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At least 1,297 records · Page 72

Evolution of Metastable Phases During Mg Metal Corrosion: An In Situ Cryogenic X-ray Photoelectron Spectroscopy Study

Magnesium and its alloys are potential structural materials candidates for a wide variety of applications due to their high strength-to-weight ratio. However, ductility and poor corrosion resistance under ambient environmental conditions are the bottleneck for industrial deployment. Designing passivation layers and/or corrosion resistant alloys requires fundamental understanding of the corrosion process. The traditional ex-situ spectroscopic measurements of polycrystalline metal surface with ubiquitous surface impurities and grain boundaries only provided an indistinct view of the corrosion process. To clearly distinguish the mechanism and sequence of corrosion process, we employed in-situ cryo-based x-ray photoelectron spectroscopy (XPS) measurements on Mg single crystal surface exposed to aqueous salt solution. Clean Mg (0001) surfaces were exposed to pure D2O and NaCl aqueous solution (5 wt% NaCl+95 wt% D2O). The interfacial reactions were studied using multimodal analysis including XPS, x-ray diffraction (XRD) and scanning electron microscopy (SEM). In contrast to previous studies, our experiments demonstrated the formation of magnesium chloride hydroxide hydrate during aqueous salt corrosion processes. Evidence of metastable ClO* radicals were also found during the initial aqueous salt solution exposure.

Shutthanandan, Vaithiyalingam↗

ADDITIVE MANUFACTURING OF REFRACTORY ALLOYS

Refractory alloys are known for their high temperature capabilities and are intended for use at ultra-high temperatures above even 1200°C, which exceeds the capabilities of conventional superalloys. Additive manufacturing (AM) is an attractive alternative processing route because refractory alloys are difficult to fabricate through traditional methods; AM can form a near net-shape part with a tailored microstructure. This work seeks to evaluate the solidification behavior of refractory alloys under AM conditions and establish corresponding solidification models. Two binary alloys, Mo30Nb and Nb7.5Ta, as well as the commercial Nb alloy, C103, and one refractory high entropy alloy (RHEA), MoNbTaTi, were subjected to single track melts in a laser powder bed fusion (LPBF) machine. Each melt track was evaluated in the scanning electron microscope (SEM), which determined that some AM conditions used led to non-ideal behavior. Electron backscatter diffraction (EBSD) revealed that the Nb7.5Ta, C103, and MoNbTaTi all exhibited new grain nucleation to various extents while the Mo30Nb exhibited primarily epitaxial growth. This was found to be inconsistent with solidification models that were developed for each alloy and each set of AM conditions to predict the columnar to equiaxed transition behavior (CET) of the experimental microstructures. This disparity was largely attributed to the input parameters for the solidification model, which were developed using Thermo-Calc and SYSWELD. These input parameters include the alloy specific Gibbs-Thomson coefficient and thermophysical properties, the solute specific liquidus slopes and partitioning coefficients, as well as the process specific thermal gradients. Each input parameter was evaluated to determine the likely changes required for the modeled values to generate solidification models that better correspond to what was observed experimentally.

Miklas, Abigail↗

Non-Markovian dynamics of open quantum system with memory

Highlights: • Non-Markovian master equation for open quantum system with power-law memory is proposed. • Non-Markovian dynamics of two-level quantum system with memory is described. • Solutions of non-Markovian quantum master equations are derived. • Complete positivity and bi-positivity in non-Markovian quantum dynamics with memory are described. • Exact solution of non-Markovian equations of system with memory is proposed. In this paper, non-Markovian generalization of master equation for open quantum system is proposed. Non-Markovian dynamics of two-level quantum system with memory and interaction with environment is described. To describe this system, the Gorini–Kossakowski–Sudarshan equation for open quantum states is generalized by taking into account power-law fading memory. The non-Markovian quantum processes with power-law memory are described by using integration and differentiation of non-integer orders. Complete positivity and bi-positivity in non-Markovian quantum dynamics with memory are described. An example of two-level quantum systems with power-law memory is suggested. Exact solution of the non-Markovian master equations of two-level open quantum systems with memory is derived.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Benders Decomposition Using Graph Modeling and Multi-Parametric Programming

Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose a flexible and modular algorithmic framework for accelerating Benders decomposition. Specifically, we express the problem structure by using a graph-theoretic modeling abstraction in which nodes represent optimization subproblems and edges represent connectivity between subproblems. A key innovation of our approach is that we embed multiparametric programming (mp) surrogates for node subproblems, which maps the exact analytical map of the subproblem solution space. The use of mp surrogates allows us to replace subproblem solves with fast look-ups and function evaluations for primal and dual variables during the iterative Benders process. We formally show the equivalence between classical Benders cuts and those derived from the mp solution. We implement our framework in the open-source PlasmoBenders.jl software package. To demonstrate the capabilities of the proposed framework, we apply it to a two-stage stochastic programming problem, which aims to make optimal capacity expansion decisions under market uncertainty. We evaluate both single-cut and multicut variants of Benders decomposition and show that the use of mp surrogates achieves substantial speedups in subproblem solve time, while preserving the convergence guarantees of Benders decomposition. We highlight advantages in solution analysis and interpretability that is enabled by mp critical region tracking; specifically, we show that these reveal how decisions evolve geometrically across the Benders search. Our results aim to demonstrate that combining surrogate modeling with graph modeling offers a promising and extensible foundation for structure-exploiting decomposition. In addition, by decomposing the problem into more tractable subproblems, the proposed approach also aims to overcome scalability issues of mp. Finally, the use of mp surrogates provides a unifying and modular optimization framework that enables the representation of heterogeneous node subproblems as modeling objects with a homogeneous structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic Layer Deposition (ALD) of Metal and Metal Oxide Films: A Surface Science Study (Final Report)

This is the final report for this project. The long-term objective of our project is to develop a general molecular-level picture of the surface chemistry associated with ALD processes. Our central hypothesis is that the chemistry of ALD precursors can differ significantly from that seen in solution. Awareness of such differences should provide general guidelines on what to watch for when synthesizing new ALD precursors and designing and optimizing new ALD processes, especially in terms of minimizing the incorporation of impurities in the growing films and of carrying out depositions under mild pressure and temperature conditions. The main objective of our research project has been to advance the fundamental knowledge of the surface chemistry of ALD precursors needed for the design and optimization of film deposition processes. A modern surface-science approach has been implemented to both elucidate the mechanism of the reactions of the precursors on the surface and characterize the composition and morphology of the growing films.

36 MATERIALS SCIENCE↗

Atomic Layer Deposition (ALD) of Metal and Metal Oxide Films: A Surface Science Study (Final Report)

This is the final report for this project. The long-term objective of our project is to develop a general molecular-level picture of the surface chemistry associated with ALD processes. Our central hypothesis is that the chemistry of ALD precursors can differ significantly from that seen in solution. Awareness of such differences should provide general guidelines on what to watch for when synthesizing new ALD precursors and designing and optimizing new ALD processes, especially in terms of minimizing the incorporation of impurities in the growing films and of carrying out depositions under mild pressure and temperature conditions. The main objective of our research project has been to advance the fundamental knowledge of the surface chemistry of ALD precursors needed for the design and optimization of film deposition processes. A modern surface-science approach has been implemented to both elucidate the mechanism of the reactions of the precursors on the surface and characterize the composition and morphology of the growing films. In general, emphasis is being placed on: • Identifying the primary reactions that may lead to the deposition of clean films; •Identifying the secondary reactions that may help the ALD process, by, for instance, helping with the reduction (or oxidation) of the metal atom; • Identifying the secondary reactions that may lead to the deposition of undesirable impurities in the growing films; • Determining the kinetic parameters of the relevant surface reactions in order to define the optimum conditions for film deposition and to minimize impurity deposition. • Characterizing the nature of the resulting films, with focus on their stoichiometry and on the final oxidation states of the constituent elements; and • Using the information obtained to propose better precursors for given ALD processes.

