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At least 235 records · Page 13

Slip-free multiplication and complexity of dislocation networks in FCC metals

Abstract During plastic deformation of crystalline solids, intricate networks of dislocation lines form and evolve. To capture dislocation density evolution, prominent theories of crystal plasticity assume that 1) multiplication is driven by slip in active slip systems and 2) pair-wise slip system interactions dominate network evolution. In this work, we analyze a massive database of over 100 discrete dislocation dynamics simulations (with cross-slip suppressed), and our findings bring both of these assumptions into question. We demonstrate that dislocation multiplication is commonly observed on slip systems with no applied stress and no plastic strain rate, a phenomenon we refer to as slip-free multiplication. We show that while the formation of glissile junctions provides one mechanism for slip-free multiplication, additional mechanisms which account for the influence of coplanar interactions are needed to fully explain the observations. Unlike glissile junction formation which results from a binary reaction between a pair of slip systems, these new multiplication mechanisms require higher order reactions that lead to complex network configurations. While these complex configurations have not been given much attention previously, they account for about 50% of the line intersections in our database.

36 MATERIALS SCIENCE↗

Best Practices in PEC Water Splitting: How to Reliably Measure Solar-to-Hydrogen Efficiency of Photoelectrodes

Photoelectrochemical (PEC) water splitting, which utilizes sunlight and water to produce hydrogen fuel, is potentially one of the most sustainable routes to clean energy. One challenge to success is that, to date, similar materials and devices measured in different labs or by different operators lead to quantitatively different results, due to the lack of accepted standard operating procedures and established protocols for PEC efficiency testing. With the aim of disseminating good practices within the PEC community, we provide a vetted protocol that describes how to prepare integrated components and accurately measure their solar-to-hydrogen (STH) efficiency (η STH ). This protocol provides details on electrode fabrication, η STH test device assembly, light source calibration, hydrogen evolution measurement, and initial material qualification by photocurrent measurements under monochromatic and broadband illumination. Common pitfalls in translating experimental results from any lab to an accurate STH efficiency under an AM1.5G reference spectrum are discussed. A III–V tandem photocathode is used to exemplify the process, though with small modifications, the protocol can be applied to photoanodes as well. Dissemination of PEC best practices will help those approaching the field and provide guidance for comparing the results obtained at different lab sites by different groups.

08 HYDROGEN↗

LES and RANS Spray Combustion Analysis of OME 3-5 and n-Dodecane

Clean-burning oxygenated and synthetic fuels derived from renewable power, so-called e-fuels, are a promising pathway to decarbonize compression–ignition engines. Polyoxymethylene dimethyl ethers (PODEs or OMEs) are one candidate of such fuels with good prospects. Their lack of carbon-to-carbon bonds and high concentration of chemically bound oxygen effectively negate the emergence of polycyclic aromatic hydrocarbons (PAHs) and even their precursors like acetylene (C 2 H 2 ), enabling soot-free combustion without the soot-NO x trade-off common for diesel engines. The differences in the spray combustion process for OMEs and diesel-like reference fuels like n-dodecane and their potential implications on engine applications include discrepancies in the observed ignition delay, the stabilized flame lift-off location, and significant deviations in high-temperature flame morphology. For CFD simulations, the accurate modeling and prediction of these differences between OMEs and n-dodecane proved challenging. This study investigates the spray combustion process of an OME 3 − 5 mixture and n-dodecane with advanced optical diagnostics, Reynolds-Averaged Navier–Stokes (RANS), and Large-Eddy Simulations (LESs) within a constant-volume vessel. Cool-flame and high-temperature combustion were measured simultaneously via high-speed (50 kHz) imaging with formaldehyde (CH 2 O) planar laser-induced fluorescence (PLIF) representing the former and line-of-sight OH* chemiluminescence the latter. Both RANS and LES simulations accurately describe the cool-flame development process with the formation of CH 2 O. However, CH 2 O consumption and the onset of high-temperature reactions, signaled by the rise of OH* levels, show significant deviations between RANS, LES, and experiments as well as between n-dodecane and OME. A focus is set on the quality of the simulated results compared to the experimentally observed spatial distribution of OH*, especially in OME fuel-rich regions. The influence of the turbulence modeling is investigated for the two distinct ambient temperatures of 900 K and 1200 K within the Engine Combustion Network Spray A setup. The capabilities and limitations of the RANS simulations are demonstrated with the initial cool-flame propagation and periodic oscillations of CH 2 O formation/consumption during the quasi-steady combustion period captured by the LES.

