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Chemical and structural characterization of particulate fallout isolated from air-filters

We report particulate nuclear fallout is the radioactive byproduct of a nuclear event formed by the mixture of proximate environmental materials with vaporized bomb debris. The fallout debris can be transported into the atmosphere during cloud rise, raining out locally and dispersing globally constituting a radiation hazard and contributing to the distribution of anthropogenic radionuclides in the environment. Questions remain on how entrainment of environmental material in the fireball affects fallout formation processes and radionuclide incorporation and distribution during cooling. To inform the characterization of fallout including the development of fallout size distributions and how radionuclides are incorporated into fallout debris where entrainment plays a role, we analyzed an archived historic US air-filter collected by aircraft in the aftermath of ground interacting nuclear tests. Particulate fallout collected on the filter was isolated and analyzed using scanning electron microscopy (SEM), transmission electron microscopy (TEM) and NanoSIMS (Secondary Ion Mass Spectrometry) to determine chemistry, structure, morphology, and size of the particles. Results demonstrate that the particles isolated from the filter have spherical shape, display complex internal structures, and are mainly composed of Fe and Si oxides. In these spherical particles, Pu is preferentially associated with Fe-rich composition. The characterization of fallout particulate samples can provide information on nucleation and particle growth from the vapor phase to improve modeling and simulation of fallout hazards.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Y-12 National Security Complex Biological Monitoring and Abatement Program—2024 Calendar Year Report

This report provides the results of the CY 2024 sampling of East Fork Poplar Creek (EFPC) as part of the Y-12 National Security Complex (Y-12) Biological Monitoring and Abatement Program (BMAP). The results are presented in the context of historical trends. The Y-12 BMAP was developed in 1985 to demonstrate that the effluent limits established for Y-12 protected the classified uses of the receiving stream, particularly the growth and propagation of aquatic life (Loar et al. 1989). Over the years, the BMAP has become an important and valuable long-term measure of stream conditions resulting from actions and activities at the Y-12 Complex. The BMAP currently consists of three tasks: (1) bioaccumulation monitoring, (2) benthic macroinvertebrate community monitoring, and (3) fish community monitoring. The benthic macroinvertebrate community monitoring task includes studies to evaluate the receiving stream’s biological integrity annually in comparison with Tennessee Water Quality Criteria following Tennessee Department of Environment and Conservation (TDEC) protocols. In addition to presenting the EFPC biological monitoring results, this report includes results from Comprehensive Environmental Response, Compensation, and Liability Act–funded BMAP programs in Bear Creek and McCoy Branch (presented in Appendixes A and B, respectively), as required in the Y-12 National Pollutant Discharge Elimination System (NPDES) permit. Additional biological testing at the Y-12 Complex includes toxicity testing of select storm drains as required in the NPDES permit. Although toxicity testing is not formally part of the BMAP, toxicity testing results from 2024 are provided in Appendix C.

54 ENVIRONMENTAL SCIENCES↗

ARM Aerial Facility (AAF) Merged Value-Added Product Report for Historical G-1 Field Campaigns

