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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Predictions of core plasma performance for the SPARC tokamak

SPARC is designed to be a high-field, medium-size tokamak aimed at achieving net energy gain with ion cyclotron range-of-frequencies (ICRF) as its primary auxiliary heating mechanism. Empirical predictions with conservative physics indicate that SPARC baseline plasmas would reach $\textit{Q}$ ≈ 11, which is well above its mission objective of $\textit{Q}$ > 2. To build confidence that SPARC will be successful, physics-based integrated modelling has also been performed. The TRANSP code coupled with the theory-based trapped gyro-Landau fluid (TGLF) turbulence model and EPED predictions for pedestal stability find that $\textit{Q}$ ≈ 9 is attainable in standard H-mode operation and confirms $\textit{Q}$ > 2 operation is feasible even with adverse assumptions. In this analysis, ion cyclotron waves are simulated with the full wave TORIC code and alpha heating is modelled with the Monte–Carlo fast ion NUBEAM module. Detailed analysis of expected turbulence regimes with linear and nonlinear CGYRO simulations is also presented, demonstrating that profile predictions with the TGLF reduced model are in reasonable agreement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Divertor heat flux challenge and mitigation in SPARC

Owing to its high magnetic field, high power, and compact size, the SPARC experiment will operate with divertor conditions at or above those expected in reactor-class tokamaks. Power exhaust at this scale remains one of the key challenges for practical fusion energy. Based on empirical scalings, the peak unmitigated divertor parallel heat flux is projected to be greater than 10 GW m -2 . This is nearly an order of magnitude higher than has been demonstrated to date. Furthermore, the divertor parallel Edge-Localized Mode (ELM) energy fluence projections (~11–34 MJ m -2 ) are comparable with those for ITER. However, the relatively short pulse length (~25 s pulse, with a ~10 s flat top) provides the opportunity to consider mitigation schemes unsuited to long-pulse devices including ITER and reactors. The baseline scenario for SPARC employs a ~1 Hz strike point sweep to spread the heat flux over a large divertor target surface area to keep tile surface temperatures within tolerable levels without the use of active divertor cooling systems. In addition, SPARC operation presents a unique opportunity to study divertor heat exhaust mitigation at reactor-level plasma densities and power fluxes. Not only will SPARC test the limits of current experimental scalings and serve for benchmarking theoretical models in reactor regimes, it is also being designed to enable the assessment of long-legged and X-point target advanced divertor magnetic configurations. Experimental results from SPARC will be crucial to reducing risk for a fusion pilot plant divertor design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

ARC physics basis–magnetohydrodynamics

ARC is designed to produce 400 ⁢MW of net electricity and prove the commercial feasibility of a fusion power plant. In order to achieve this goal ARC has to operate with optimal core performance in a stationary scenario that minimises wear on the first wall and divertor. This requires avoiding or mitigating magnetohydrodynamic (MHD) instabilities which have the potential to not only degrade the plasma core but also lead to deleterious transient heat loads on plasma facing components. Therefore, this work aims at characterising the MHD stability of the high performance ARC scenario and inform the design of error field correction coils. Firstly, simulations of vertical displacement events show that an in-vessel coil is not needed and instead the poloidal shaping coils can be used to control vertical stability. These simulations also inform the demands on the corresponding coil power supplies. Stability analysis of the ideal kink mode with or without a conducting wall and kinetic effects suggests that the ARC baseline scenario operates deeply in the stable region. Using RDCON, tearing modes at the 𝑚/𝑛 =2/1 and 3/2 surfaces (with poloidal mode number 𝑚, and toroidal mode number 𝑛) are shown to be linearly stable, and including thermal transport effects in the rational surfaces lead to further stabilisation. However, other transient plasma instabilities can seed neoclassical tearing modes (NTMs). The marginally stable width of NTMs in ARC strongly depends on the internal inductance and can fall below 0.1% of the normalised poloidal flux. Furthermore, an empirical cross-machine model of the 𝑛 =1 error field leading to a disruption predicts a critical error field larger than SPARC but smaller than ITER. Three-dimensional coils can be designed with the Generalised Purturbed Equilbium Code based on a simple model that calculates the maximum correctable error field that is limited by the neoclassical toroidal viscosity torque. Broad scans of different coil geometries identify a set of 2 rows of off-midplane coils to be a suitable solution. It is also determined that such a set of three-dimensional coils is capable of correcting 𝑛 =2 error fields to some degree and creating strong enough 𝑛 =2 or 𝑛 =3 edge resonant perturbation fields for the suppression of edge-localised modes at reasonable coil currents. The final design of the first ARC will be further informed by results from SPARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Overview of the physics basis for the ARC fusion power plant