CFD↗

Electronic Structure of Single-Atom Alloys and Its Impact on The Catalytic Activities

Single-atom alloys (SAAs) are promising materials for heterogeneous catalysis due to their unique structure and electronic properties. SAAs have active sites narrowed down to the single-atom level, which combines the advantages of alloy materials and single-site catalysts. Given the unique structural feature of SAAs, their electronic properties can be more flexibly tailored than for their monometallic counterparts, which can be used to effectively control their catalytic activities. One interesting feature commonly observed for SAAs is the lower density of state (DOS) near the Fermi level than their bulk references. Comparing with results for their monometallic bulk reference, the most noticeable electronic property change in SAAs is the narrowing of the valence band, which gives them free-atom-like character. Moreover, the d-band position of both single atoms and their host metals can show a pronounced shift. These changes of electronic structure in SAAs could largely affect the adsorption behavior of adsorbates during the catalytic processes. Close examination of the relationship between electronic structure and catalytic activity can provide useful guidance for rational design of new catalysts with improved performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High mass and halo resolution from fast low resolution simulations

Generating mocks for future sky surveys requires large volumes and high resolutions, which is computationally expensive even for fast simulations. Here we try to develop numerical schemes to calibrate various halo and matter statistics in fast low resolution simulations compared to high resolution N-body and hydrodynamic simulations. For the halos, we improve the initial condition resolution and develop a halo finder "relaxed-FoF", where we allow different linking lengths for different halo mass and velocity dispersions. We show that our relaxed-FoF halo finder improves the common statistics, such as halo bias, halo mass function, halo auto power spectrum, cross correlation coefficient with the reference halo catalog, and halo-matter cross power spectrum. We also calibrate small-scale velocities of small halos to improve the power spectrum in redshift space. For the matter statistics, we incorporate the potential gradient descent (PGD) method into fast simulations to improve the matter distribution at nonlinear scales. By building a lightcone output, we show that the PGD method significantly improves the weak lensing convergence tomographic power spectrum. With these improvements FastPM is comparable to the high resolution full N-body simulation of the same mass resolution, with two orders of magnitude fewer time steps. These techniques can be used to improve the halo and matter statistics of FastPM simulations for mock catalogs of future surveys such as DESI and LSST.

79 ASTRONOMY AND ASTROPHYSICS↗

Generalized Bayesian Framework for Evaluation of Integral Benchmark Experiments

A recently published generalized Bayesian optimization framework has provided a way to retract any or all of the three common assumptions underlying the conventional Generalized Linear Least Squares (GLLS) optimization method based on the concepts introduced in reference two. These assumptions are: 1. Perfection: The model used for data evaluation and the prior probability distribution function (PDF) of generalized* data are perfect; 2. Normality: The prior and posterior PDF are normal; and 3. Linearity: The model is linear. In this work we outline how the framework in 1 could be directly adopted for improved evaluation of nuclear criticality integral benchmark experiments (IBEs) by: 1. Removing the first assumption alone by utilizing the concept of imperfections introduced in 1 to enable evaluation in the presence of discrepancies between the data and model or of missing covariance information by a GLLS method that will be seen as a generalization of the conventional GLLS method employed by the TSURFER code, and by 2. Removing the remaining two assumptions by implement- ing a Markov Chain Monte Carlo method for computation of the posterior PDF in the SAMPLER code, where TSURFER and SAMPLER are the uncertainty quantification (UQ) codes for IBEs in the SCALE code system based on the GLLS, and the stochastic method, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Progress in development of characterization capabilities to evaluate candidate materials for direct air capture applications

