OU-S) = 5.035 ± 0.004 eV, and D 0 (USe) = 4.609 ± 0.009 eV. These results provide the first measurement of D 0 (USe) and reduce the error limits in the previous values of D 0 (SU-S) and D 0 (OU-S) by a factor of more than 70.

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

Mesoporous Fe-doped MgO nanoparticles as a heterogeneous photo-Fenton-like catalyst for degradation of salicylic acid in wastewater

Mesoporous Fe-doped MgO nanoparticles were synthesized using a facile sol-gel method and utilized for photo-Fenton-like degradation of salicylic acid (SA). The MgO surface dissolution facilitated an increase in the pH under the reaction conditions that allowed the Fe-MgO catalyst to be active without detectable iron leaching. Under simulated solar radiation, SA was completely degraded with an initial rate constant of 0.048 min -1 at the optimal reaction conditions of 500 ppm loading of 5% Fe-MgO, 20 mM H 2 O 2 concentration, and 50 ppm SA concentration. The catalyst was stable over 5 reaction cycles. The Fe-MgO catalyst was shown to have a surface area up to 171 m 2 /g and contain hematite (Fe 2 O 3 ) nanoparticles with octahedrally coordinated iron catalytic centers, as inferred from diffuse reflectance UV–vis measurements. Post-reaction catalyst characterization showed that some Fe 2+ was present in the catalyst due to the redox cycle during the chain initiation and propagation steps of the reaction.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Crystal Growth, Single Crystal Structure, and Biological Activity of Thiazolo-Pyridine Dicarboxylic Acid Derivatives

Four novel TPDCA derivatives were prepared via a supersaturation method combining TPDCA with water, N-methyl-2-pyrrolidone (NMP), Na(PO 2 H 2 ), and ammonia solution: 2(C 9 H 7 NO 5 S)H 2 O (1), (C 9 H 7 NO 5 S)C 5 H 9 NO (2), (C 9 H 7 NO 5 S)Na(PO 2 H 2 ) (3), and (C 9 H 5 NO 5 S)(NH 4 )2(H 2 O) (4). Their crystal structures were determined by single-crystal X-ray diffraction. Compounds (1) and (2) crystallize in the monoclinic space groups P2 1 and P2 1 /c, respectively, whereas compounds (3) and (4) crystallize in the triclinic space group P1 - . Weak and moderate hydrogen bonds were detected in the four compounds. In the biological tests, (1) and (3) exhibited significant antibacterial activity against Escherichia coli and Staphylococcus aureus; in addition, (1) was cytotoxic against leukemia HL-60 cells with the IC 50 value of 158.5 ± 12.5 μM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Automated Conflict Resolution For Air Traffic Control

The ability to detect and resolve conflicts automatically is considered to be an essential requirement for the next generation air traffic control system. While systems for automated conflict detection have been used operationally by controllers for more than 20 years, automated resolution systems have so far not reached the level of maturity required for operational deployment. Analytical models and algorithms for automated resolution have been traffic conditions to demonstrate that they can handle the complete spectrum of conflict situations encountered in actual operations. The resolution algorithm described in this paper was formulated to meet the performance requirements of the Automated Airspace Concept (AAC). The AAC, which was described in a recent paper [1], is a candidate for the next generation air traffic control system. The AAC's performance objectives are to increase safety and airspace capacity and to accommodate user preferences in flight operations to the greatest extent possible. In the AAC, resolution trajectories are generated by an automation system on the ground and sent to the aircraft autonomously via data link .The algorithm generating the trajectories must take into account the performance characteristics of the aircraft, the route structure of the airway system, and be capable of resolving all types of conflicts for properly equipped aircraft without requiring supervision and approval by a controller. Furthermore, the resolution trajectories should be compatible with the clearances, vectors and flight plan amendments that controllers customarily issue to pilots in resolving conflicts. The algorithm described herein, although formulated specifically to meet the needs of the AAC, provides a generic engine for resolving conflicts. Thus, it can be incorporated into any operational concept that requires a method for automated resolution, including concepts for autonomous air to air resolution.