Commonwealth Fusion Systems plans to build ARC as the first fusion power plant at a site in Chesterfield County, Virginia, USA by the early 2030s. We present an overview of analysis comprising the physics basis of the ARC V3A design, a high-magnetic-field tokamak with 𝐵 0 =11.4 T, 𝐼 𝑝 =12.0 MA, 𝑅 0 =4.62 m, 𝑎 =1.18 m. ARC V3A is designed to produce 𝑃 𝑓⁡𝑢⁢𝑠 ≈1.13 GW DT fusion power and deliver ⩾400 MW net electric power to the grid. This overview includes quantitative analysis of fundamental issues for design of and operational plasma scenarios for a tokamak power plant, and lays out the design targets and strategic choices for ARC, including empirical fusion performance projections, assessment of H-mode access, ion cyclotron resonance heating simulations, alpha particle physics and time-dependent full-pulse simulations. This is complemented by topical papers on fusion performance and transport, disruption physics, boundary physics and magnetohydrodynamic stability. Critically, these studies identify key model uncertainties and physics risks to be retired through SPARC operation. Due to the modular nature of ARC, early results from SPARC can be incorporated into the design of the first ARC as well as subsequent replacements of the ARC vacuum vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Learning and meta-learning of stochastic advection–diffusion–reaction systems from sparse measurements

Physics-informed neural networks (PINNs) were recently proposed in [18] as an alternative way to solve partial differential equations (PDEs). A neural network (NN) represents the solution, while a PDE-induced NN is coupled to the solution NN, and all differential operators are treated using automatic differentiation. Here, we first employ the standard PINN and a stochastic version, sPINN, to solve forward and inverse problems governed by a non-linear advection–diffusion–reaction (ADR) equation, assuming we have some sparse measurements of the concentration field at random or pre-selected locations. Subsequently, we attempt to optimise the hyper-parameters of sPINN by using the Bayesian optimisation method (meta-learning) and compare the results with the empirically selected hyper-parameters of sPINN. In particular, for the first part in solving the inverse deterministic ADR, we assume that we only have a few high-fidelity measurements, whereas the rest of the data is of lower fidelity. Hence, the PINN is trained using a composite multi-fidelity network, first introduced in [12], that learns the correlations between the multi-fidelity data and predicts the unknown values of diffusivity, transport velocity and two reaction constants as well as the concentration field. For the stochastic ADR, we employ a Karhunen–Loève (KL) expansion to represent the stochastic diffusivity, and arbitrary polynomial chaos (aPC) to represent the stochastic solution. Correspondingly, we design multiple NNs to represent the mean of the solution and learn each aPC mode separately, whereas we employ a separate NN to represent the mean of diffusivity and another NN to learn all modes of the KL expansion. For the inverse problem, in addition to stochastic diffusivity and concentration fields, we also aim to obtain the (unknown) deterministic values of transport velocity and reaction constants. The available data correspond to 7spatial points for the diffusivity and 20 space–time points for the solution, both sampled 2000 times. We obtain good accuracy for the deterministic parameters of the order of 1–2% and excellent accuracy for the mean and variance of the stochastic fields, better than three digits of accuracy. In the second part, we consider the previous stochastic inverse problem, and we use Bayesian optimisation to find five hyper-parameters of sPINN, namely the width, depth and learning rate of two NNs for learning the modes. Here, we obtain much deeper and wider optimal NNs compared to the manual tuning, leading to even better accuracy, i.e., errors less than 1% for the deterministic values, and about an order of magnitude less for the stochastic fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Toward a First-Principles Framework for Predicting Collective Properties of Electrolytes