As part of U.S. national efforts to combat the detrimental effect of global climate change, the National Institute of Standards and Technology (NIST) was recently tasked to support efforts in direct air capture (DAC) of carbon dioxide research and deployment. In order to develop test procedures, materials, and documentary standards, key characterization methods relevant to DAC materials have been investigated and used to identify desirable properties for a potential Standard Reference Material (SRM). Select amine-supported materials that previously showed potential for DAC applications have been characterized using commonly available laboratory methods. Further insights into the adsorption characteristics have been gained from developing and applying more specialized characterization tools ideal for probing low concentrations of carbon dioxide. A broad suite of capabilities that examine relevant properties under appropriate conditions gives the most profound insights into a material's specific performance. We advocate for even more specialized capabilities to be developed and standardized to quantitatively monitor the interactions of CO 2 with molecular species in complex and often disordered systems to advance DAC and support carbon dioxide reduction (CDR) in general.

carbon dioxide↗

Recent Improvements to the NWChem COSMO Module

This work presents recent developments in the COSMO solvation model implementation in NWChem. A new cavity construction approach, based on the solvent-excluding surface (SES) and utilizing the well-established GEPOL algorithm, has been introduced. Additionally, a straightforward procedure to merge surface segments that are too close─often a source of numerical artifacts─has been implemented. The available methods for correcting outlying surface charges have also been reviewed and improved. To validate the new implementation, we computed dielectric solvation energies for a chemically diverse set of approximately 100 molecules, including neutral species, small ions, and common ionic liquid components. Results were compared to those from GAMESS using the double-cavity method as a reference. Although the double-cavity approach can be regarded as more accurate, the simpler correction schemes available in NWChem─based on scaling factors or Lagrange multipliers─can achieve excellent agreement if the potential is also properly corrected, with mean unsigned deviations of around 0.15 kcal/mol. Predictions of typical vapor–liquid and liquid–liquid equilibria using a COSMO-SAC variant based on NWChem also showed very promising results.

Cavities↗

Artificial Intelligence for Data Center Operations (AI Ops)

HPC data centers such as the one at NREL's ESIF will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence (AI) and machine learning (ML) approaches provide the means to improve HPC data center efficiency (energy, operational, and managerial efficiency) and resiliency by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. The goal of coupled improvement of data center resiliency and energy efficiency through automated data collection and AI has led to a multi-year, multi-staged collaboration between NREL and Hewlett-Packard Enterprise's Advanced Technology Group, referred to as Artificial Intelligence for Data Center Operations (AIOps). The extended efforts within the AIOps project include a common goal of building capabilities for an advanced smart facility and demonstration of data collection and AI modeling techniques in the ESIF data center.