36 MATERIALS SCIENCE↗

Recovery of Rare Earth Elements from Bioleachates by Precipitation

Rare earth elements are essential components in electronic devices, however because of the limited imports and mining capabilities in the US, recycling these rare earths is crucial. Common practices used to recover REEs including hydrometallurgy and pyrometallurgy are harmful to the environment. Bioleaching, a form of biohydrometallurgy, is an emerging process that uses organic acids synthesized by microorganisms and can leach REEs at comparable efficiencies to less environmentally conscious processes. Once the REEs are leached by the bio-lixiviant produced by microorganisms, the REEs are suspended in the solution and need to precipitate out in order to be harvested for reuse. Common chemicals used for rare earth precipitation in hydrometallurgy processes include sodium sulfate and oxalic acid. These two reagents were tested at varying stoichiometric excess concentrations in bio-leachate derived from smart phone speaker magnets and bio-lixiviant. Following the precipitation reactions, it was observed that the oxalic acid reaction precipitated an abundance of iron (II) oxalate, an REE contaminate. This is most likely due to the bio-leachate having a higher pH compared to the hydrometallurgical leachates. Therefore, it was determined that sodium sulfate is a better candidate for REE precipitation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Catalytic Processes to Accelerate Decarbonization in a Net-Zero Carbon World

Reducing carbon dioxide emissions is one of the critical challenges to mitigate global climate change, which is having detrimental impacts on society and the environment. Fossil fuel combustion in transportation, power generation, and industrial processes is the dominant contributor to carbon emissions. Over the past decades, sustainable solutions and strategies have been investigated and developed to enable decarbonization. Catalysis plays an essential role to address this global challenge by increasing energy efficiency, reducing carbon emissions, capturing carbon dioxide, and utilizing clean energy sources to displace fossil fuels. In this Review, the role of catalysis in reducing energy demand was discussed, enhancing process efficiency, displacing carbon-intensive feedstocks and products, and therefore, reducing carbon emissions. Here, recent advances in catalyst development were summarized, focusing on applications to enhance industrial processes efficiency and enable utilization of clean energy sources. Emerging approaches in catalysis were reviewed, including the manufacture of iron and steel, direct air capture of CO 2 , production of ethylene, ammonia, and sustainable aviation fuels, plastic recycling, and the synthesis of biobased plastics. The Review was concluded with suggested research directions to achieve a carbon net-zero world.

36 MATERIALS SCIENCE↗

Discrete Green’s functions and spectral graph theory for computationally efficient thermal modeling

Here, this work concerns solutions of the heat equation with the spectral graph method, for which the temperature is defined at discrete points in the domain and the spatial relationship among the points is described by a graph. The heat equation on the graph is solved using matrix techniques involving the eigenvectors and eigenvalues of the Laplacian matrix. The spectral graph approach precludes the computationally intensive meshing and numerous time-integration steps of the finite element method. In the present work, the spectral graph method is extended to include heat loss at the boundaries with a generalized boundary condition, and physics-based edge weights are introduced which simplify the calibration process. From this approach a discrete Green’s function is defined which allows for solutions under a variety of heating conditions including: space-varying initial conditions; time-and-space varying internal heating; and, time-and-space-varying heating at boundaries of type 1 (Dirichlet), type 2 (Neumann) and type 3 (Robin). Results are provided for benchmark heat transfer problems in one spatial dimension and in three spatial dimensions, and verification is provided by comparison with exact analytical solutions and finite difference solutions. The spectral graph method converges within 0.4% error of the analytical solution. The practical utility of the approach is demonstrated by thermal simulation of a multilayer additive manufacturing process. The spectral graph results are compared to experimentally-obtained temperature data for two metal parts, with error less than 5% of the experimental measurements, with computation time less than one minute on a desktop computer.

36 MATERIALS SCIENCE↗

Iodine Speciation Basis and Gap Analysis for Hanford Tank Farm Inventory and during Processing

Pacific Northwest National Laboratory (PNNL) is providing baseline technical support to Washington River Protection Solutions (WRPS) for the One System River Protection Project (RPP) Integrated Flowsheet team. This report documents the evaluation of the technical bases available to support iodine speciation and distribution within Hanford wastes and subsequent waste streams generated during direct feed low-activity waste (DFLAW) pretreatment operations (specifically, waste retrievals and staging, and particle filtration and cesium decontamination using crystalline silicotitanate (CST) ion exchange [in the tank side cesium removal (TSCR) system]. The task performed a literature survey of information related to iodine species in environments analogous to Hanford tank waste and the subsequent waste streams to define a technical basis for the possible iodine speciation in Hanford waste. In doing so it can be determined how likely laboratory studies on iodine speciation in tank waste are to be universally relevant across the Hanford tanks. The task evaluated iodide and iodate as the primary species of interest with a focus on organo-iodine where appropriate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Transport in Stochastic Media with Random Chord Length Distributions