Conspectus Given the universal importance of electrolyte solutions, it is natural to expect that we have a nearly complete understanding of the fundamental properties of these solutions (e.g., the chemical potential) and that we can therefore explain, predict, and control the phenomena occurring in them. In fact, reality falls short of these expectations. But, recent advances in the simulation and modeling of electrolyte solutions indicate that it should soon be possible to make progress toward these goals. In this Account, we will discuss the use of first-principles interaction potentials based in quantum mechanics (QM) to enhance our understanding of electrolyte solutions. Specifically, we will focus on the use of quantum density functional theory (DFT) combined with molecular dynamics simulation (DFT-MD) as the foundation for our approach. The overarching concept is to understand and accurately reproduce the balance between local or short-ranged (SR) structural details and long-range (LR) correlations, allowing the prediction of the thermodynamics of both single ions in solution as well as the collective interactions characterized by activity/osmotic coefficients. In doing so, relevant collective motions and driving forces characterized by chemical potentials can be determined. Here, in this Account, we will make the case that understanding electrolyte solutions requires a faithful QM representation of the SR nature of the ion–ion, ion–water, and water–water interactions. However, the number of molecules that is required for collective behavior makes the direct application of high-level QM methods that contain the best SR physics untenable, making methods that balance accuracy and efficiency a practical goal. Alternatives such as continuum solvent models (CSMs) and empirically based classical molecular dynamics have been extensively employed to resolve this problem but without yet overcoming the fundamental issue of SR accuracy. We will demonstrate that accurately describing the SR interaction is imperative for predicting both intrinsic properties, namely, at infinite dilution, and collective properties of electrolyte solutions. DFT has played an important role in our understanding of condensed phase systems, e.g., bulk liquid water, the air–water interface, ions in bulk, and at the air–water interface. This approach holds huge promise to provide benchmark calculations of electrolyte solution properties that will allow for the development and improvement of more efficient methods, as well as an enhanced understanding of fundamental phenomena. However, the standard protocol using the generalized gradient approximation with van der Waals (vdW) correction requires improvement in order to achieve a high level of quantitative accuracy. Simply simulating with higher level DFT functionals may not be the best route considering the significant computational cost. Alternative methods of incorporating information from higher levels of QM should be explored; e.g., using force matching techniques on small clusters, where high level benchmark calculations are possible, to develop ideal correction terms to the DFT functional is a promising possibility. We argue that DFT with statistical mechanics is becoming an increasingly useful framework enabling the prediction of collective electrolyte properties.

Duignan, Timothy T.↗
DOE OSTI2026

Molecular Programming of Diorganyl Dichalcogenides for Rational Nanocrystal Design

Soft-chemistry nanocrystal synthesis leverages low-temperature, solution-phase reactions to access materials that can be kinetically stabilized rather than thermodynamically favored. Under such mild conditions, reaction pathways are governed not only by precursor composition but also by the molecular details that dictate how reactive atomic species are generated and delivered. Furthermore, harnessing this kinetic sensitivity offers a powerful opportunity: by deliberately programming precursor reactivity, nanocrystal composition, structure, and morphology can be rationally designed rather than empirically discovered.

Chalcogenides↗
DOE OSTI2023

Evaluating Retention Index Score Assumptions to Refine GC–MS Metabolite Identification

As metabolomics grows into a high-throughput and high demand research field, current metrics for the identification of small molecules in gas chromatography–mass spectrometry (GC–MS) still require manual verification. Though steps have been taken to improve scoring metrics by combining spectral similarity (SS) and retention index (RI), the problem persists. A large body of literature has analyzed and refined SS scores, but few studies have explicitly studied improvements to RI scores. Here, in this study, we examined whether uninvestigated assumptions of the RI score are valid and propose ways to improve them. Query RIs were matched to library RI with a generous window of ±35 to avoid unintentional removal of valid compound identifications. Each match was manually verified as a true positive (TP), true negative, or unknown. Metabolites with at least 30 TP identifications were included in downstream analyses, resulting in a total of 87 metabolites from samples of varying complexity and type (e.g., amino acid mixtures, human urine, fungal species, and so on.). Our results showed that the RI score assumptions of normality, consistent variance across metabolites, and a mean error centered at 0 are often violated. We demonstrated through a cross-validation analysis that modifying these underlying assumptions according to empirical metabolite-specific distributions improved the TP and negative rankings. Further, we statistically determined the minimum number of samples required to estimate distributional parameters for scoring metrics. Overall, this work proposes a robust statistical pipeline to reduce the time bottleneck of metabolite identification by improving RI scores and thus minimize the effort to complete manual verification.