97 MATHEMATICS AND COMPUTING↗

Geodyn Material Library: Pseudocap models for dry porous tocks

This report describes the second edition of the Pseudocap Strength models for porous rocks implemented in GEODYN material library. The first model was developed in 2007 and calibrated for concrete. Then, the model parameters were calibrated based on triaxial tests reported for limestones and sandstones of various porosities. In these models some key parameters were chosen as functions of the reference porosity,Φ. Since then multiple modifications were implemented in the model, therefore, it has been recalibrated for some common porous materials such as limestones, sandstones, alluvium, tuffs and granite. Two types of models are described in this repot. The first type (called Pseudocap Model or PM) is for rocks from a specific location. Parameters were calibrated for several specific geologic materials. The second type (called Generic Pseudocap Model or GPM) is useful for the sites where only basic information (rock type, porosity) is available. Generic models include built-in correlations between porosities and other mechanical properties observed for certain rock types. The models of both types were validated by comparing not only to quasi-static triaxial tests for these materials but also to shock Hugoniot data and spherical explosion data for some materials. All models were derived in the frame of isotropic plasticity. They are designed to be used in explicit finite element/difference codes. Tangent stiffness tensor is not provided but can be calculated numerically for the model to be used in implicit finite element codes. For an isotropic material the stress can be decomposed into volumetric and deviatoric parts. The volumetric part is modeled using an Equation of state (EOS) which calculates the pressure and the bulk sound speed as functions of the internal specific energy and density. Here a simple, Mie-Gruneisen EOS is presented, but tabulated EOS (LEOS) provided by the library can be used as well. The stress is limited by the yield surface which depends on three invariants of the stress tensor and specific internal energy. In addition, to capture the strain-rate dependence a simple multiplier is used for the yield surface which depends on the equivalent plastic strain rate. The failure surface (the ultimate yield, Y f , defined later) is chosen in the Hoek-Brown form, commonly used in rock mechanics. It includes measurable parameters such as Unconfined Compressive Strength (UCS) as well as scale parameters characterizing the quality of the rock such as GSI (Geologic Strength Index). Thus, even though the model is calibrated for small samples it offers a way to extrapolate the strength to the field scale using geological characterization of the rock mass. The model captures effects of brittle-ductile transition in rocks by introducing a cap multiplier to the yield function. The rate of dilatancy (bulking) is proportional to the slope of the yield surface affected by the cap. Therefore, it takes place only at low confinements when the pressure is less than the brittle-ductile transition pressure, P BD . On the contrary, the porous compaction takes place at pressures higher than P BD . The cap moves as the porosity is compacted or new porosity is generated due to dilatancy. The porous compaction is modeled using an evolution equation which includes deviatoric stress so that the onset of compaction corresponds to the cap surface. The model captures effects of shear-enhanced compaction which is an important for porous rocks. Section 2 describes the modeling framework and Section 3 presents the model calibration procedure. Section 4 compares experimental data for various rocks versus model predictions. The model parameters used for this comparison are given in Appendix. The files with material constants are available with the latest GEODYN material library distribution.

58 GEOSCIENCES↗

CFM-ID 4.0: More Accurate ESI MS/MS Spectral Prediction and Compound Identification

In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compound-to-mass-spectrum prediction, and also one of the top tools for in silico mass-spectrum-to-compound identification. This work improves CFM-ID’s ability to predict ESI-MS/MS spectra from compounds by: (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions, in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a webservice and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid

Wang, Fei↗

Parallel Algorithms for Efficient Computation of High-Order Line Graphs of Hypergraphs

This paper considers structures of systems beyond dyadic (pairwise) interactions and investigates mathematical modeling of multi-way interactions and connections as hypergraphs, where captured relationships among system entities are set-valued. To date, in most situations, entities in a hypergraph are considered connected as long as there is at least one common ``neighbor''. However, minimal commonality sometimes discards the ``strength'' of connections and interactions among groups. To this end, considering the ``width'' of a connection, referred to as the \emph{$s$-overlap} of neighbors, provides more meaningful insights into how closely the communities or entities interact with each other. In addition, $s$-overlap computation is the fundamental kernel to construct the line graph of a hypergraph, a low-order approximation of the hypergraph which can carry significant information about the original hypergraph. Subsequent stages of a data analytics pipeline then can apply highly-tuned graph algorithms on the line graph to reveal important features. Given a hypergraph, computing the $s$-overlaps by exhaustively considering all pairwise entities can be computationally prohibitive. To tackle this challenge, we develop efficient algorithms to compute $s$-overlaps and the corresponding line graph of a hypergraph. We propose several heuristics to avoid execution of redundant work and improve performance of the $s$-overlap computation. Our parallel algorithm, combined with these heuristics, is orders of magnitude (more than $10\times$) faster than the naive algorithm in all cases and the SpGEMM algorithm with filtration in most cases (especially with large $s$ value).