Erzberger, Heinz↗
DOE OSTI2024

1. Physical Security Engineering by Design for Nuclear Facilities; 2. Nuclear Power Plant Site Security Management – A Security Strategy; 3. The UAE Women in Nuclear Energy Security

1. Security by design, or SeBD, is a comprehensive approach that integrates the physical protection system of a nuclear plant into every stage of its existence. This includes planning, designing, constructing, commissioning, and operating the facility, using a combination of analytical, physical, technological, and procedural measures. Essentially, SeBD involves intentionally applying and incorporating security into all aspects of design and operation throughout the entire lifecycle of a facility. By implementing this methodology throughout various phases such as program development, process implementation, staff training and procedures management in conjunction with plant equipment, facilities can be optimized to minimize security risks without compromising functional design requirements. This ultimately improves the overall security posture of the site and reduces the need for costly modifications or additional security resources post-design. 2. A site security strategy is a living document that is revised on a periodic or event-driven basis, ensuring that site security operations and corresponding procedures provide long-term, effective protection for the entire nuclear power plant (NPP) site. A site security strategy aims to mitigate threats across the entire NPP site via in-depth defense approaches and mutual support; therefore, if a layer is omitted or altered, then the effect across all layers must be re-evaluated. Therefore, the aim of the site security strategy is to provide an appropriate, scalable security regime that deters, denies, delays, and detects incidents and, equally importantly, reassures legitimate users and the regulator that due diligence and regulatory compliance have been achieved, ensuring that the site is safe and secure. Robust access control for vehicles and pedestrians is at the heart of the strategy. Vehicle and pedestrian searching and screening are seen as the strongest mitigation methods against vehicle- and pedestrian-borne attacks. The security strategy must also be supported through comprehensive staff training and the development of robust processes, procedures, and planning. If all these measures are to be effective, then training must be implemented during each phase of construction, partial operation/commissioning, and full operation. No single element of site security is completely isolated from the influence of other elements. Ideally, consideration of all key elements will result in a security strategy that is integrated and proportional to the threat and that does not over specify individual security solutions through the application of isolated measures but rather applies a holistic, all-encompassing approach. 3. When women enter the labor force, numerous positive outcomes emerge, including increased GDP, educational gains, and decreased maternal mortality. Despite these benefits, women's employment rates and equality vary significantly worldwide as does support for women in the workforce. This paper will explore the multifaceted benefits of women's employment, the factors influencing labor force participation rates, and the urgency to achieve gender equality as outlined in the 2015 United Nations Sustainable Development Goals (SDGs). It will then examine the emerging presence of women in the traditionally male-dominated nuclear field, specifically within the United Arab Emirates (UAE) as a testament to their resilience and determination to break social norms and advance gender equality.

Zineddin, Dr. Z.↗
DOE OSTI2025

Removal of Homogeneous Broadening from 1 H-Detected Multidimensional Solid-State NMR Spectra

1 H-detected magic-angle spinning (MAS) NMR experiments have revolutionized the NMR studies of biological and inorganic solids by providing unparalleled sensitivity and resolution. Despite these gains, homogeneous broadening, originating from the incomplete removal of homonuclear dipolar interactions under fast MAS, remains highly prevalent and limits the achievable resolution. In direct analogy to super-resolution microscopy methods, we show that resolution beyond that currently achievable by fast MAS alone can be obtained by experiment-driven deconvolution. Following the acquisition of a single 2D NMR spectrum to measure the frequency-dependent homogeneous lineshapes, any number of 1 H-detected spectra can be enhanced in resolution, yielding comparable spectra as obtained with twice the MAS frequency. In conclusion, the versatility of this approach is demonstrated in the enhancement of single- and double-quantum homonuclear correlation spectra, in addition to heteronuclear correlation spectra acquired on a surface organometallic complex and the protein GB1.

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

Operando High-Energy-Resolution X-ray Spectroscopy of Evolving Cu Nanoparticle Electrocatalysts for CO 2 Reduction

Advances in electrocatalysis research rely heavily on building a thorough mechanistic understanding of catalyst active sites under realistic operating conditions. Only recently have techniques emerged that enable sensitive spectroscopic data collection to distinguish catalytically relevant surface sites from the underlying bulk material under applied potential in the presence of an electrolyte layer. Here, we demonstrate that operando high-energy-resolution fluorescence detected X-ray absorption spectroscopy (HERFD-XAS) is a powerful spectroscopic method which offers critical surface chemistry insights in CO 2 electroreduction with sub-electronvolt energy resolution using hard X-rays. Combined with the high surface area-to-volume ratio of 5 nm copper nanoparticles, operando HERFD-XAS allows us to observe with clear evidence the breaking of chemical bonds between the ligands and the Cu surface as part of the ligand desorption process occurring under electrochemical potentials relevant for the CO 2 reduction reaction (CO 2 RR). In addition, the dynamic evolution of oxidation state and coordination number throughout the operation of the nanocatalyst was continuously tracked. With these results in hand, undercoordinated metallic copper nanograins are proposed to be the real active sites in the CO 2 RR. In conclusion, this work emphasizes the importance of HERFD-XAS compared to routine XAS in catalyst characterization and mechanism exploration, especially in the complicated electrochemical CO 2 RR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Spontaneous Raman–LIF–CO–OH measurements of species concentration in turbulent spray flames