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

Tunable Atomic Layer Deposition into Ultra-High-Aspect-Ratio (>60000:1) Aerogel Monoliths Enabled by Transport Modeling

Atomic layer deposition (ALD) modification of ultra-high-aspect-ratio structures (>10,000:1) is a powerful platform with applications in catalysis, filtration, and energy conversion. However, the deposition of conformal and tunable ALD coatings at these aspect ratios remains challenging, resulting in empirical tradeoffs between precursor utilization and reaction time. Here, we demonstrate tunable control of the ALD infiltration depth into an aerogel monolith (AM) and develop a reaction-diffusion model to accurately describe the coating process. Specifically, we investigate the ALD exposure time and precursor dose needed to conformally coat a silica AM with pore sizes of ~20 nm, a monolith thickness of ~2.5 mm, and aspect ratios exceeding 60,000:1. We demonstrate complete infiltration into the AM, which is quantified by elemental mapping. A reaction-diffusion model is developed, which accounts for multiple doses and precursor depletion in the ALD chamber during an exposure step. The experimentally validated model enables the prediction and tuning of infiltration depth into a tortuous, high-aspect-ratio structure such as an AM, allowing for the synthesis of rationally designed material architectures. Additionally, the model allows for co-optimization of the total deposition time and percentage of unreacted precursor, which are important for the manufacturability and sustainability of ALD processing. Lastly, we demonstrate that ultra-thin ALD Al 2 O 3 coatings can be used to stabilize silica AMs against structural degradation under high-temperature annealing conditions (700-800 °C), by limiting changes in surface area and monolith volume. As a result, this improved high-temperature stability has implications for numerous aerogel applications, including catalysis and thermal insulation.

14 SOLAR ENERGY↗
DOE OSTI2022

Size Dependent Optical Properties and Structure of ZnS Nanocrystals Prepared from a Library of Thioureas

Here, ZnS nanocrystals (λ max (1S e -1S 3/2h ) = 260 - 320 nm, d = 1.7 - 10.0 nm) are synthesized from Zn(O 2 CR) 2 (O 2 CR = tetra-decanoate, oleate and 2-hexyldecanoate), N,N'-disubstituted and N,N',N'-trisubstituted thioureas, and P,P,N-trisubstituted phos-phanecarbothioamides. The influence of precursor substitution, ligand sterics, and reaction temperature on the final nanocrystal size were evaluated. By using saturated hydrocarbon solvents and saturated aliphatic carboxylate ligands, polymeric byproducts could be avoided and pure ZnS nanocrystals isolated. Elevated temperatures, slower precursor conversion reactivity and branched zinc 2-hexyldecanoate yield the largest ZnS nanocrystals. Carefully purified zinc carboxylate, rapidly converting precursors, and cooling the synthesis mixture following complete precursor conversion provide quasi spherical nanocrystals with the narrowest shape dispersity. Nanocrystal sizes were measured using pair distribution function (PDF) analysis of X-ray scattering and scanning transmission electron microscopy (STEM) and plotted versus the energy of their first excitonic optical absorption. The resulting empirical relationship provides a useful method to characterize the nanocrystal size from 1.7-4.0 nm using optical absorption spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Energy Transfer Mechanisms in Large Low-Bandgap Polymers from Time-Resolved Experiments and Nonadiabatic Molecular Dynamics Calculations

Conjugated polymers offer unprecedented chemical tunability for modulating energy transfer in a multitude of infrared light applications. In this work, we use a combination of time-resolved spectroscopic experiments and nonadiabatic molecular dynamics calculations to probe the photochemistry and nonradiative transitions in a recently synthesized narrow bandgap donor–acceptor conjugated polymer based on alternating cyclopentadithiophene and electronegative benzothiadiazole heterocycles. Using large-scale semi-empirical nonadiabatic molecular dynamics, which can treat a large 260-atom hexamer, we calculate an S 5 → S 1 lifetime of 34.75 fs, which is consistent with our time-resolved spectroscopic data. Our simulations suggest that vibronic motions of the central carbons in the cyclopentadithiophene functional groups are predominantly involved in the nonradiative transitions, and the excitation becomes more localized on a monomer fragment over time. The combined use of time-resolved experiments and nonadiabatic molecular dynamics calculations in this work provides mechanistic insight into chemical functionalities that can be tuned to enhance energy transfer in other prospective low-bandgap polymer materials.