hypergraph algorithms, graph algorithms, parallel ↗

Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme

Compressible density-based solvers are widely used in OpenFOAM, and the parallel scalability of these solvers is crucial for large-scale simulations. In this paper, we report our experiences with the scalability of OpenFOAM’s native rhoCentralFoam solver, and by making a small number of modifications to it, we show the degree to which the scalability of the solver can be improved. The main modification made is to replace the first-order accurate Euler scheme in rhoCentralFoam with a third-order accurate, four-stage Runge-Kutta or RK4 scheme for the time integration. The scaling test we used is the transonic flow over the ONERA M6 wing. This is a common validation test for compressible flows solvers in aerospace and other engineering applications. Numerical experiments show that our modified solver, referred to as rhoCentralRK4Foam, for the same spatial discretization, achieves as much as a 123.2% improvement in scalability over the rhoCentralFoam solver. As expected, the better time resolution of the Runge–Kutta scheme makes it more suitable for unsteady problems such as the Taylor–Green vortex decay where the new solver showed a 50% decrease in the overall time-to-solution compared to rhoCentralFoam to get to the final solution with the same numerical accuracy. Finally, the improved scalability can be traced to the improvement of the computation to communication ratio obtained by substituting the RK4 scheme in place of the Euler scheme. All numerical tests were conducted on a Cray XC40 parallel system, Theta, at Argonne National Laboratory.

Li, Sibo↗

Comprehensive analysis of common polymers using hyphenated TGA-FTIR-GC/MS and Raman spectroscopy towards a database for micro- and nanoplastics identification, characterization, and quantitation

Environmental contamination by micro- and nanoplastics (MNPs) is well documented with potential for their increased accumulation globally. Growing public concern over environmental, ecological, and human exposure to MNPs has led to exponential increase in publications, news articles, and reports. Significant knowledge gap exists in standardized analytical methods for the identification and quantification of MNPs from real world environmental samples. Here, in this study, we report comprehensive datasets utilizing thermogravimetric analyzer (TGA) coupled to a Fourier transformed infrared spectrometer (FTIR) and a gas chromatography/mass spectrometer (GC/MS) with corresponding Raman spectral data for the most common polymers documented to be present in the environment (35 plastics of 12 polymer types), to serve as a base line reference for the identification and quantitation of MNPs. Various parameters for TGA-FTIR-GC/MS data acquisition were optimized. Commercial consumer plastic product compositions were identified using this analytical database. Case studies to showcase the utility of the method for polymer mixtures analysis is included. This dataset would serve towards the development of a collaborative, global, comprehensive, and curated public database for the identification of various MNPs and mixtures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders

We report the design/discovery of new materials is highly nontrivial owing to the near-infinite possibilities of material candidates and multiple required property/performance objectives. Thus, machine learning tools are now commonly employed to virtually screen material candidates with desired properties by learning a theoretical mapping from material-to-property space, referred to as the forward problem. However, this approach is inefficient and severely constrained by the candidates that the human imagination can conceive. Thus, in this work on polymers, we tackle the materials discovery challenge by solving the inverse problem: directly generating candidates that satisfy desired property/performance objectives. We utilize syntax-directed variational autoencoders (VAE) in tandem with Gaussian process regression (GPR) models to discover polymers expected to be robust under three extreme conditions: (1) high temperatures, (2) high electric field, and (3) high temperature and high electric field, useful for critical structural, electrical, and energy storage applications. This approach to learn from and augment) human ingenuity is general and can be extended to discover polymers with other targeted properties and performance measures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Si impurities on microstructure and tensile properties of a cast Al-Mg-Fe alloy

Al-Mg alloys are attractive for structural castings owing to their superior strength and ductility in the as-cast state. However, given the tight tolerance for impurities, Al-Mg alloys produced from secondary sources still face multiple challenges. Here, we report the effect of increased Si impurity (0.05–1.6 wt%), which is commonly found in secondary Al sources, on microstructure and tensile properties of a cast Al-4.3Mg-1.6Fe (wt%) alloy, commercially referred to as Castaduct-42 alloy. Microstructural characterization revealed that Si addition increased the volume fraction, size, and aspect ratio of primary Al13Fe4 intermetallic particles as well as the volume fraction of other binary and ternary eutectic phases. Tensile testing results demonstrated that increasing Si impurities from 0.05 to 1.6 wt% reduced ductility from 14.3 ± 1.4 % to 2.2 ± 1.0 %. A particle cracking damage accumulation model coupled with failure analysis indicated primary Al13Fe4 intermetallic particles to be the major contributing factor to the deterioration in ductility with increasing Si content. Additionally, the stabilizing effect of Si on primary Al 13 Fe 4 was inconsistent with the CALPHAD calculation results based on existing CALPHAD databases which predict a slightly decreasing primary Al13Fe4 phase fraction with increasing Si concentration. This work provides new insights into the phase stability and mechanical behavior of the lesser studied Al-Mg-Fe-Si alloy system that will contribute to the development of sustainable cast Al-Mg based alloys.