This paper presents new measurements of species concentrations, temperature and mixture fraction in selected regions of a turbulent ethanol spray flame. The line-Raman–LIF–COsingle bondOH setup developed at the Sandia's Combustion Research Facility is utilised to probe regions of a spray flame where laser breakdown of liquid droplets is avoided and the remaining interferences can be corrected. The spray flame is stabilised on the piloted Sydney needle spray burner, where axial translation of the liquid injecting needle in the air-blast stream can transition the spray from dilute to dense. The solution to obtaining successful measurements is found to be multifaceted and includes: the appropriate selection of flame conditions; high sensitivity of the Raman detection system permitting reduced laser energies; development of a pre-processing algorithm to reject strong droplet interferences; and application of the hybrid matrix inversion method combined with wavelet denoising to account for interference corrections and noise at the very low signal levels obtained. Unique and necessary for the successful measurements reported in this paper, a pre-processing algorithm is outlined that removes data points corrupted with strong interferences from droplets. These interferences arise from a range of sources, but the most intense are due to the laser interaction with surrounding mist or liquid fragments, such that measurements near the jet centreline are corrupted and hence discarded. Reliable measurements of mixture fraction, temperature obtained from the sum of the species number densities, and species mole fractions are reported for regions in the flames sufficiently far from the centreline. The paper demonstrates the feasibility of the judicious use of Raman scattering in turbulent spray flames, the results of which will be extremely useful for validating numerical simulations.

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

Effect of Ligand Chemistry on the Electronic Properties and Reactivity of Cobalt Acetate Autoxidation Catalysts

Autoxidation chemistry catalyzed by cobalt(II) acetate is an industrial pathway for converting hydrocarbons into oxygenated compounds and has promising potential applications in plastic waste deconstruction. However, the chemical properties of the Co acetate-based catalysts and their roles in the reaction mechanism are poorly understood, and as a result, attempts to redesign the autoxidation chemical process for novel applications lack clear direction. In this work, we investigate the structure and electronic properties of a series of multinuclear Co(III) compounds that have been proposed as active participants in catalytic autoxidation. Through a combination of X-ray spectroscopic measurements [Co K-edge X-ray absorption spectroscopy (XAS), extended X-ray absorption fine structure (EXAFS), Kβ X-ray emission spectroscopy (XES), and high-energy resolution fluorescence detection (HERFD) XAS] and theoretical methods, we characterize the interactions of Co with acetate and hydroxyl ligands in these compounds. Here we show that the substitution of acetate ligands with hydroxyls in these compounds causes an increase in the electron density on Co, driven by the loss of a π back-bonding interaction between Co and acetate and an increase in electron donation to Co from the hydroxyl ligands. We further classify the bonding between Co and acetate based on the orbital overlap and show that the experimental absorption and emission spectra are well-described by the resulting molecular orbitals. Finally, we predict the impacts of acetate/hydroxyl ligand exchange on autoxidation catalytic properties, showing that the reaction free energies for key Co oxidation and reduction steps are extremely sensitive to metal-ligand bonding interactions and thus have meaningful impacts on overall reactivity. The results of this study constitute an important set of design criteria for developing novel homogeneous autoxidation catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Tracing priming effects in palsa peat carbon dynamics using a stable isotope-assisted metabolomics approach

