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Near-Surface Imaging of the Multicomponent Gas Phase above a Silver Catalyst during Partial Oxidation of Methanol

Fundamental chemistry in heterogeneous catalysis is increasingly explored using operando techniques in order to address the pressure gap between ultrahigh vacuum studies and practical operating pressures. Because most operando experiments focus on the surface and surface-bound species, there is a knowledge gap of the near-surface gas phase and the fundamental information the properties of this region convey about catalytic mechanisms. In this work, we demonstrate in situ visualization and measurement of gas-phase species and temperature distributions in operando catalysis experiments using complementary near-surface optical and mass spectrometry techniques. The partial oxidation of methanol over a silver catalyst demonstrates the value of these diagnostic techniques at 600 Torr (800 mbar) pressure and temperatures from 150 to 410 °C. Planar laser-induced fluorescence provides two-dimensional images of the formaldehyde product distribution that show the development of the boundary layer above the catalyst under different flow conditions. Raman scattering imaging provides measurements of a wide range of major species, such as methanol, oxygen, nitrogen, formaldehyde, and water vapor. Near-surface molecular beam mass spectrometry enables simultaneous detection of all species using a gas sampling probe. Detection of gas-phase free radicals, such as CH 3 and CH 3 O, and of minor products, such as acetaldehyde, dimethyl ether, and methyl formate, provides insights into catalytic mechanisms of the partial oxidation of methanol. The combination of these techniques provides a detailed picture of the coupling between the gas phase and surface in heterogeneous catalysis and enables parametric studies under different operating conditions, which will enhance our ability to constrain microkinetic models of heterogeneous catalysis.

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Label-Free In Situ Chemical Characterization of Amyloid Plaques in Human Brain Tissues

The accumulation of amyloid plaques and increased brain redox burdens are neuropathological hallmarks of Alzheimer’s disease. Altered metabolism of essential biometals is another feature of Alzheimer’s, with amyloid plaques representing sites of disturbed metal homeostasis. Despite these observations, metal-targeting disease treatments have not been therapeutically effective to date. A better understanding of amyloid plaque composition and the role of the metals associated with them is critical. To establish this knowledge, the ability to resolve chemical variations at nanometer length scales relevant to biology is essential. Here, we present a methodology for the label-free, nanoscale chemical characterization of amyloid plaques within human Alzheimer’s disease tissue using synchrotron X-ray spectromicroscopy. Our approach exploits a C–H carbon absorption feature, consistent with the presence of lipids, to visualize amyloid plaques selectively against the tissue background, allowing chemical analysis to be performed without the addition of amyloid dyes that alter the native sample chemistry. Using this approach, we show that amyloid plaques contain elevated levels of calcium, carbonates, and iron compared to the surrounding brain tissue. Chemical analysis of iron within plaques revealed the presence of chemically reduced, low-oxidation-state phases, including ferromagnetic metallic iron. The zero-oxidation state of ferromagnetic iron determines its high chemical reactivity and so may contribute to the redox burden in the Alzheimer’s brain and thus drive neurodegeneration. Ferromagnetic metallic iron has no established physiological function in the brain and may represent a target for therapies designed to lower redox burdens in Alzheimer’s disease. Additionally, ferromagnetic metallic iron has magnetic properties that are distinct from the iron oxide forms predominant in tissue, which might be exploitable for the in vivo detection of amyloid pathologies using magnetically sensitive imaging. We anticipate that this label-free X-ray imaging approach will provide further insights into the chemical composition of amyloid plaques, facilitating better understanding of how plaques influence the course of Alzheimer’s disease.

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Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

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Accuracy in Resolving the First Hydration Layer on a Transition-Metal Oxide Surface: Experiment (AP-XPS) and Theory

Understanding the equilibrium conditions at the metal oxide/aqueous interface is a key component toward visualizing the structure of water in confined environments and differentiating the catalytic activity of transition-metal oxides. While ambient pressure X-ray photoelectron spectroscopy (AP-XPS) has been the primary technique to investigate the formation of a hydration layer on many surfaces, results over the extended relative humidity (RH) range accessible experimentally have not been compared quantitatively to theoretical predictions. With the use of first-principles theoretical methods and accumulated knowledge of AP-XPS spectral analysis, we do so here for a model surface, TiO 2 -terminated undoped SrTiO 3 (100) (STO). The measured distribution of OH and H 2 O coverages from vacuum up to the first hydration layer is in good agreement with a static density functional theory (DFT) configuration involving partial dissociation of H 2 O per Ti-atom mediated by H-bonding. Furthermore, ab initio molecular dynamics (AIMD) simulations at 300 K for select coverages (1/4, 1/2, and 1 ML) test the role of fluctuations and entropy in the competition between adsorption and dissociation with coverage. This comparison between theory and experiment for OH and H 2 O coverages on STO provides a foundation for a more quantitative assessment of the first hydration layer and associated competition between adsorption, dissociation, and H-bonding on transition-metal oxide surfaces.