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

Relationship between Sodium Content and Copper Activity for High Voltage Stability in O3-Type Layered Oxide Cathodes

Layered oxides with an O3 framework have attracted attention as cathode materials for sodium-ion batteries due to their high discharge capacity. Yet they are hampered for commercialization by poor cyclability due to structural instability during the sodium (de)intercalation process. The introduction of Cu in small fractions to the transition metal layers has been empirically observed to improve reversible specific capacity and cycling stability. Understanding the redox activity of Cu in O3-type Na x TMO 2 materials is crucial, as it could directly influence the charge compensation mechanism, voltage profile, and structural stability. However, the precise role of Cu in O3-type sodium cathodes under high-voltage cycling conditions (>4.1 V) remains insufficiently understood. To close this gap of knowledge, we studied the effect of Cu in two representative layered oxides with the same O3 stacking but different sodium stoichiometry, Na 0.9 Mn 1/2 Fe 1/3 Cu 1/6 O 2 and NaMn 1/2 Fe 1/3 Cu 1/6 O 2 . X-ray spectroscopy reveals that in Na 0.9 Mn 1/2 Fe 1/3 Cu 1/6 O 2 , Cu exhibits dual redox activity, Cu + /Cu 2+ in the pristine state and Cu 2+ /Cu 3+ upon charging in the sodium-deficient material, whereas only the Cu + /Cu 2+ redox couple is observed in the fully stoichiometric layered oxide. Furthermore, the results indicate that even a slight deficiency in sodium can significantly impact the electrochemical performance and material stability and alter the elemental redox activity of Cu.

Batteries↗
DOE OSTI2020

Structural Tolerance Factor Approach to Defect-Resistant I 2 -II-IV-X 4 Semiconductor Design

Recent work on quaternary semiconductors Cu 2 BaSn(S,Se) 4 and Ag 2 BaSnSe 4 for photovoltaic and thermoelectric applications, respectively, has shown the promise of exploring the broader family of defect-resistant I 2 -II-IV-X 4 materials (where I, II, and IV refer to the formal oxidation state of the metal cations and X is a chalcogen anion) with tetrahedrally coordinated I/IV cations and larger II cations (i.e., Sr, Ba, Pb, and Eu) for optoelectronic and energy-related applications. Chemical dissimilarity among the II and I/IV atoms represents an important design motivation because it presents a barrier to antisite formation, which otherwise may act as electronically harmful defects. We herein show how all 31 experimentally reported I 2 -II-IV-X 4 examples (with large II cations and tetrahedrally coordinated smaller I/IV cations), which form within five crystal structure types, are structurally linked. Based on these structural similarities, we derive a set of tolerance factors that serve as descriptors for phase stability within this family. Despite common usage in the well-studied perovskite system, Shannon ionic radii are found to be insufficient for predicting metal–chalcogen bond lengths, pointing to the need for experimentally derived correction factors as part of an empirically driven learning approach to structure prediction. Here, we use the tolerance factors as a predictive tool and demonstrate that four new I 2 -II-IV-X 4 compounds, Ag 2 BaSiS 4 , Ag 2 PbSiS 4 , Cu 2 PbGeS 4 , and Cu 2 SrSiS 4 , can be synthesized in correctly predicted phases. One of these compounds, Ag 2 PbSiS 4 , shows potentially promising optoelectronic properties for photovoltaic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Flue Gas Desulfurization Wastewater Composition and Implications for Regulatory and Treatment Train Design

The U.S. Environmental Protection Agency is currently revising its regulations on trace element discharges from flue gas desulfurization (FGD) wastewater.<br>In this work, we expand a predictive model of trace element behavior at coal-fired power plants (CFPPs) to estimate the trace element concentration of FGD wastewater at the plant level. We demonstrate that variation in trace element concentrations in FGD wastewater can span several orders of magnitude and is a function of both coal rank and installed air pollution control devices. This conclusion suggests that the benefits and costs of FGD wastewater treatment for the median plant will poorly describe the actual benefits and costs over the full range of existing CFPPs.