For 30 years, the U.S. Department of Energy (DOE) Office of Science supported an instrumented Grumman Gulfstream-1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) user facility Data Center (ADC) and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated data set was recently developed covering the final six years of G-1 operations (2013 to 2018). The integrated data set includes data collected from 236 flights (766.4 hours). Four of the seven field campaigns were based in the U.S. One campaign collected data from the wildfires in the U.S. Pacific Northwest and agricultural burns in the lower Mississippi River valley as part of the Biomass Burning Observation Project (BBOP) in 2013. In 2015, the ARM Cloud Aerosol Precipitation Experiment provided data on atmospheric rivers and associated aerosol-cloud interactions that produce heavy precipitation on the U.S. west coast during the early spring. Research data from Airborne Carbon Measurements-V (ACME-V), collected during the summer of 2015, gave scientists insight into trends and variability of trace gases in the atmosphere over the North Slope of Alaska to improve arctic climate models. In the early summer and autumn of 2016, the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign provided an extensive data set geared toward coupled processes that affect the life cycle of shallow clouds through the interaction among aerosol, cloud, land surface, and ecosystems. In 2014 (March and October), the airborne sampling moved outside of the U.S. to the city of Manaus in central Amazonia, Brazil, where residential and industrial emissions were extensively characterized by flights of the G-1. The GoAmazon2014/15 aircraft campaign data are being integrated with aquatic and terrestrial ecosystem measurements to quantify anthropogenic perturbations to a usually pristine tropical environment. Another international airborne mission was carried out in the Eastern North Atlantic region. The Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign saw the G-1 aircraft fly from Terceira Island in the Azores during the summer of 2017 and the winter of 2018. The campaign studied both seasons to measure key aerosol and cloud processes under various meteorological and cloud conditions with different aerosol sources. Then the G-1 deployed to the Sierras de Córdoba range in central Argentina from October to November 2018 for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign to study orographic convective cloud interactions with their surrounding environment. These comprehensive datastreams provide much-needed insight into spatiotemporal variability of thermodynamic quantities, aerosol and cloud states, and properties for addressing essential science questions in Earth system process studies.

54 ENVIRONMENTAL SCIENCES↗

ARM Aerial Facility (AAF) Merged Value-Added Product Report for Historical G-1 Field Campaigns

For 30 years, the U.S. Department of Energy (DOE) Office of Science supported an instrumented Grumman Gulfstream-1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) user facility Data Center (ADC) and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated data set was recently developed covering the final six years of G-1 operations (2013 to 2018). The integrated data set includes data collected from 236 flights (766.4 hours). Four of the seven field campaigns were based in the U.S. One campaign collected data from the wildfires in the U.S. Pacific Northwest and agricultural burns in the lower Mississippi River valley as part of the Biomass Burning Observation Project (BBOP) in 2013. In 2015, the ARM Cloud Aerosol Precipitation Experiment provided data on atmospheric rivers and associated aerosol-cloud interactions that produce heavy precipitation on the U.S. west coast during the early spring. Research data from Airborne Carbon Measurements-V (ACME-V), collected during the summer of 2015, gave scientists insight into trends and variability of trace gases in the atmosphere over the North Slope of Alaska to improve arctic climate models. In the early summer and autumn of 2016, the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign provided an extensive data set geared toward coupled processes that affect the life cycle of shallow clouds through the interaction among aerosol, cloud, land surface, and ecosystems. In 2014 (March and October), the airborne sampling moved outside of the U.S. to the city of Manaus in central Amazonia, Brazil, where residential and industrial emissions were extensively characterized by flights of the G-1. The GoAmazon2014/15 aircraft campaign data are being integrated with aquatic and terrestrial ecosystem measurements to quantify anthropogenic perturbations to a usually pristine tropical environment. Another international airborne mission was carried out in the Eastern North Atlantic region. The Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign saw the G-1 aircraft fly from Terceira Island in the Azores during the summer of 2017 and the winter of 2018. The campaign studied both seasons to measure key aerosol and cloud processes under various meteorological and cloud conditions with different aerosol sources. Then the G-1 deployed to the Sierras de Córdoba range in central Argentina from October to November 2018 for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign to study orographic convective cloud interactions with their surrounding environment. These comprehensive datastreams provide much-needed insight into spatiotemporal variability of thermodynamic quantities, aerosol and cloud states, and properties for addressing essential science questions in Earth system process studies.

54 ENVIRONMENTAL SCIENCES↗

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗

Impact of UV-light and pH on the Fate of Tc, I, and U in Wetlands at Savannah River Site - 20230