Thermal radiation transport computations in binary Markovian random mixtures rely almost exclusively on the Levermore-Pomraning (LP) model which is obtained by applying a heuristic closure to the ensemble averaged random medium transport equation. The validity of this model has been extensively tested by comparing numerical results over a broad parameter range (material types and mixing parameters) against benchmark solutions in planar geometry. The conditions under which the LP-model provides useful results and when it breaks down are now well established, but work to date has been largely restricted to homogeneous mixing statistics, i.e., the mean chord lengths of both materials are taken to be spatially constant. In recent work, this limitation was relaxed by allowing the mean chord lengths and, in a consistent fashion, the volume fractions in the LP-model to vary spatially and in a follow-up investigation benchmark solutions were obtained by ensemble averaging results over material realizations sampled from a nonhomogeneous Poisson process (NHPP). Numerical experiments in rod geometry with specifically linear and quadratic spatial dependence of chord lengths showed that the material averaged radiation intensities vary nonmonotonically with depth into the medium, in stark contrast to solutions obtained assuming uniform chord lengths. Moreover, depending on the local optical thickness and strength of scattering, the LP-model results showed locally more nuanced deviations from the benchmark solutions than was the case with constant chord lengths. These limited numerical investigations highlight the nontrivial qualitative and quantitative consequences of nonhomogeneous mixing statistics, in particular that closure approximations may not be uniformly valid or invalid over the problem domain.

42 ENGINEERING↗

Sovereign Credit Rating Processes Adapted to Critical Infrastructure Cyber Risk Assessment

United States critical infrastructure entities are increasingly targeted by motivated and capable threat actors and must be prepared to assess and treat a diverse range of cyber risks. Consequently, this necessitates some form of analytical process to evaluate risks and inform cyber security investment decisions. A potential solution for structuring cyber risk evaluation exists within the field of sovereign credit ratings – where agencies employ mature approaches that integrate quantitative and qualitative data to produce a singular value of assessment. Adapting such approaches, we present a novel criterion and methodology for measuring and communicating the likelihood element of cyber risk. The methodology is composed of three sequential phases: a quantitative baseline organized by distinct capability frames, a bounded qualitative adjustment per frame, and a greater-bounded qualitative adjustment spanning the entire process. The process culminates in publication of a cyber capability rating that communicates a critical infrastructure entity’s ability and willingness to mitigate discontinuous function due to cyberattack.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation↗

Development of Algal Biomass Yield Improvements in an Integrated Process (Final Report)

This project built on the success of Global Algae Innovations Algae Biomass Yield Phase 1 project to accelerate the commercialization of algal biofuels through development of an integrated, economical, photosynthetic, open raceway system to produce algal oil. Two parallel pathways to a biofuel were investigated. In the algal crude oil pathway, highlighted in blue, the dewatered algal biomass slurry is used as a feed to hydrothermal liquefaction to produce an algae crude oil and recycle aqueous stream. In the algal lipid oil pathway, highlighted in green, the algal biomass slurry is dried, and the oil is extracted to produce an algal lipid oil biofuel intermediate and a high protein algae meal co-product. Upgrading to drop-in fuels has been demonstrated for the biofuel intermediates in both pathways. Since the algal lipid oil pathway requires lipid accumulation, the productivity is generally lower than the algal crude oil pathway, but the required productivity for economical algal biofuel production is also lower because the coproduct value is greater. The outdoor cultivation was performed at the Kauai Algae Farm. The project team has expertise across the full breadth strain development, advanced algal cultivation, open raceway contamination control, CO 2 supply, harvesting, dewatering, extraction, hydrothermal liquefaction, technoeconomic analysis and life cycle analysis: Hildebrand laboratory at Scripps Institution of Oceanography – diatom strain development. Mayfield laboratory at UCSD - green algae strain development. TSD Management Associates- CO 2 supply, algal harvesting and dewatering, and algal drying and extraction. Qualitas - large-scale test site for algal harvesting technology. Texas A&M University - algal drying and extraction technology. Pacific Northwest National Laboratory - hydrothermal liquefaction technology. GE Water and Power - membrane technology. National Renewable Energy Laboratory - algal techno-economic analysis. Phase 1 of the project resulted in tremendous productivity and pre-processing improvements in an integrated, large-scale, low-cost cultivation and pre-processing process that moved algal technology closer to economic viability for biofuels than ever before. Phase 2 accomplishments further facilitate development of a commercial algal biofuel industry by adding: several top performing strains and strain development tools including breeding; open-pond cultivation innovations that achieved a 30% improvement in overall productivity, an 83% reduction in cost, and a 95% reduction in energy use relative to conventional technology; further improvements in harvesting that led to the Zobi harvester ® as a universal, economical, low energy, commercially available microalgae harvesting solution; breakthroughs in drying and extraction including a new low energy drying process and several new low energy extraction unit operations that together with the Zobi harvester ® achieve a 90% reduction in cost and 97% reduction in energy use relative to conventional technology. These improvements are sufficient to enable economical production of algae biofuel and protein meal co-product if the process were scaled up to a commercial-scale 5,000-acre algae farm.