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Tracing Actin Filament Bundles in Three-Dimensional Electron Tomography Density Maps of Hair Cell Stereocilia

Cryo-electron tomography (cryo-ET) is a powerful method of visualizing the three-dimensional organization of supramolecular complexes, such as the cytoskeleton, in their native cell and tissue contexts. Due to its minimal electron dose and reconstruction artifacts arising from the missing wedge during data collection, cryo-ET typically results in noisy density maps that display anisotropic XY versus Z resolution. Molecular crowding further exacerbates the challenge of automatically detecting supramolecular complexes, such as the actin bundle in hair cell stereocilia. Stereocilia are pivotal to the mechanoelectrical transduction process in inner ear sensory epithelial hair cells. Given the complexity and dense arrangement of actin bundles, traditional approaches to filament detection and tracing have failed in these cases. In this study, we introduce BundleTrac, an effective method to trace hundreds of filaments in a bundle. A comparison between BundleTrac and manually tracing the actin filaments in a stereocilium showed that BundleTrac accurately built 326 of 330 filaments (98.8%), with an overall cross-distance of 1.3 voxels for the 330 filaments. BundleTrac is an effective semi-automatic modeling approach in which a seed point is provided for each filament and the rest of the filament is computationally identified. We also demonstrate the potential of a denoising method that uses a polynomial regression to address the resolution and high-noise anisotropic environment of the density map.

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Radiological Performance Modeling: Platform Comparison

Zapadnoe Uranium Mill Tailings Site, Pridneprovsky Chemical Plant Ukraine: Two exposure scenarios were utilized to develop performance assessment models in GoldSim and NORMALYSA. The first scenario is an onsite worker exposed to radioactivity through external ground irradiation as well as radon and radioactive dust inhalation. The second being an offsite Resident 300 years after institutional control exposed through the ingestion of garden vegetables irrigated by contaminated ground water, ingestion of fish from Konoplyanka River, and agricultural activities in contaminated garden. NORMALYSA utilizes a modular interface to connect extensive pre-created modules to develop contaminant transport and risk assessment models for safety assessments and performance assessments at NORM and legacy sites. Developed by Facilia AB, the program was tested with the creation of the Zapadnoe model under the International Atomic Energy Agency MODARIA Il Working Group 1 (WG1). Default values are provided for input parameters where site specific data and distributions lack. Probabilistic simulations and inputs are limited to parameters with assigned Gaussian probability functions. Similar results for transient worker inhalation dose were found in comparison with the Zapadnoe GoldSim model. However, the NORMALYSA model has results larger by an order of magnitude for external radiation in the transient worker and for aquatic food ingestion, inhalation, and garden food ingestion to the resident. Performance Assessment Modeling: Radiological performance models promote good management and support in remediation and environmental decision making by optimizing radioactive waste disposal site performance. a performance assessment model of the Zapadnoe uranium mill tailings site and a model for calculating authorized limits at Los Alamos National Laboratory are created to demonstrate and highlight the respective capabilities of three modeling platforms: GoldSim, NORMALYSA, and RESRAD-Onsite. GoldSim is a general-purpose modeling platform with the ability to simulate site-specific FT radionuclide transport and risk assessment using a graphical interface to create and link elements that act as indivisible building blocks of the model. The Zapadnoe performance assessment model created in GoldSim is composed of input parameters collected from site specific parameters from WG1 as well as standard assumptions seen in the Generic PA Model from Neptune and Company. The multivariate Zapadnoe simulation contains both deterministic and probabilistic simulation capabilities with the ability to quantitatively represent the uncertainty and associated risks of the site via the Monte Carlo simulation method. Model parameters, documentation, and assumptions are built directly into the model creating a transparent, reproducible, and more purposeful site specific model. To demonstrate this, an ingestion of water pathway was included in addition to the exposure pathways included in the NORMALYSA model. GoldSim offers a wide variety of probability distributions to choose from as well as many tools to visualize the uncertainty of the models and explore which pathways and radionuclides dominate dose. In contrast to the NORMALYSA model, the GoldSim model uses dynamic simulation to calculate tritium concentrations. Authorized limits support the evaluation of radiological health effects from radionuclides present in bulk contaminated soil in order to assist in the process of clearing land for release under different uses. Calculations of authorized limits in RESRAD-Onsite and GoldSim models support the evaluation for 15 radionuclides using a residential exposure scenario, indoor and outdoor inhalation of dust and vapor phase radionuclides (tritium), incidental soil ingestion, and ingestion grown fruits and Vegetables. RESRAD-Onsite, developed by Argonne National Laboratory is a dedicated computer code for calculating radiation doses and cancer risks to an individual located on top of radioactively contaminated soils. It can also be used to provide guidelines for deriving radionuclide soil levels corresponding to a specific dose criterion. The menu driven user interface facilitates selection of radionuclides and soil concentrations, as well as defines parameter values related to materials, environmental factors, and exposure pathways. The program contains radionuclide-specific data such as dose conversion factors and risk coefficients, as well as soil-water partition coefficients and transfer factors for biotic media. The GoldSim model successfully emulates the RESRAD-Onsite code using identical radiological decay and ingrowth factors, radiation dose conversion factors, and other input parameters. DE EEDE ETS Each model supports dynamic modeling of radionuclide ingrowth and decay over time, and integrate this capability with the transport of radionuclides in the environment via processes such as advection and/or diffusion in fluids, or within porous solid media, The applicability of each program is heavily dependent on project context. In the context of developing Authorized Limits, RESRAD-Onsite may be a more desirable option as it was developed for this particular application. For simple disposal or legacy sites or sites that do not need site-specific model structure, NORMALYSA may be a desirable modeling platform, GoldSim can be used to model any problem for which RESRAD or NORMALYSA is applicable, but its strength lies in its flexibility, analytical, and probabilistic capabilities.