The Savannah River Site (SRS) is one of the major nuclear facilities owned by the U.S Department of Energy. During the Cold War, these facilities produced large amounts of radioactive and hazardous waste. On site, three unlined seepage basins in the F-Area received approximately 1.8 billion gallons of low-level waste containing nitric acid, radionuclides, and dissolved metals due to plutonium and tritium production operations. The acidic nature of the waste created a source of relatively mobile radionuclides below the basins. Radionuclides previously disposed of within the F-Area, including uranium isotopes (U), technetium-99 (Tc-99), and iodine-129 (I-129), are moving with groundwater towards Four Mile Branch Wetland, where they are subsequently upwelling and interacting with natural organic matter (NOM). Many environmental factors including redox conditions, porewater composition, pH, light, and temperature affect the degradation of organic matter as well as interactions with Tc-99, U, and I-129. In particular, the high concentrations of nitrate from the acidic waste may increase the formation of reactive oxygen species (ROS) that impact both degradation of NOM and behavior of contaminants. In the presence of sunlight, I-129, Tc-99, and U speciation and complexation behavior may be affected by ROS and NOM degradation products in addition to the factors generally considered in subsurface systems in the absence of light. This research aims to determine whether the interactions between radionuclides, NOM, and nitrate affect the fate of I-129, Tc-99, and U and which processes are controlling their behavior. Experiments were conducted at variable pH in the presence of NaNO{sub 3} in order to determine the impact of light and pH on NOM degradation and to evaluate the impact on the fate of contaminants of concern. Soil samples high in NOM collected from two sites in the Southeastern United States (Savannah River Site and the Everglades) were studied. Batch experiments were conducted with NOM and the following aqueous contaminants, U, I-129, Tc-99 with exposure to ultraviolet (UV) light in an environmental chamber. This study was conducted in a sterile environment in order to exclude the potential for microbial degradation of organic matter. Results indicated photodegradation of NOM and significant interaction of radionuclides with NOM. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sparse optimization of two-dimensional terahertz spectroscopy

Two-dimensional terahertz spectroscopy (2DTS) is a low-frequency analog of two-dimensional optical spectroscopy that is rapidly maturing as a probe of a wide variety of condensed matter systems. However, a persistent problem with 2DTS is the long experimental acquisition times, which prevent its broader adoption. A potential solution, requiring no increase in experimental complexity, is signal reconstruction via compressive sensing. In this work, we apply the sparse exponential mode analysis (SEMA) technique to 2DTS of a cuprate superconductor. We benchmark the performance of the algorithm in reconstructing terahertz nonlinearities and find that SEMA reproduces the asymmetric photon echo line shapes at sampling rates as low as 10%, reaching the reconstruction noise floor at sampling rates beyond 20%–30%. The success of SEMA in reproducing such subtle, asymmetric line shapes confirms compressive sensing as a general method to accelerate 2DTS and multidimensional spectroscopies more broadly.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Priors on red galaxy stochasticity from hybrid effective field theory

ABSTRACT We investigate the stochastic properties of typical red galaxy samples in a controlled numerical environment. We use halo occupation distribution (HOD) modelling to create mock realizations of three separate bright red galaxy samples consistent with data sets used for clustering and lensing analyses in modern galaxy surveys. Second-order Hybrid Effective Field Theory (HEFT) is used as a field-level forward model to describe the full statistical distribution of these tracer samples, and their stochastic power spectra are directly measured and compared to the Poisson shot-noise prediction. While all of the galaxy samples we consider are hosted within haloes with sub-Poisson stochasticity, we observe that the galaxy samples themselves possess stochasticities that range from sub-Poisson to super-Poisson, in agreement with predictions from the halo model. As an application of our methodology, we place priors on the expected degree of non-Poisson stochasticity in cosmological analyses using such samples. We expect these priors will be useful in reducing the complexity of the full parameter space for future analyses using second-order Lagrangian bias models. More generally, the techniques outlined here present the first application of HEFT methods to characterize models of the galaxy–halo connection at the field level, revealing new connections between once-disparate modelling frameworks.