09 BIOMASS FUELS↗

In-situ thermodynamics measurements at metal oxides-solution interfaces using Flow Adsorption Microcalorimetry.

Mineral-fluid interfaces are the principal sites of geochemical processes near Earth’s surface, hosting chemical reactions that play a fundamental role in (bio)geochemical cycles and in the fate and transport of anthropogenic contaminants, and that effectively control the compositions of soil and water environments. These complex interfaces are critical for our energy and environmental future. The mineral-fluid interface has been studied in an unprecedented level of detail with both experimental and computational approaches, separately and in combination. However, conspicuously missing from studies of the mineral-fluid interface are direct measurements of the energies of ion sorption and exchange. The literature on energetics and enthalpies of exchange, adsorption, dissolution, precipitation, and surface protonation reactions, especially those directly supported by experimental data, remains scarce despite their fundamental nature. The overarching goal of this project is to complete a systematic study of the thermodynamics properties of interfacial reactions at four MO surfaces (Rutile (α-TiO2), Quartz (SiO2), boehmite (γ-AlOOH) and goethite (α-FeOOH)) through the application and construction of novel flow adsorption microcalorimetry techniques and instrumentations. These unique and specialized microcalorimeters will operate at various temperatures and solution chemical compositions allowing for in-situ measurements across metal oxides and ligands of various characteristics. The overall research goal will be accomplished by completing the following three specific objectives (O): O1) Determine the energetics of surface protonation and deprotonation, ion exchange and ligand sorption reactions; O2) Investigate the surface charge thermodynamic properties under a range of temperature and solution chemical compositions; and O3) Develop predictive trends of the interplay between MO structure, surface coverage and surface reactivity. In addition to key thermodynamics parameters, calorimetric measurements provide a wealth of mechanistic information about reactions energetics and kinetics, surface charge characteristics, and structure-reactivity or selectivity relationships, all obtained in-situ and in real-time. This report includes science highlights from various projects completed over the performance period of the project. Also listed are dissemination opportunities, people supported on the grant and the impact on available physical resources and the discipline as a whole.

58 GEOSCIENCES↗

Predicting Excitation Energies of Twisted Intramolecular Charge-Transfer States with the Time-Dependent Density Functional Theory: Comparison with Experimental Measurements in the Gas Phase and Solvents Ranging from Hexanes to Acetonitrile

Electronically excited states characterized by intramolecular charge transfer play an essential role in many biological processes and optical devices. The ability to make quantitative ab initio predictions of the relative energetics involved is a challenging yet desirable goal, especially for large molecules in solution. In this work, we present a data set of 61 experimental measurements of absorption and emission processes, both in the gas phase and in solvents representing a broad range of polarities, which involve intramolecular charge transfer mediated by a nonzero, "twisted" dihedral angle between one or more donor and acceptor subunits. Among a variety of density functionals investigated within the framework of linear-response theory, the "optimally tuned" LRC-ωPBE functional, which utilizes a system-specific yet nonempirical procedure to specify the range-separation parameter, emerges as the preferred choice. For the entire set of excitation energies, involving changes in dipole moment ranging from 4 to >20 Debye, the mean signed and absolute errors are 0.02 and 0.18 eV, respectively (compared, e.g., to -0.30 and 0.30 for PBE0, 0.44 and 0.47 for LRC-ωPBEh, 0.83 and 0.83 for ωB97X-V). We analyze the performance of polarizable continuum solvation models available in Q-Chem that partition the solvent response into fast and slow time scales, and clear trends emerge when measurements corresponding to the four small 4-(dimethylamino)benzonitrile (DMABN)-like molecules and a charged species are excluded. We make the case that the large errors found only for small molecules in the gas phase and weak solvents cannot be expected to improve via the optimal tuning procedure, which enforces a condition that is exact only in the well-separated donor-acceptor limit, and present empirical evidence implicating the outsized importance for small donor-acceptor systems of relaxation effects that cannot be accounted for by the linear-response time-dependent density functional theory within the adiabatic approximation. Finally, we demonstrate the utility of the optimally tuned density functional approach by targeting the charge-transfer states of a large biomimetic model system for light-harvesting structures in Photosystem II.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-Equilibrium Plasma Interactions with Biomaterials, Biological Solutions and Tissues