Introduction: Peatlands store up to a third of global soil carbon, and in high latitudes their litter inputs are increasing and changing in composition under climate change. Although litter significantly influences peatland carbon and nutrient dynamics by changing the overall lability of peatland organic matter, the physicochemical mechanisms of this impact—and thus its full scope—remain poorly understood. Methods: We applied multimodal metabolomics (UPLC-HRMS, 1 H NMR) paired with 13 C Stable Isotope-Assisted Metabolomics (SIAM) to track litter carbon and its potential priming effects on both existing soil organic matter and carbon gas emissions. Through this approach, we achieved molecule-specific tracking of carbon transformations at unprecedented detail. Results: Our analysis revealed several key findings about carbon dynamics in palsa peat. Microbes responded rapidly to litter addition, producing a short-term increase in CO 2 emissions, fueled nearly exclusively by transformations of litter carbon. Litter inputs significantly contributed to the organic nitrogen pool through amino acids and peptide derivatives, which served as readily accessible nutrient sources for microbial communities. We traced the fate of plant-derived polyphenols including flavonoids like rutin, finding evidence of their degradation through heterocyclic C-ring fission, while accumulation of some polyphenols suggested their role in limiting overall decomposition. The SIAM approach detected subtle molecular changes indicating minimal and transient priming activity that was undetectable through conventional gas measurements alone. This transient response was characterized by brief microbial stimulation followed by rapid return to baseline metabolism. Pre-existing peat organic matter remained relatively stable; significant priming of its consumption was not observed, nor was its structural alteration. Discussion: This suggests that while litter inputs temporarily increase CO 2 emissions, they don’t sustain long-term acceleration of stored carbon decomposition or substantially decrease peat’s carbon store capacity. Our findings demonstrate how technological advancements in analytical tools can provide a more detailed view of carbon cycling processes in complex soil systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Atomistic‐Level Effects of Noncovalent Interactions and Crystalline Packing for Organic Material Structural Integrity upon Exposure to Gamma Radiation

Developing an atomistic understanding of ionizing radiation induced changes to organic materials is necessary for intentional design of greener and more sustainable materials for radiation shielding and detection. Cocrystals are promising for these purposes, but a detailed understanding of how the specific intermolecular interactions within the lattice upon exposure to radiation affect the structural stability of the organic crystalline material is unknown. This study evaluates atomistic-level effects of γ radiation on both single- and multicomponent organic crystalline materials and how specific noncovalent interactions and packing within the crystalline lattice enhance structural stability. Dose studies were performed on all crystalline systems and evaluated via experimental and computational methods. Changes in crystallinity were evaluated by p-XRD and free radical formation was analyzed via EPR spectroscopy. Type of intermolecular interactions and packing within the crystal lattice was delineated and related to the specific free radical species formed and the structural integrity of each material. Periodic DFT and HOMO-LUMO surface mapping calculations provided atomistic-level identifications of the most probable sites for the radicals formed upon exposure to γ radiation and relate intermolecular interactions and molecular packing within the crystalline lattice to experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Deep Learning enabled spectral energy conversion for in situ exposure measurements

A detector-specific deep learning (DL) approach is presented for spectra-to-exposure conversion using large-format sodium iodide (NaI(Tl)) detectors deployed for in situ environmental radiation measurements in emergency response scenarios. Accurate determination of exposure from NaI spectra is challenging due to poor energy resolution, partial energy absorption, and the strong sensitivity of traditionally deployed analytical conversion methods to calibrated source geometry and pre-deployment assumptions. Here, to address these limitations, a multi-layer perceptron model was trained on a hybrid in situ /Monte Carlo dataset constructed to span a broad range of photon energies, spatial extents, and realistic deployment variability, representative of general in situ emergency response conditions. The DL model was evaluated against commonly fielded analytical approaches under matched simulation conditions, including a single-factor method, a G-function method, and a modeled pressurized ion chamber (PIC) baseline. This study was intentionally computational in scope to enable controlled, like-for-like comparisons between conversion techniques while minimizing confounding real-world variability. Comparison to the modeled PIC provides contextual benchmarking and is not intended as a field inter-comparison with deployed instruments. Across the evaluated 20 keV to 3 MeV energy range, the DL approach consistently exhibited higher accuracy and reduced variance relative to the analytical methods against a deterministically calculated exposure. This may indicate improved robustness to spectral complexity without reliance on source-, geometric-, or spectral region-specific optimization. While results do not represent real-world validation, the presented work demonstrates that deep learning may effectively learn the nonlinear detector response-to-exposure relationship for asymmetric NaI(Tl) detectors and offers a promising pathway for improving in situ exposure estimation using spectroscopic systems already integrated into initial real-time emergency response operations.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2010

Carbon Isotope Characterization of Organic Intermediaries in Hydrothermal Hydrocarbon Synthesis by Pyrolysis-GC-MS-C-IRMS