79 ASTRONOMY AND ASTROPHYSICS↗

Uranium (VI) Adsorbate Structures on Portlandite [Ca(OH)2] Type Surfaces Determined by Computational Modelling and X-ray Absorption Spectroscopy

Portlandite [Ca(OH) 2 ] is a potentially dominant solid phase in the high pH fluids expected within the cementitious engineered barriers of Geological Disposal Facilities (GDF). This study combined X-ray Absorption Spectroscopy with computational modelling in order to provide atomic-scale data which improves our understanding of how a critically important radionuclide (U) will be adsorbed onto this phase under conditions relevant to a GDF environment. Such data are fundamental for predicting radionuclide mass transfer. Surface coordination chemistry and speciation of uranium with portlandite [Ca(OH) 2 ] under alkaline groundwater conditions (ca. pH 12) were determined by both in situ and ex situ grazing incidence extended X-ray absorption fine structure analysis (EXAFS) and by computational modelling at the atomic level. Free energies of sorption of aqueous uranyl hydroxides, [UO 2 (OH) n ] 2–n (n = 0–5) with the (001), (100) and (203) or (101) surfaces of portlandite are predicted from the potential of mean force using classical molecular umbrella sampling simulation methods and the structural interactions are further explored using fully periodic density functional theory computations. Although uranyl is predicted to only weakly adsorb to the (001) and (100) clean surfaces, there should be significantly stronger interactions with the (203/101) surface or at hydroxyl vacancies, both prevalent under groundwater conditions. The uranyl surface complex is typically found to include four equatorially coordinated hydroxyl ligands, forming an inner-sphere sorbate by direct interaction of a uranyl oxygen with surface calcium ions in both the (001) and (203/101) cases. In contrast, on the (100) surface, uranyl is sorbed with its axis more parallel to the surface plane. The EXAFS data are largely consistent with a surface structural layer or film similar to calcium uranate, but also show distinct uranyl characteristics, with the uranyl ion exhibiting the classic dioxygenyl oxygens at 1.8 Å and between four and five equatorial oxygen atoms at distances between 2.28 and 2.35 Å from the central U absorber. These experimental data are wholly consistent with the adsorbate configuration predicted by the computational models. These findings suggest that, under the strongly alkaline conditions of a cementitious backfill engineered barrier, there would be significant uptake of uranyl by portlandite to inhibit the mobility of U(VI) from the near field of a geological disposal facility.

36 MATERIALS SCIENCE↗

A Framework to Demonstrate a DNP3 Interface With a CIM-Based Data Integration Platform: Preprint

The contemporary electrical grid is characterized by its complexity and abundance of data. A control-rich environment supported by information and communication technologies within an Advanced Distribution Management System (ADMS) presents a viable and cost-effective option for utility companies aiming to implement advanced real-time analytical schemes for monitoring and remotely controlling distribution feeders. Modular platform-based approaches to distribution operations require a structured framework for acquiring field device measurements, performing analytics, converting the setpoint to the correct protocol, and sending it on the appropriate communications network to the field devices. We present the development and deployment of an application service to integrate an open-source standardsbased platform with an ADMS test bed with field devices using the Distributed Network Protocol (DNP3) for data exchange. The step-by-step procedure for establishing the DNP3-Master service on an open-source distribution platform is outlined, comprehensively explaining the Master setup process. Moreover, sample use case results highlight the capabilities of the DNP3- Master service setup. Results demonstrate the scalability and configurability of the DNP3-Master service, making it adaptable for integration with other relevant applications, thus providing potential opportunities for real-world field trials and real-time assessments.

ADMS↗

An automated cluster surface scanning method for exploring reaction paths on metal-cluster surfaces

Metal-cluster surfaces present a wide variety of unique coordination environments. This complexity makes it difficult to manually probe the surface reactivity of such clusters. Here, we present a simple and automated method to systematically discover reaction pathways on cluster surfaces, based on the automated cluster surface scanning (ACSS) technique for mapping out potential energy surfaces. We showcase our method on 55-atom icosahedral Cu and Ag clusters, where we determine the activation energies of four elementary steps common in heterogeneous catalysis – hydrogen recombination (H* + H* → H 2 * + *), oxygen recombination (O* + O* → O 2 * + *), water formation (OH* + H* → H 2 O* + *), and CO oxidation (CO* + O* → CO 2 * + *) – with density functional theory calculations (DFT-PBE + D3). We show that the ACSS method requires significantly less human effort than the established manually performed climbing-image nudged elastic band (MP + CI-NEB) technique and locates transition states with comparable accuracy (root-mean-squared error of 0.10 eV) and similar computational cost. Rigorous sampling of the potential energy surface with the ACSS method allows one to locate all lowest-energy reaction pathways obtained via the MP+CI-NEB approach, as well as alternative pathways that one may have missed with the MP+CI-NEB approach due to the many possible pathways available on these clusters. The accuracy and efficiency afforded by the ACSS method could enable high-throughput exploration of the diverse reactivity of metal clusters.

