Rare earth elements recovery using staged precipitation from a leachate generated from coarse coal refuse
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Energy & Fuels↗
SEARCH · Engineering Papers
Results for “PRECIPITATION”
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Effect of the thermionic emission on the recombination and electron beam induced current contrast at the interface of a metallic precipitate embedded in a semiconductor matrix
The barrier height and the recombination velocity at the interface between a metallic precipitate and a semiconductor matrix are investigated with a new self consistent procedure based both on the analysis of the recombination and emission balance rates for electrons and holes and on the determination of the size-dependent electronic structure of the embedded precipitate. In the present work, the precipitate is modeled within the spherical well potential framework. The main result is the dependence of the recombination features on the electronic structure of the metal precipitate unlike the models based only on the Shockley-Read-Hall theory. The behaviors of the surface charge density on the metallic precipitate and the barrier height versus the precipitate size are similar to our previous studies. Unlike previous works, the recombination velocity reaches a constant non-zero value for sizes smaller than a critical size which is dependent on the defect concentration at the interface. The new dependencies of the recombination parameters are illustrated by the calculation of the electron beam induced current (EBIC) contrast at the interface.
36 MATERIALS SCIENCE↗
Improved Estimates of Pentad Precipitation through the Merging of Independent Precipitation Datasets
Three independent, quasi-global, gridded datasets of precipitation (a rain gauge-based dataset, the satellite-only component of the NASA Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission [IMERG] Final Run precipitation product, and precipitation estimates derived from NASA Soil Moisture Active Passive [SMAP] soil moisture retrievals), are objectively combined into a single pentad precipitation dataset at 36-km resolution using a unique approach based on extended triple collocation. The quality of each of the four datasets is then evaluated against independent observations. When a global land surface model at 36-km resolution is integrated four times, once utilizing the merged precipitation forcing and once with each of the three contributing datasets, the near-surface soil moisture variations produced with the merged forcing validate best against independent satellite-based soil moisture fields. In addition, the merged dataset is found to be more consistent, relative to each contributor, with estimates of air temperature variations across the globe. The merged dataset thus appears to draw successfully on the complementary strengths of each contributor: the particularly high quality of the rain gauge-based dataset in areas of high gauge density, the more uniform accuracy across the globe of the IMERG data, and the moderate accuracy, particularly in semi-arid regions, of the soil moisture retrieval-based data. Plain Language Summary Obtaining measurements of precipitation across the globe can be challenging. Rain gauges in some ways provide the most accurate measurements, but gauges are absent in many parts of the world, and even where they exist, they only measure precipitation at the gauge itself and therefore may not provide an accurate large-scale average. Satellite-based estimates of precipitation largely overcome these problems, but such data have their own issues, notably a “snapshot” (rather than a time-average) character of the measurements and difficulty associated with interpreting the measured radiances in the presence of complex land surfaces. In the present paper, we use a novel approach to generate a “merged” dataset, one that optimally combines the gauge precipitation information and the satellite-based precipitation information with a third set of estimates derived from soil moisture retrievals. The merged precipitation dataset and each of the three contributors (aggregated here to 5-day averages at a spatial resolution of about 36-km) are then evaluated for consistency with independent geophysical fields. The merged dataset is found to perform best, a clear indication that it takes proper advantage of the complementary strengths of each contributor and, accordingly, that the presented approach for merging the different contributors is indeed viable.