Cold atmospheric pressure plasma discharges offer an abundant source of reactive oxygen and nitrogen species (RONS) at room temperature enabling unique interactions with biomaterials, biological solutions and tissues. These interactions particularly with living matter are presently an important intellectual frontier in plasma science with promising potential applications ranging from human health care to advanced biomaterial processing. Exciting case studies have been reported that illustrate the huge potential of cold atmospheric plasma technology in wound healing and cancer treatment. The interaction of plasma with conducting and dielectric biomaterials such as tissue strongly influences the plasma properties. In turn this changes the impact of the plasma on the biomaterial. Particularly in the case of living matter, liquid based solutions are ubiquitous which complicates interfacial processes. The lack of insight into the underlying mechanisms of the interaction of plasma with wounds and tumors is currently a bottleneck for the further development of the technology and gives rise to many interesting scientific questions. This project was focused on plasma properties and kinetics during plasma-biomaterial interactions. Both DC pulsed and RF driven atmospheric pressure plasma jets, extensively used by the plasma community were studied. The bio-interfaces included hydrogel as a tissue model, (saline) solutions, bacteria and virus. Plasma diagnostics used include Thomson scattering, Rayleigh scattering, Raman scattering, (two-photon absorption) laser induced fluorescence, optical emission spectroscopy, absorption spectroscopy, molecular beam mass spectrometry and fast imaging allowing to determine electron densities and temperatures, ionic species, reactive species including radicals, gas temperatures, gas composition, electric fields and solution components transferred to the gas phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Crystallization and Phase Transformations of Aluminum (Oxy)hydroxide Polymorphs in Caustic Aqueous Solution

Gibbsite, bayerite, and boehmite are important aluminum (oxy)hydroxide minerals in nature and have been widely deployed in various industrial applications. They are also major components in caustic nuclear wastes stored at various U.S. locations. Knowledge of their crystallization and phase transformation processes contributes to understanding their occurrence and could help optimize waste treatment processes. While it has been reported that partial conversion of bayerite and gibbsite to boehmite occurs in basic solutions at elevated temperatures, systematic studies of factors affecting the phase transformation as well as the underlying reaction mechanisms are non-existent, particularly in highly alkaline solutions. We explored the effects of sodium hydroxide concentrations (0.1~3 M), reaction temperature (60~100 ?) and aluminum concentrations (0.1~1 M) on the crystallization and transformation of these aluminum (oxy)hydroxides. Detailed structural and morphological characterization by X-ray diffraction (XRD), scanning electron microscopy (SEM), and nuclear magnetic resonance (NMR) spectrometry revealed that these processes depend largely on the reaction temperature and the Al/OH- ratio. When 1 = Al/OH- = 2.5, the reactions favor formation of high crystallinity precipitates, whereas at Al/OH- ratio ? 2.5 precipitation ceases unless the Al concentration is higher than 1 M. We identified pseudoboehmite, bayerite and gibbsite as intermediate phases to bayerite, gibbsite and boehmite, respectively, all of which transform via dissolution-reprecipitation. Gibbsite transforms to boehmite in both acidic and weak caustic environments at temperatures above 80 oC. However, a ‘bar-shaped’ gibbsite morphology dominates in highly caustic environments (3 M NaOH). The findings enable a robust basis for selection of various solid phases by tuning the reaction conditions.

aluminum (oxy)hydroxide polymorphs, crystallizatio↗