36 MATERIALS SCIENCE↗

Interactions between macro‐ and micro‐climate: Effects on phenolic compound production in Nardus stricta at high elevations

Abstract Phenolic compounds are key to plant defence, offering protection as antioxidants, UV shields, and antimicrobials. Their production is largely shaped by environmental conditions. It is believed that plants at lower elevations increase phenolic content to counter herbivory, while those at higher elevations rely on phenolics to manage abiotic stresses, such as climate variability. Microhabitat warming also affects phenolic levels, but responses differ, depending on broader climatic contexts: plants in warmer, lower‐elevation environments show limited adaptability, whereas high‐elevation plants demonstrate greater plasticity. Despite the importance of these environmental interactions, many small‐scale abiotic studies lack sufficient spatial replication across broader gradients like elevation or latitude, while large‐scale studies frequently overlook microscale factors. This study investigated the effects of macroclimate factors and microhabitat warming on phenolic production in Nardus stricta across five semi‐natural grassland sites (1546–1875 m a.s.l.) in Portugal's Serra da Estrela. Warming was simulated using open‐top chambers over two growing seasons, after which leaf samples were analysed for phenolic compounds, and soil nutrients were measured. The N. stricta plants at the highest elevation site contained significantly higher leaf flavonoid concentrations. Microhabitat warming led to a significant decrease in flavonoid concentrations, but only at the highest elevation site. These effects occurred independently of soil nutrient levels, suggesting direct thermal effects or stress responses might be involved. Our findings highlight the complex interactions between macro‐ and microenvironmental factors in shaping plant chemistry, underscoring critical considerations for plant resilience in the face of climate change. This understanding is essential for developing strategies to support plant and ecosystem adaptation to changing climates.

Moreira, X. [Misión Biológica de Galicia (MBG‐CSIC↗

Crystallization of ApoA1 and ApoE4 Nanolipoprotein Particles and Initial XFEL-Based Structural Studies

Nanolipoprotein particles (NLPs), also called “nanodiscs”, are discoidal particles with a patch of lipid bilayer corralled by apolipoproteins. NLPs have long been of interest due to both their utility as membrane-model systems into which membrane proteins can be inserted and solubilized and their physiological role in lipid and cholesterol transport via high-density lipoprotein (HDL) and low-density lipoprotein (LDL) maturation, which are important for human health. Serial femtosecond crystallography (SFX) at X-ray free electron lasers (XFELs) is a powerful approach for structural biology of membrane proteins, which are traditionally difficult to crystallize as large single crystals capable of producing high-quality diffraction suitable for structure determination. To facilitate understanding of the specific role of two apolipoprotein/lipid complexes, ApoA1 and ApoE4, in lipid binding and HDL/LDL particle maturation dynamics, and to develop new SFX methods involving NLP membrane protein encapsulation, we have prepared and crystallized homogeneous populations of ApoA1 and ApoE4 NLPs. Crystallization of empty NLPs yields semi-ordered objects that appear crystalline and give highly anisotropic and diffuse X-ray diffraction, similar to fiber diffraction. Several unit cell parameters were approximately determined for both NLPs from these measurements. Thus, low-background, sample conservative methods of delivery are critical. Here we implemented a fixed target sample delivery scheme utilizing the Roadrunner fast-scanning system and ultra-thin polymer/graphene support films, providing a low-volume, low-background approach to membrane protein SFX. This study represents initial steps in obtaining structural information for ApoA1 and ApoE4 NLPs and developing this system as a supporting scaffold for future structural studies of membrane proteins crystalized in a native lipid environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microstructure modeling of nuclear structural materials: Recent progress and future directions