Mauter, Meagan↗
DOE OSTI2021

Prediction of the Thermal Runaway Limit and Optimal Operation of Heat Transfer-Limited, Fixed-Bed Reactor Systems

Here, we derive a new prediction for thermal runaway starting from the alpha model for fixed-bed reactor systems. This method accounts for thermal resistance internal to the reactor tube and the radial temperature gradients that result. To showcase our method, we compare its predictions to other common criteria for thermal runaway using o-xylene oxidation as the example chemistry. Even in systems where internal heat transfer is negligible, the empirical practical design criterion for thermal runaway is inaccurate. For cases where internal heat transfer is relevant, our runaway limit is more stringent than limits derived from simpler 1-D models. To augment our work, we optimize the product yield with the thermal runaway constraint using orthogonal collocation. Using the alpha model, the results illustrate that the thermal runaway limit can be accurately determined using either numerical or analytical methods.

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

Solvent Selection for the Separation of Lignin-Derived Monomers Using the Conductor-like Screening Model for Real Solvents

The separation of desired monomers from a liquid-phase mixture of lignin depolymerization products is necessary to facilitate their upscaling and upgrading for industrial applications. One effective method to separate multiple liquid-phase products is countercurrent chromatography (CCC), which is a common liquid chromatography technique that separates target solutes based on differences in their partitioning in a biphasic solvent system. Effective CCC separation requires the selection of solvent compositions to tune solute partition coefficients. Here, to alleviate the experimental burden of selecting optimal solvent systems, we apply the conductor-like screening model for real solvents (COSMO-RS) method to compute partition coefficients of representative lignin monomers from four currently used depolymerization strategies in standard solvent systems. We further design new ternary and quaternary solvent systems that are predicted to further improve separation efficacy. On the basis of these predicted partition coefficients and empirical solvent selection criteria for CCC measurements, we suggest a range of solvent systems that would be suitable for the effective separation of aromatic lignin-derived products via CCC or similar liquid–liquid extraction methods.

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

Thermodynamics of CeSiO 4 : Implications for Actinide Orthosilicates

Zircon (ZrSiO 4 : I4 1 /amd) can accommodate actinides, such as thorium, uranium, and plutonium. The zircon structure has been determined for several of the end member compositions of other actinides, such as plutonium and neptunium. However, the thermodynamic properties of these actinide zircon structure-types are largely unknown due to the difficulties in synthesizing these materials and handling transuranium actinides. Thus, we have completed a thermodynamic study of cerium orthosilicate, stetindite (CeSiO 4 ), a surrogate of PuSiO 4 . For the first time, the standard enthalpy of formation of CeSiO 4 was obtained by high temperature oxide melt solution calorimetry to be -1971.9 ± 3.6 kJ/mol. Stetindite is energetically metastable with respect to CeO 2 and SiO 2 by 27.5 ± 3.1 kJ/mol. The metastability explains the rarity of the natural occurrence of stetindite and the difficulty of its synthesis. Applying the obtained enthalpy of formation of CeSiO 4 from this work, along with those previously reported for USiO 4 and ThSiO 4 , we developed an empirical energetic relation for actinide orthosilicates. Here, the predicted enthalpies of formation of AnSiO 4 are then made with a discussion of future strategies to efficiently immobilize Pu or minor actinides in the zircon structure.

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

Mechanisms of Al3+ dimerization in alkaline solutions

The molecular speciation of aluminum (Al3+) in alkaline solutions is fundamental to its precipitation chemistry within a number of industrial applications that include ore renement and industrial processing of Al wastes. Under these conditions, Al3+ is predominantly Al(OH) {4 , while at high [Al] dimeric species also known to form. To date, the mechanism of dimer formation remains unclear and it is likely infuenced by complex ion ion interactions. In the present work, we investigate the role of ion pairing and a suite of potential dimerization pathways using a three-pronged approach that consists of density functional theory-based molecular dynamics (DFTMD), static DFT calculations (sDFT) and semi-empirical density functional tight binding molecular dynamics (SEMD). Specic cation eects imparted by the background electrolyte cations Na+, Li+ and K+ have been examined. Our simulations predict that when the Al species are ion paired with either cation the formation of the oxo-bridged Al2O(OH) 2{6 is favored with respect to the dihydroxo-bridged Al2(OH) 2{8 , in agreement with previousspectroscopic work. The formation of both dimers rst proceeds by bridging of two monomeric units via one hydroxo ligand, leading to a labile Al2(OH) 2{8 isomer. The eect of contact ion pairing of Li+ and K+ on the dimerization energetics is distinctly more favorable than that of Na+, which may have an impact on further ligomerization.

Pouvreau, Maxime↗