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Visualizing Orbital Content of Electronic Bands in Anisotropic 2D Semiconducting ReSe 2

Many properties of layered materials change as they are thinned from their bulk forms down to single layers, with examples including indirect-to-direct band gap transition in 2H semiconducting transition metal dichalcogenides as well as thickness-dependent changes in the valence band structure in post-transition-metal monochalcogenides and black phosphorus. Here, we use angle-resolved photoemission spectroscopy to study the electronic band structure of monolayer ReSe 2 , a semiconductor with a distorted 1T structure and in-plane anisotropy. By changing the polarization of incoming photons, we demonstrate that for ReSe 2 , in contrast to the 2H materials, the out-of-plane transition metal dz2 and chalcogen pz orbitals do not contribute significantly to the top of the valence band, which explains the reported weak changes in the electronic structure of this compound as a function of layer number. We estimate a band gap of 1.7 eV in pristine ReSe 2 using scanning tunneling spectroscopy and explore the implications on the gap following surface doping with potassium. Additionally, a lower bound of 1.4 eV is estimated for the gap in the fully doped case, suggesting that doping-dependent many-body effects significantly affect the electronic properties of ReSe 2 . Our results, supported by density functional theory calculations, provide insight into the mechanisms behind polarization-dependent optical properties of rhenium dichalcogenides and highlight their place among two-dimensional crystals.

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Structures of the intermediates of Kok’s photosynthetic water oxidation clock

Inspired by the period-four oscillation in flash-induced oxygen evolution of photosystem II discovered by Joliot in 1969, Kok performed additional experiments and proposed a five-state kinetic model for photosynthetic oxygen evolution, known as Kok’s S-state clock or cycle. The model comprises four (meta)stable intermediates (S 0 , S 1 , S 2 and S 3 ) and one transient S 4 state, which precedes dioxygen formation occurring in a concerted reaction from two water-derived oxygens bound at an oxo-bridged tetra manganese calcium (Mn 4 CaO 5 ) cluster in the oxygen-evolving complex. This reaction is coupled to the two-step reduction and protonation of the mobile plastoquinone QB at the acceptor side of PSII. Here in this paper, using serial femtosecond X-ray crystallography and simultaneous X-ray emission spectroscopy with multi-flash visible laser excitation at room temperature, we visualize all (meta)stable states of Kok’s cycle as high-resolution structures (2.04–2.08 Å). In addition, we report structures of two transient states at 150 and 400 µs, revealing notable structural changes including the binding of one additional ‘water’, Ox, during the S 2 →S 3 state transition. Our results suggest that one water ligand to calcium (W3) is directly involved in substrate delivery. The binding of the additional oxygen Ox in the S 3 state between Ca and Mn1 supports O–O bond formation mechanisms involving O5 as one substrate, where Ox is either the other substrate oxygen or is perfectly positioned to refill the O5 position during O 2 release. Thus, our results exclude peroxo-bond formation in the S 3 state, and the nucleophilic attack of W3 onto W2 is unlikely.