We report results of experiments designed to characterize the carbon isotope composition of intermediate organic compounds produced as a result of mineral surface catalyzed reactions. The impetus for this work stems from recently reported detection of methane in the Martian atmosphere coupled with evidence showing extensive water-rock interaction during Martian history. Abiotic formation by Fischer-Tropsch-type (FTT) synthesis during serpentinization reactions may be one possible process responsible for methane generation on Mars, and measurement of carbon and hydrogen isotopes of intermediary organic compounds can help constrain the origin of this methane. Of particular interest within the context of this work is the isotopic composition of organic intermediaries produced on the surfaces of mineral catalysts (i.e. magnetite) during hydrothermal experiments, and the ability to make meaningful and reproducible isotope measurements. Our isotope measurements utilize a unique analytical technique combining Pyrolysis-Gas Chromatograph-Mass Spectrometry-Combustion-Isotope Ratio Mass Specrometry (Py-GC-MS-C-IRMS). Others have conducted similar pyrolysis-IRMS experiments on low molecular weight organic acids (Dias, et al, Organic Geochemistry, 33 [2002]). Our technique differs in that it carries a split of the pyrolyzed GC-separated product to a Thermo DSQ-II quadrupole mass spectrometer as a means of making qualitative and semi-quantitative compositional measurements of the organic compounds. A sample of carboxylic acid (mixture of C1 through C6) was pyrolyzed at 100 XC and passed through the GC-MS-C-IRMS (combusted at 940 XC). In order to test the reliability of our technique we compared the _13C composition of different molecular weight organic acids (from C1 through C6) extracted individually by the traditional sealed-tube cupric oxide combustion (940 XC) method with the _13C produced by our pyrolysis technique. Our data indicate that an average 4.3. +/-0.5. (V-PDB) apparent isotopic fractionation accompanies the pyrolysis extractions. We postulate that this isotope offset could be the result of incomplete thermal desorption during pyrolysis. We are continuing to investigate the reliability of this pyrolysis technique for correcting carbon isotope measurements of mineral surface catalyzed organic compounds.

Socki, Richard A.↗
DOE OSTI2023

Practical benzylation of N,N -substituted ethanolamines related to chemical warfare agents for analysis and detection by Electron Ionization Gas Chromatography-Mass Spectrometry

The benzylation of three, low-molecular weight N,N-disubstituted ethanolamines related to chemical warfare agents (CWAs) to furnish derivatives with improved Gas Chromatography-Mass Spectrometry (GC-MS) profiles is described. Due to their low molecular weight and polar nature, N,N-disubstituted ethanolamines are notoriously difficult to detect by routine GC-MS analyses during Organisation for the Prohibition of Chemical Weapons (OPCW) proficiency tests (PTs), particularly in scenarios when they are present at low levels (~1-10 ppm) amidst more abundant interferences. Our studies revealed that the optimal derivatization conditions involved the treatment of the ethanolamine with benzyl bromide in the presence of an inorganic base (e.g., Na 2 CO 3 ) in dichloromethane at 55 °C for 2 hours. This optimized set of conditions were then successfully applied to the derivatization of N,N-dimethylethanolamine, N,N-diethylethanolamine and N,N-diisopropylethanolamine present separately at 1 and 10 μg/mL concentrations in a glycerol-rich matrix sample featured in the 48 th OPCW PT. The benzylated derivatives of the three ethanolamines possessed retention times long enough to clear the massive glycerol-containing matrix interferences. In conclusion, the protocol herein is introduced as an alternative method for derivatization of these CWA and pharmaceutically important species and should find broad applicability in laboratories where their routine forensic analysis is carried out.

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

A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data

The detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detection times and a high rate of false positives pose a significant hindrance in the deployment of PGAA-based systems to identify the presence of illicit substances in nuclear forensics. In the present work, six different machine-learning algorithms were developed to classify radioactive elements based on the PGAA energy spectra. The model performance was evaluated using standard classification metrics and trend curves with an emphasis on comparing the effectiveness of algorithms that are best suited for classifying imbalanced datasets. We analyse the classification performance based on Precision, Recall, F1-score, Specificity, Confusion matrix, ROC-AUC curves, and Geometric Mean Score (GMS) measures. The tree-based algorithms (Decision Trees, Random Forest and AdaBoost) have consistently outperformed Support Vector Machine and K-Nearest Neighbours. Based on the results presented, AdaBoost is the preferred classifier to analyse data containing PGAA spectral information due to the high recall and minimal false negatives reported in the minority class.

97 MATHEMATICS AND COMPUTING↗