Modeling and simulation of microstructures are essential to understand the complex responses and behaviors of nuclear materials in extreme environments. The needs to assess the extended life operation as well as the growing interest in accelerating nuclear materials development and qualification have stimulated the use of high-fidelity multiscale models aided by empirical and ab initio data. This paper reviews the role of various models across different length and time scales in investigating irradiation effects on microstructure evolution and degradation, in particular the embrittlement caused by radiation induced or enhanced formation of nanoscale chemical heterogeneities. The strength and limitations of these models, including classical rate theories, cluster dynamics, phase-field methods, and atomistic models informed by ab initio energies, are discussed with seminal examples. Challenges regarding the lack of thermo-kinetic data and theoretical treatments considering chemical complexities and magnetic excitations, as well as the stabilizing effect by excess point defects in nuclear structural materials are presented, along with potential solutions based on ab initio informed surrogate energy models and statistical sampling by Monte Carlo simulations. Further, the review then highlights the opportunities to leverage the advantages of different methods by establishing hybrid models by shared variables or coupled codes and applications. Finally, the review concludes with forward-looking remarks on how the use of physics-based models can aid the improvement of machine-learning models of property degradation and vice versa.

36 MATERIALS SCIENCE↗

Impact of salinity origin on microbial communities in saline springs within the Illinois Basin, USA

Abstract Saline springs within the Illinois Basin result from the discharge of deep‐seated evaporated seawater (brine) and likely contain diverse and complex microbial communities that are poorly understood. In this study, seven saline/mineral springs with different geochemical characteristics and salinity origins were investigated using geochemical and molecular microbiological analyses to reveal the composition of microbial communities inhabiting springs and their key controlling factors. The 16S rRNA sequencing results demonstrated that each spring harbours a unique microbial community influenced by its geochemical properties and subsurface conditions. The microbial communities in springs that originated from Cambrian/Ordovician strata, which are deep confined units that have limited recharge from overlying formations, share a greater similarity in community composition and have a higher species richness and more overlapped taxa than those that originated from shallower Pennsylvanian strata, which are subject to extensive regional surface and groundwater recharge. The microbial distribution along the spring flow paths at the surface indicates that 59.8%–94.2% of total sequences in sedimentary samples originated from spring water, highlighting the role of springs in influencing microbiota in the immediate terrestrial environment. The results indicate that the springs introduce microbiota with a high biodiversity into surface terrestrial or aquatic ecosystems, potentially affecting microbial reservoirs in downstream ecosystems.

54 ENVIRONMENTAL SCIENCES↗

2023 American Society for Mass Spectrometry (ASMS) 71st Annual Conference on Mass Spectrometry and Allied Topics

Introduction (120 words max) Understanding metal-cluster chemistry occuring at solvent boundaries in the aqueous and organic phases has applications in environments from cellular processes to nuclear fuel reprocessing. Transport of metal ions at the boundaries from aqueous to organic phases involves forming a metal-ligand complex, and wherever the initial metal coordination environment is significantly different from the final one, the metal transitions through a series of transient species in passing from one phase to another. Here an investigation of the role of coordination in the chemistry of the transient species using gas-phase measurements that are free of solvent effects to better understand the binding of complexes of metals with triphenylphosphine chalcogenide ligands, examining metal-ligand homo- and hetero-dimers to better understand transient species. Methods (120 word max) Mass spectrometry and collision induced dissociation (CID) experiments were performed with a Bruker (Billerica, MA, USA) micrOTOF-Q II quadrupole time-of-flight mass spectrometer (QTOF) and Bruker amaZon speed ETD (ion trap). High resolution/high mass accuracy spectra were generated using the QTOF. External calibration was performed with Agilent (Santa Clara, CA, USA) ESI-L Low Concentration tuning mix. Both mass spectrometers were equipped with either the electrospray ionization source or nanospray sources. Metal samples were prepared between 40 – 60 uM of the metal-ligand complex in 25% water and 75% acetonitrile. Metal-ion clusters were isolated and subjected to collision induced dissociation. Density functional theory calculations were performed. Preliminary Data or Plenary Speakers Abstract (300 words max) Metal ion clusters with triphenylphosphine chalcogenide ligands were observed for group I metals with triphenylphosphine chalcogenide samples in the mass spectrum upon electrospray ionization. For each metal ligand complex of interest, the parent ion was isolated and collision induced dissociation fragmentation spectra were acquired. We observed clusters of group I metal with triphenylphosphine oxide, triphenyl phosphine sulfide, and triphenylphosphine selenide, with homodimers and heterodimer formation. In samples where the ligands were mixed, we observed mixed sodium ligand clusters at varying amounts. These mixed ligand clusters were fragmented. Metal clusters of mixed ligand dimers containing triphenylphosphine oxide showed preferential loss of the other ligand, either triphenylphosphine sulfide or triphenyl selenide. In samples with mixed triphenylphosphine sulfide and triphenylphosphine selenium ligands, sodium bound similarly between the ligands, and losses were more evenly split, showing loss ratio upon CID with losses of triphenylphosphine sulfide:triphenylphosphine selenide 43:57 ratio observed on CID. These results suggest that the oxide binds significantly more strongly than either the selenium or sulfur triphenylphosphine ligand, and the sulfur and selenium ligands are more evenly bound. Calculations were performed using density functional theory to calculate likely structures and bond energies between the group I metal and the ligands. Novel Aspect Novel analysis of sodium bound dimers with chalcogenide triphenylphosphine ligands were investigated using mass spectrometry and theoretical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