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High-Resolution Comonomer Sequencing of Blocky Brominated Syndiotactic Polystyrene Copolymers Using 13C NMR Spectroscopy and Computer Simulations

This work demonstrates the first high-resolution comonomer sequencing of Blocky brominated syndiotactic polystyrene (sPS-co-sPS-Br) copolymers based on pentad assign- ments of the quaternary carbon region of the nuclear magnetic resonance spectrum. Copolymers containing p-bromostyrene (Br-Sty) units were prepared in matched sets using postpolymerization bromination methods carried out in the heterogeneous gel state (Blocky) and homogeneous solution state (Random). Quantitative information from the quaternary carbon spectra, heteronuclear multiple bond correlation spectroscopy, electronic structure calculations, and simulated statistically random copolymers was correlated to confirm the carbon resonance assignments for all 20 possible pentad comonomer sequences. Using the experimental pentad sequence prevalences, a computer code was developed to simulate chains with microstructures typical of each sample as a means to visually represent the copolymer blockiness with quantitative precision. Based on the microstructure and distribution of run lengths in these chains, the simulations revealed that the Blocky copolymers contain a high degree of blockiness. By comparing the run lengths in the simulated chains to the average number of styrene units in a crystalline segment of sPS (found by small-angle X-ray scattering), copolymer crystallizability was predicted. For the simulated Blocky B-21% (21 mol % Br-Sty) chain, the probability of randomly selecting a styrene unit in a crystallizable block was 25.8%, while that in the simulated Random R-18% was zero, in excellent agreement with the experimental crystallization behavior measured by differential scanning calorimetry. Additionally, these predictions confirmed that the simulated chains accurately represent the ensemble of chains in their respective copolymer samples. Furthermore, each simulated Blocky chain contained one or more long sPS blocks that paralleled the measured 38-40 styrene units spanning a crystalline segment within the sPS/CCl4 gel. This finding affirmed that the long sPS segments originated from the precise lamellar structure within the heterogeneous gel morphology (i.e., block length is correlated with lamellar thickness). Overall, the ability to tailor the copolymer microstructure through control of the semicrystalline gel morphology opens the door to synthesizing ordered copolymers by postpolymerization functionalization processes with unprecedented levels of compositional control.

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Going around the Kok cycle of the water oxidation reaction with femtosecond X-ray crystallography

The water oxidation reaction in photosystem II (PS II) produces most of the molecular oxygen in the atmosphere, which sustains life on Earth, and in this process releases four electrons and four protons that drive the downstream process of CO 2 fixation in the photosynthetic apparatus. The catalytic center of PS II is an oxygen-bridged Mn 4 Ca complex (Mn 4 CaO 5 ) which is progressively oxidized upon the absorption of light by the chlorophyll of the PS II reaction center, and the accumulation of four oxidative equivalents in the catalytic center results in the oxidation of two waters to dioxygen in the last step. The recent emergence of X-ray free-electron lasers (XFELs) with intense femtosecond X-ray pulses has opened up opportunities to visualize this reaction in PS II as it proceeds through the catalytic cycle. In this review, we summarize our recent studies of the catalytic reaction in PS II by following the structural changes along the reaction pathway via room-temperature X-ray crystallography using XFELs. The evolution of the electron density changes at the Mn complex reveals notable structural changes, including the insertion of O X from a new water molecule, which disappears on completion of the reaction, implicating it in the O—O bond formation reaction. We were also able to follow the structural dynamics of the protein coordinating with the catalytic complex and of channels within the protein that are important for substrate and product transport, revealing well orchestrated conformational changes in response to the electronic changes at the Mn 4 Ca cluster.