Precipitation↗
In Situ Study of Particle Precipitation in Metal-Doped CeO2 during Thermal Treatment and Ion Irradiation for Emulation of Irradiating Fuels
Metallic particles formed in oxide fuels (e.g., UO 2 ) during neutron irradiation have an adverse impact on fuel performance. A fundamental investigation of particle precipitation is needed to predict the fuel performance and potentially improve fuel designs and operations. In this study, we report on the precipitation of Mo-dominant β-phase particles in polycrystalline CeO 2 (surrogate for UO 2 ) films doped with Mo, Pd, Rh, Ru, and Re (surrogate for Tc). In situ heating scanning transmission electron microscopy indicates that particle precipitation starts at ~1073 K with a limited particle growth to ~10 nm. While particle concentration increases with increasing temperature, particle size remains largely unchanged up to 1273 K. There is a dramatic change in the microstructure following vacuum annealing at 1373 K, probably due to phase transition of reduced cerium oxide. At the high temperature, particles grow up to 75 nm or larger with distinctive facets. The particles are predominantly composed of Mo with a body-centered cubic structure (β phase). An oxide layer was observed after storage at ambient conditions. In situ heating X-ray photoelectron spectroscopy reveals an increasing reduction of Ce charge state from 4+ to 3+ in the doped CeO 2 film at temperatures from 673 to 1273 K. In situ ion irradiation transmission electron microscopy with 2 MeV Al 2+ ions up to a dose of ~20 displacements per atom at nominally room temperature does not lead to precipitation of visible particles. However, irradiation with 1.7 MeV Au 3+ ions to ~10 dpa at 973 K produces ~2 nm sized pure Pd particles; Au 3+ irradiation at 1173 K appears to result in precipitates of ~6 nm in size. Some of the defects produced by ion irradiation could be nucleation sites for precipitation, leading to generation of smaller particles with a higher concentration.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
North American extreme precipitation events and related large-scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends
This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defned based on the characteristic spatial variations of a meteorological feld or on the remote circulation response to a known forcing, LSMPs are defned relative to the occurrence of a specifc phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary infuence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to defnitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many diferent defnitions of “extreme” are in use, making it difcult to directly compare diferent studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identifed and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.
Barlow, Mathew↗
Investigation of precipitate refinement in Mg alloys by an analytical composite failure model
An analytical model is developed to simulate precipitate refinement in second phase strengthened magnesium alloys. The model is developed based on determination of the stress fields inside elliptical precipitates embedded in a rate dependent inelastic matrix. The stress fields are utilized to determine the failure mode that governs the refinement behavior. Using an AZ31 Mg alloy as an example, the effects the applied load, aspect ratio and orientation of the particle is studied on the macroscopic failure of a single α-Mg17Al12 precipitate. Additionally, a temperature dependent version of the corresponding constitutive law is used to incorporate the effects of temperature. In plane strain compression, an extensional failure mode always fragments the precipitates. The critical strain rate at which the precipitates start to fail strongly depends on the orientation of the precipitate with respect to loading direction. The results show that the higher the aspect ratio is, the easier the precipitate fractures. Precipitate shape is another factor influencing the failure response. In contrast to elliptical precipitates with high aspect ratio, spherical precipitates are strongly resistant to sectioning. In pure shear loading, in addition to the extensional mode of precipitate failure, a shearing mode may get activated depending on orientation and aspect ratio of the precipitate. The effect of temperature in relation to strain rate was also verified for plane strain compression and pure shear loading cases.
Tabei, Ali↗
Few multi-year precipitation-reduction experiments find a shift in the productivity-precipitation relationship
Well-defined productivity–precipitation relationships of ecosystems are needed as benchmarks for the validation of land models used for future projections. The productivity–precipitation relationship may be studied in two ways: the spatial approach relates differences in productivity to those in precipitation among sites along a precipitation gradient (the spatial fit, with a steeper slope); the temporal approach relates interannual productivity changes to variation in precipitation within sites (the temporal fits, with flatter slopes). Precipitation–reduction experiments in natural ecosystems represent a complement to the fits, because they can reduce precipitation below the natural range and are thus well suited to study potential effects of climate drying. Here, we analyse the effects of dry treatments in eleven multiyear precipitation–manipulation experiments, focusing on changes in the temporal fit. We expected that structural changes in the dry treatments would occur in some experiments, thereby reducing the intercept of the temporal fit and displacing the productivity–precipitation relationship downward the spatial fit. Seventy two percent of expiriments showed that dry treatments did not alter the temporal fit. This implies that current temporal fits are to be preferred over the spatial fit to benchmark land-model projections of productivity under future climate within the precipitation ranges covered by the experiments. Moreover, in two experiments, the intercept of the temporal fit unexpectedly increased due to mechanisms that reduced either water loss or nutrient loss. The expected decrease of the intercept was observed in only one experiment, and only when distinguishing between the late and the early phases of the experiment. This implies that we currently do not know at which precipitation–reduction level or at which experimental duration structural changes will start to alter ecosystem productivity. Our study highlights the need for experiments with multiple, including more extreme, dry treatments, to identify the precipitation boundaries within which the current temporal fits remain valid.