Abstract The assessment and regulation of chemical toxicity to protect human health and the environment are done one chemical at a time and seldom at environmentally relevant concentrations. However, chemicals are found in the environment as mixtures, and their toxicity is largely unknown. Understanding the hazard posed by chemicals within the mixture is critical to enforce protective measures. Here, we demonstrate the application of bioactivity profiling of environmental water samples using the sentinel and ecotoxicology model species Daphnia to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a Daphnia strain to 30 sampled waters of the Chaobai River and measured the gene expression response profiles. Using a multiblock correlation analysis, we establish correlations between chemical mixtures identified in 30 water samples with gene expression patterns induced by these chemical mixtures. We identified 80 metabolic pathways putatively activated by mixtures of inorganic ions, heavy metals, polycyclic aromatic hydrocarbons, industrial chemicals, and a set of biocides, pesticides, and pharmacologically active substances. Our data-driven approach discovered both known bioactivity signatures with previously described modes of action and new pathways linked to undiscovered potential hazards. This study demonstrates the feasibility of reducing the complexity of real-world mixture toxicity to characterize the biomolecular effects of a defined number of chemical components based on gene expression monitoring of the sentinel species Daphnia.

Engineering↗

Spectroscopic signatures and oxidation characteristics of nanosecond laser-induced cerium plasmas

Improving technologies related to the wide area environmental sampling of nuclear materials supports the nuclear nonproliferation mission of preventing the proliferation of nuclear weapons by monitoring nuclear weapons tests and detecting undeclared nuclear fuel cycle activities. Standoff, laser-based detection techniques such as laser-induced breakdown spectroscopy have the potential to offer robust, field-deployable methods that provide rapid element-specific and phase identifiable measurements over a wide range of materials. This work aims to elucidate the effects of atmospheric conditions and oxidation reactions on the highly complex and transient spectroscopic signatures of laser-induced plutonium surrogate plasmas. Time-resolved spectra of nanosecond laser ablation cerium plasmas were measured using laser-induced breakdown spectroscopy in a range of atmospheres containing low to high concentrations of oxygen. Here, the growth of strong CeO molecular emission bands was observed in the visible spectrum, where it was shown that the persistence of CeO is reduced from around 60 μs to 50 μs in oxygen rich atmospheric environments. To further investigate the growth and depletion of CeO in the laser-produced plasma, ratios of CeO-to-Ce emission were generated using integrated intensities corresponding to the Q-branch of the CeO D 1 -X 1 transitions and numerous strong atomic Ce peaks. It was determined that the fastest rate of formation of CeO in argon occurred for moderate oxygen mass fractions between 0.10 and 0.15 while the ratios were reduced at higher oxygen mass fractions (i.e., Y O 2 = 0.20) due to competing oxidation reactions and lower plasma temperatures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