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Replacement of Calcium Carbonate Polymorphs by Cerussite

Calcium carbonate (CaCO 3 ) polymorphs, calcite, aragonite, and vaterite, serve as a major sink to retain various metal ions in natural and engineered systems. Here, we visualize the systematic trends in reactivities of calcite, vaterite, and aragonite to Pb 2+ dissolved in acidic aqueous solutions using in situ optical microscopy combined with ex situ scanning electron and transmission X-ray microscopies. All three polymorphs undergo pseudomorphic replacement by cerussite (PbCO 3 ) but with distinct differences in the evolution of their morphologies. The replacement of calcite and aragonite occurs through the formation of a pseudomorphic cerussite shell (typically 5–10 μm thick) followed by a slower inward propagation of reaction fronts through a thin solution gap (~0.1 μm wide) between the shell and the CaCO 3 substrate. The replacement of vaterite is characterized by the formation of a thinner cerussite shell (≤1 μm thick) and a larger cavity between the shell and the host mineral. These systematic differences in cerussite morphology for different CaCO 3 polymorphs are explained by the relative dissolution and precipitation rates of the reactant and product minerals, coupled with the role of ion transport through the cerussite shells. We also find that the replacement of calcite by cerussite is the slowest when all three polymorphs coexisted. Furthermore, our results provide mechanistic insights into the growth mode of cerussite on dissolving calcium carbonate and demonstrate these CaCO 3 polymorphs as promising substrate materials for removal and recycling of Pb from acidic polluted water and industrial effluents.

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Evaluation of a Sulfate Solubility Limit Greater Than 0.65 Weight Percent in Sludge Batch 10 Glasses

Previous laboratory-scale crucible testing with batch chemicals confirmed that the sulfate (SO 4 2- ) limit for Sludge Batch 10 (SB10) was 0.65 weight percent (wt.%) in glass. This limit signifies that 0.65 wt.% SO 4 2- can be retained in the glass without the formation of a sulfate phase. The Defense Waste Processing Facility imposes this constraint in the Material Tracking Program. Based on preliminary calculations to support the Material Tracking Program, it was anticipated that transfer volumes of the monosodium titanate/sludge solids (MST/SS) stream from the Salt Waste Processing Facility (SWPF) may need to be reduced to maintain projected sulfate concentrations below 0.65 wt.% in glass. Savannah River Mission Completion requested that the Savannah River National Laboratory perform additional sulfate testing to determine whether a sulfate solubility limit greater than 0.65 wt.% is feasible for SB10, which could allow for higher transfer volumes of the MST/SS stream. This report documents the results of the testing at higher sulfate concentrations for the glass composition region defined by the most recent SB10 projection (November 2022) and Frits 473 and 625. Frit 473 was recommended for SB10 and Frit 625 was used during SB9 processing and the SB9 to SB10 transition. A total of twenty-one glass compositions were developed based on the expected compositional variables, which include sludge-only (SO) and coupled processing with the SWPF, waste loading (WL), and frit composition. The target sulfate concentrations were varied from 0.65-0.85 wt.% at 32 and 40% WL. Each glass was prepared from reagent grade chemicals and melted at 1150 °C. Visual observations were used to confirm the presence of a sulfate salt phase on the cooled glass surfaces. Representative samples of each glass were submitted for chemical composition analysis by inductively coupled plasma-optical emission spectroscopy and Cs analysis by inductively coupled plasma-mass spectrometry. Overall the majority of mean measured values are consistent with the target values for each major oxide of interest with less than 5% error. The percent errors for the measured SO 4 2- concentrations are generally less than 10%, which is comparable with previous sulfate solubility study measurements and acceptable. Only the SO glasses based on Frit 625 formed a sulfate phase at a 0.80 wt.% SO 4 2- target concentration at both 32 and 40% WL. The remainder of the glasses did not form a sulfate layer. Due to the formation of the sulfate phase, the limit is conservatively set at 0.70 wt.% based on the measured sulfate concentrations of 0.71 wt.% and 0.75 wt.% for these two glasses. None of the SO or coupled operation glasses based on Frit 473 formed a sulfate salt phase, which supports a sulfate limit of 0.80 wt.%. The following SO 4 2- concentration limits are recommended during SO and coupled SB10 processing: (1) 0.70 wt.% during processing with Frit 625, and (2) 0.80 wt.% during processing with Frit 473.