54 ENVIRONMENTAL SCIENCES↗
A Theory for the Balance between Warm Rain and Ice Crystal Processes of Precipitation in Mixed-Phase Clouds
Abstract Mixed-phase clouds contain both supercooled cloud liquid and ice crystals. In principle, precipitation may be initiated either by the liquid phase or by the ice phase. Ice crystals may grow by vapor diffusion to become snow (“ice crystal process”), forming “cold” precipitation. Equally, cloud droplets, when large enough, coalesce to form “warm” precipitation by the “warm rain process.” Warm rain could be supercooled and freeze as “warm” graupel. In the present paper, a new simplified theoretical analysis is provided to examine the microphysical system consisting of three species of hydrometeor, namely, cloud liquid, “cold ice” (crystals, snow), and “warm rain” (frozen or supercooled). This is obtained by nondimensionalizing and simplifying the evolution equations for the mass of each species. Analytical formulas are given for equilibria. Feedback analysis shows that the sign of the feedback is linked to the abundance of precipitation, with a neutral surface in the 3D phase space. The system’s precipitation amount explodes while in the initial unstable regime, crossing the neutral surface and approaching the equilibrium point that is a stable attractor. Positive and negative feedbacks are elucidated. In a standard case, the cold ice mass is about 1000 times larger than the warm rain mass. To illustrate the physical behavior of the theory, sensitivity tests are performed with respect to environmental conditions (e.g., aerosol, updraft speed) and microphysical parameters (e.g., riming and sedimentation rates for cold ice). Cold ice prevails, especially in fast ascent, due to its low bulk density, favoring slow sedimentation and a wide cross-sectional area for riming. Significance Statement The theory elucidates how the ice phase can prevail in the precipitation from any mixed-phase clouds with supercooled cloud liquid and crystals. The ice phase radically suppresses cloud liquid by riming when active and “wins” the competition against coalescence. This prevalence of ice is shown to arise from the low bulk density of snow. The cloud is viewed as a system of negative and positive feedbacks that prevail in realms of stability and instability in a 3D phase space.
Meteorology & Atmospheric Sciences↗
Satellite Precipitation Measurements: What Have We Learnt About Cloud-Precipitation Processes From Space?
Precipitation is one of the fundamental elements that define global and regional climatology. Precipitation systems consist of a broad spectrum of three-dimensional structures in which microphysical processes interact with macro-scale processes in the cloud system and the ambient environment that prescribe the evolution of the system. Since 1970s, satellite observations of precipitation have been a fundamental tool in quantifying this complex interaction. They have first quantified the frequency and intensity of global precipitation, including remote areas over open oceans and polar regions, thus providing today’s precipitation climatology. More recently, satellite observations of cloud and precipitation have been exploited for understanding the physical mechanisms governing precipitation systems. A subset of these studies also provided observation-based metrics to probe physical processes operating in cloud-precipitation systems and to apply them as diagnostic measures for evaluating the representation of the processes in numerical models for better projections of future climate. In this chapter, we first review the theoretical basis of precipitation remote sensing from space and describe how it is practically applied in satellite missions. In the first part of the chapter, an historical overview of the satellite missions is described, summarising the instruments and retrieval algorithms developed in the missions. In the second part, we introduce a set of studies discussing the fundamental mechanisms behind precipitation formation, highlighting what we have learnt to date on cloud-precipitation processes from satellite observations.
Precipitation↗
Exploring topography-based methods for downscaling subgrid precipitation for use in Earth System Models
Topography exerts major control on land surface processes. To improve representation of topographic impacts on land surface processes, a new topography-based subgrid structure has been introduced to the Energy Exascale Earth System Model to represent the subgrid heterogeneity of surface elevation. To take advantage of the new subgrid structure for improving land surface modeling, this study explores four variations of topography-based methods for downscaling grid precipitation to the corresponding subgrids. In the first three methods, the deviation of the subgrid precipitation from the grid’s is equal to the grid precipitation multiplied by the ratio of the elevation difference between the subgrid and grid mean to a specified elevation equals to the grid elevation, the difference between the maximum and minimum subgrid elevation, and the maximum subgrid elevation, respectively. The second method limits the ratio to 0.5 to avoid extreme values on mountains and the third method accounts for the slope effect. The fourth method is similar to the third method except that the Froude Number is used to limit the numerator in a blocking regime of the ambient flow. The downscaled precipitation is evaluated using the PRISM precipitation data over the U.S. using statistical metrics. Results show that by accounting for topographic slope besides elevation, the third and fourth methods show clear advantages over the first and second methods. Furthermore, introducing the Froude Number in the fourth method improves downscaling skill and shows consistent advantages over the third method in areas with larger subgrid heterogeneity across different grids sizes.