36 MATERIALS SCIENCE↗

Expanding the Scope of Commercial Opportunities for Investor-Owned Electric Utilities

Technological advances and a more engaged customer population are pushing utilities and their regulators towards new strategies that promote growth and transformation. Common to many of these efforts is an interest in expanding the set of profit-generating product and service offerings, hereafter referred to as alternative commercial opportunities, beyond just buying and selling electricity. Prior work has focused on specific categories and types of alternative commercial opportunities and in specific market segments. The report fills an important gap in the literature in two ways. First, we develop a comprehensive taxonomy to categorize the alternative commercial opportunities and provide numerous examples within each category. Second, we identify six issues that regulators may want or need to address when determining if and how investor-owned electric utilities pursue these commercial opportunities. The work is intended to inform regulators and decision-makers about how to navigate these broader reform opportunities, as well as rationalize their response within the context of their state policy strategy and in comparison to their peers in other states.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hydrothermal solution calorimetry in acidic aqueous solutions and revisiting the standard partial molal thermodynamic properties of Nd 3+ from 25 to 300 °C

The mobility of rare earth elements (REE) can be predicted in aqueous fluids using geochemical modeling but the accuracy of these models strongly depends on the availability of robust thermodynamic properties for the REE aqueous species. The REE 3+ aqua ions are important in the derivation of the formation constants of all the major REE complexes including the chloride, sulfate, and fluoride species which predominate in many hydrothermal-magmatic systems. However, the thermodynamic properties of the REE 3+ aqua ions are still commonly derived from the Helgeson-Kirkham-Flowers (HKF) equation of state parameters tabulated several decades ago. The standard state thermodynamic properties at reference conditions (25 °C and 1bar) and their extrapolations to high temperature need to be verified, if not revised, based on hydrothermal experiments. In this study, the enthalpy of solution was measured for synthetic Nd hydroxide from 25 to 150 ºC to retrieve the standard partial molal thermodynamic properties of Nd 3+ as a function of temperature. The experiments were conducted in aqueous perchloric acid based solutions with starting pH of 2 and varying ionic strength (0.01 to 0.09 mol/kg NaClO 4 ). The standard partial molal enthalpy of formation (Δ f H°) of Nd 3+ derived from the experimental study displays differences of up to 10 kJ/mol compared to the enthalpy values derived from the HKF equation of state in the studied temperature range. These inaccuracies are resolved by adjusting the standard partial molal Gibbs energy of formation (Δ f G°) of Nd 3+ at 25 °C and 1 bar from -672.0 to -679.7 kJ/mol. The heat capacity function (C p °) derived between 25 and 150 ºC can be described by: C p ° = a 0 + a 1 ·T + a 2 ·T -2 , with a 0 = 1256, a 1 = -2.68, a 2 = -55.56·10 6 and T in Kelvin. A set of recommended thermodynamic properties is provided for the Nd 3+ aqua ions and corrections are provided for the chloride and fluoride species to remain internally consistent with the experimentally derived properties. These results allow predicting accurately the solubility of monazite between 25 and 300 ºC. Before these corrections, the properties for the Nd 3+ aqua ions derived from the HKF parameters resulted in up to ~1.5 orders of magnitude lower monazite solubility than determined experimentally. Here, a revision of the REE +3 aqua ions properties is necessary to accurately predict the mobility of REE in hydrothermal acidic solutions.

58 GEOSCIENCES↗