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INVESTIGATION OF ROCK-FLUID INTERACTIONS USING GEOMATERIAL MICROFLUIDICS

Illite and Illite-Smectite clays are reportedly the Caney Shale's most prevalent clay minerals. The swelling and fines migration of clays may occur when water-based fluids contact the clay minerals. This may result in the reduction of pore space and permeability, and wettability alteration. Therefore, we quantified the swelling potentials, fines migration and wettability alteration of Illite and Illite-Smectite clays upon exposure to model brines and a produced water, and a model oil and a crude oil. We measured density, viscosity, pH, TDS, and interfacial tension as they are important in multiphase flow and displacement characteristics. Geomaterial microfluidics is recently being used to study physicochemical interactions of solid-fluid systems. It facilitates visualizing the surface behavior upon exposure to various fluids. This study includes preparation and characterization of Illite-Smectite clay-coated glass capillary tubes. Illite and Illite-Smectite clay-coated geomaterial microfluidic surfaces were prepared to investigate the effects of first contact fluid, brine salinity, and aging on wettability. In this work, advancing and receding contact angles of model brine-air, model oil-air, produced water-air, crude oil-air, model brine-model oil systems, and produced water-crude oil systems have been measured in the untreated, and clay-coated microfluidic channels of 1000 µm width and 50 µm depth. The aging effect was studied by retaining the non-aqueous and aqueous solutions in the corresponding microfluidic channels for approximately 24 h in the case of channels first contacted by aqueous and non-aqueous solutions, respectively. The advancing and receding contact angles of Caney shale-crude oil-produced water systems were also measured. The experimental findings indicate the swelling potential, fines migration, and wettability alteration of Illite and Illite-Smectite clays. The results signify the influence of first contact fluid, brine salinity, and aging on wettability of the untreated and clay-coated microfluidic surfaces. The experiments also demonstrate the wetting nature of the Caney shale samples from reservoir and non-reservoir zones.

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Cyanine-Incorporated Amorphous Polymeric Carbon Dots for Optical Reactive Oxygen Species Sensing

Reactive oxygen species (ROS) are common cellular oxidants that when overproduced by cellular stressors cause harm to cells. Detection of ROS is of utmost importance to understanding a wide variety of cellular function and toxicity mechanisms. Conventional ROS fluorescence assays involve using a single dye to visualize the ROS quantity. Herein, we describe ROS-sensitive, fluorescent-dye-incorporated carbon dots with dual fluorescence capabilities and good biocompatibility. Carbon dots (CDs) made of citric acid and urea were synthesized with incorporated cyanine-3-amine (Cy3), a bright red fluorescent dye, to create Cy3-CDs. Additionally, to get Cy3 into the ROS-sensitive form, this work demonstrated that Cy3 alone and Cy3 within carbon dots can be electrochemically reduced to their colorless ROS-sensitive form. Cy3, CDs, and Cy3-CDs are all responsive to additions of superoxide, leading to an increase in the fluorescence. Overall, this work examines how O 2 •– and additional oxidizers interact with CDs, Cy3, and Cy3-CDs, and molecular-level hypotheses are explored that will inform the design of future carbon dot-based ROS sensors.

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Novel Amorphous Carbons for the Adsorption of Phosphate: Part I. Elucidation of Chemical Structure of N-Metal-Doped Chars

Due to phosphate’s necessity in agriculture and its danger to the environment, the development of adsorbents for its removal has been the subject of intensive research activity. Although the introduction of nitrogen functionality to chars and modification of biochar with metals have proven to change the character of the char structure, making it more active toward nutrients, there is no study regarding the doping of biochar with metals and nitrogen simultaneously for the adsorption of phosphates. This paper is the first of two in which we report the production, characterization, and evaluation of N-metal-doped biochars from cellulose for phosphate removal from liquid effluents. In this part, we describe the production and characterization of N-Ca-, N-Fe-, and N-Mg-doped biochars. The elemental composition and surface area of each of the materials produced is reported. Elemental and surface characterization of the chars are reported with the largest N content appearing at a temperature of 800 °C (12.5 wt %) and a maximum surface area for biochar produced at 900 °C (1314 m2/g). All of the adsorbents were visualized by scanning electron microscope (SEM), confirming that although there are some crystals on the surface of the biochar produced, most of the N, Mg, and Ca are part of the polyaromatic ring structure. Transmission electron microscope (TEM) images clearly show the formation of nanoclusters with the metals in the case of N-Fe and N-Ca biochars. The N-Mg biochars show a uniform distribution of the Mg through the carbon surface. X-ray photoelectron spectroscopy (XPS) studies of the biochars produced with metals and varying nitrogen levels clearly show Mg and Ca peaks shifting their position in the presence of N, suggesting the formation of stable structures between metals and N in the carbon polyaromatic ring system. To elucidate the nature of these structures, we conducted DFT-based calculations on different configurations of the nitrogenated structures. The calculated binding energy shifts were found to closely match the XPS experimental binding energy, confirming the likelihood of these structures in biochar. Finally, based on our experimental and modeling results, we hypothesize that an important fraction of the Mg and Ca is introduced to these biochars at the edges. Another fraction of Mg and Ca is in the form of phthalocyanine-like internal structures. More experimental studies are needed to confirm the formation of these very interesting structures and their potential use as adsorbents or catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated Quantum Simulations of Polymer Aging and Degradation