Tesfa, Teklu K.↗
Observed variability of summer precipitation pattern and extreme events in East China associated with variations of the East Asian summer monsoon: VARIABILITY OF SUMMER PRECIPITATION AND EXTREME EVENT IN EAST CHINA
This paper presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in China associated with variations of the East Asian summer monsoon (EASM) from 1979-2012. A high-quality daily precipitation dataset covering 2287 weather stations in China is analyzed. Based on the precipitation pattern analysis using empirical orthogonal functions, three sub-periods of 1979-1992 (period I), 1993-1999 (period II) and 2000-2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation, the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport that contributes most to the precipitation anomalies. Lastly, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean that influences deep convection over the oceans.
EASM↗
Application of remote sensing precipitation data and the $\mathrm{CONNECT}$ algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019)
In recent years, the number of floods following unprecedented rainfall events have increased in Iran during early spring (March 21st to April 20th, referred to in Iran as the month of “Farvadin”). While numerous studies have addressed changes in climate extremes and precipitation trends at different temporal scales from daily to annual across the country, analyses of short-duration and heavy precipitation, especially during recent years, are rarely considered. Furthermore, most studies investigate the variations in extremes and total precipitation using a limited number of synoptic weather stations across Iran. Here this study assesses the variations in heavy precipitation (precipitation with intensities greater than or equal to 3 mm/3 h) at 0.04° spatial and 3-hourly temporal resolution during the month of Farvardin. In addition, the effect of atmospheric river conditions over Iran and their possible link to intensifying heavy precipitation is explored. For this purpose, the CONNected-objECT (CONNECT) algorithm is applied on a precipitation dataset, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and an Integrated Water Vapor Transport (IVT) dataset from the NASA Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2). The results suggest that the increase in the number of floods in recent years is related to the increase in the intensity and volume of heavy precipitation events, although the frequency and duration of heavy precipitation events have not changed significantly. Furthermore, the results show that atmospheric river conditions over the country are present during the same window as each year’s most extreme events. It is found that 8 out of 13 of the largest ARs over Iran come from moisture plumes with pathways over the African and Red Sea.
54 ENVIRONMENTAL SCIENCES↗
Three dimensional microstructural characterization of nanoscale precipitates in AA7075-T651 by focused ion beam (FIB) tomography
The size and distribution of precipitates in Al 7075 alloys affects both the mechanical and corrosion behavior (including stress corrosion cracking and fatigue corrosion) of the alloy. Three dimensional (3D) quantitative microstructural analysis of Al 7075 in the peak aged condition (T651) allows for a better understanding of these behaviors. In this study, Focused ion beam (FIB) tomography was used to characterize the microstructure in three dimensions. Analysis of grains and precipitates was performed in terms of volume, size, and morphology. It was found that the precipitates at the grain boundaries are larger in size, higher in aspect ratios and maximum Feret diameter compared to the precipitates inside the grains, due to earlier nucleation of the precipitates at the grain boundaries. Our data on the precipitates at the interface between grains and Mg{sub 2}Si inclusion show that the surfaces of inclusion (impurity) particles can serve as a location for heterogeneous nucleation of precipitates. - Highlights: •Focused ion beam (FIB) tomography was used to characterize the microstructure of Al 7075 in three dimensions. •Analysis of grains and precipitates was performed in terms of volume, size, and morphology. •Precipitates at the grain boundaries have larger size and aspect ratio compared to the precipitates inside the grains.