We have conducted extensive quantum simulations to predict the susceptibility of polydimethylsiloxane (PDMS) under tensile loads (i.e., stretching) to hydrolytic reactions. Initial results under uniform strain revealed that the PDMS electronic state is highly sensitive to deformations of the Si-O backbone (Figure 1). Predictions for the energy gap between the highest-occupied and lowestunoccupied molecular orbitals (i.e., the HOMO-LUMO gap, E Gap ) and visualization of these orbitals reveals the distinct possibility that strained PDMS chains have an electronically driven anisotropy in their susceptibility to hydrolysis. First, we observe that EGap begins to drop precipitously as the PDMS chain is stretched beyond 10% (labeled 1.1 in the figure). The increased accessibility of these unoccupied states generally will promote chemical degradation, as excited electronic states due to bond breaking will form more easily. Second, we observe that the geometric character of the LUMO state changes under stretching of 20% (strains of 1.20) and larger, whereby the orbital density localizes to the interior of the O-Si-O bond angles along the backbone. This LUMO localization coupled with a substantial reduction in EGap indicates that the interior O-Si-O bond angles may be potential sites for chemistry due to environmental water or by roaming acids or bases. This is in contrast to a chemical attack on the backside of the O-Si-O angle, where there is practically no density of low-energy unoccupied states. The enhanced electronic susceptibility likely couples with steric shielding by the two methyl groups that also protect the backside of the Si-O chain. These detailed results can be used as inputs for coarse-grained simulation approaches, by helping us to define the susceptibility of specific polymer chain location to scission and/or backbiting reactions, based on the local geometry of the Si-O backbone. Definition of this type of order parameter with application to larger scale models is the subject of our future work.

36 MATERIALS SCIENCE↗

Automated assignment of rotational spectra using artificial neural networks

Here, a typical broadband rotational spectrum may contain several thousand observable transitions, spanning many species. While these spectra often encode troves of chemical information, identifying and assigning the individual spectra can be challenging. Traditional approaches typically involve visually identifying a pattern. A more modern approach is to apply an automated fitting routine. In this approach, combinations of 3 transitions are searched by trial and error, to fit the A , B , and C rotational constants in a Watson-type Hamiltonian. In this work, we develop an alternative approach-to utilize machine learning to train a computer to recognize the patterns inherent in rotational spectra. Broadband high-resolution rotational spectra are perhaps uniquely suited for pattern recognition, assignment, and species identification using machine learning. Repeating patterns of transition frequencies and intensities are now routinely recorded in broadband chirped-pulse Fourier transform microwave experiments in which both the number of resolution elements and the dynamic range surpass 10 4 . At the same time, these high-resolution spectra are extremely sensitive to molecular geometry with each polar species having a unique rotational spectrum. Here we train the feed forward neural network on thousands of rotational spectra that we calculate, using the rules of quantum mechanics, from randomly generated sets of rotational constants and other Hamiltonian parameters. Reasonable physical constraints are applied to these parameter sets, yet they need not belong to existing species. A trained neural network presented with a spectrum identifies its type (e.g., linear molecule, symmetric top, or asymmetric top) and infers the corresponding Hamiltonian parameters (rotational constants, distortion, and hyperfine constants). The classification and prediction times, about 160 μs and 50 μs, respectively, seem independent of the spectral complexity or the number of molecular parameters. We describe how the network works, provide benchmarking results, and discuss future directions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