36 MATERIALS SCIENCE↗
Predicting nepheline precipitation in waste glasses using ternary submixture model and machine learning
Nepheline precipitation in nuclear waste glasses during vitrification can be detrimental due to its negative effect on chemical durability. Developing models to accurately predict nepheline precipitation from compositions is important to increase waste loading since existing models can be overly conservative. In this study, an expanded dataset containing 955 glasses was compiled from literature data, where 355 glasses are for high-level waste (HLW). Previously developed submixture models were refitted using the new dataset, where a misclassification rate of 7.8% was achieved. Nine machine learning (ML) algorithms (e.g., k-nearest neighbor, Gaussian process regression, artificial neural network, support vector machine, decision tree, etc.) were applied to evaluate their ability of predicting nepheline precipitation from compositions. Model accuracy, precision, recall/sensitivity, and F1 score were systemically compared between different ML algorithms and modeling protocols. Good model prediction with an accuracy ~0.9 (misclassification rate of ~10%) was observed with different algorithms under certain protocol. This study evaluated various ML models to predict nepheline precipitations in waste glasses, highlighting the importance of data preparation, modeling protocol, and their effect on model stability and reproducibility. The results provide insights into applying ML to predict glass properties and suggest areas for future research on modeling nepheline precipitations.
Lu, Xiaonan↗
Precipitation Recycling and the Vertical Distribution of Local and Remote Sources of Water for Precipitation
Precipitation recycling is defined as the amount of water that evaporates from a region that precipitates within the same region. This is also interpreted as the local source of water for precipitation. In this study, the local and remote sources of water for precipitation have been diagnosed through the use of passive constituent tracers that represent regional evaporative sources along with their transport and precipitation. We will discuss the differences between this method and the simpler bulk diagnostic approach to precipitation recycling. A summer seasonal simulation has been analyzed for the regional sources of the United States Great Plains precipitation. While the tropical Atlantic Ocean (including the Gulf of Mexico) and the local continental sources of precipitation are most dominant, the vertically integrated column of water contains substantial water content originating from the Northern Pacific Ocean, which is not precipitated. The vertical profiles of regional water sources indicate that local Great Plains source of water dominates the lower troposphere, predominantly in the PBL. However, the Pacific Ocean source is dominant over a large portion of the middle to upper troposphere. The influence of the tropical Atlantic Ocean is reasonably uniform throughout the column. While the results are not unexpected given the formulation of the model's convective parameterization, the analysis provides a quantitative assessment of the impact of local evaporation on the occurrence of convective precipitation in the GCM. Further, these results suggest that local source of water is not well mixed throughout the vertical column.
Bosilovich, Michael G.↗
On the relationship between precipitation extreme and local temperature over eastern China based on convection permitting simulations: roles of different moisture processes and precipitation types
The Clausius–Clapeyron (CC) scaling, which indicates a roughly 7% increase in saturated water vapor per 1 °C increase in temperature, can serve as a strong constraint linking the intensity of precipitation extremes and local temperature. However, the relationship between precipitation extreme and local temperature (referred to as the PE-T relationship) does not always follow the CC scaling and is highly dependent on climate regimes. In this study, we investigated the impacts of different moisture processes and precipitation types on the PE-T relationship over eastern China during the summertime based on convection-permitting model simulations. Consistent with observations, the simulated intensity of precipitation extremes increases with temperature at a rate close to CC (double-CC) scaling below (above) 20 °C. When the temperature exceeds 25 °C, precipitation intensity starts to drop. Precipitation extremes are mainly contributed by the stratiform, MCS (i.e., mesoscale convective system) convective, and non-MCS convective precipitation at low (< 20 °C), medium (20–25 °C), and high (> 25 °C) temperatures, respectively, suggesting that the double-CC scaling occurs when convective types become dominant, while the negative scaling at high temperatures is attributed to the reduced horizontal scale of convection. Corresponding to the reduced intensity of precipitation at high temperatures, there are stronger divergence and subsidence in the low-level atmosphere, which is probably caused by the net cooling associated with the enhanced melting and evaporation of falling hydrometeors due to the lower relative humidity in the low-level atmosphere. Overall, our findings contribute to a deeper understanding of the temperature dependence of precipitation extremes in eastern China.
54 ENVIRONMENTAL SCIENCES↗
Precipitation-site competition in duplex stainless steels: Cu clusters vs spinodal decomposition interfaces as nucleation sites during thermal aging
Competing microstructural evolution mechanisms can exist simultaneously when duplex stainless steels are operating for several decades in a high temperature service environment. Such competition between different microstructural evolution pathways can be difficult to ascertain using simple model alloy systems necessitating detailed structural and compositional analysis of phase transformation mechanisms in complex alloys Thus, in this study duplex stainless steels with complex but well understood chemistries were used to investigate the relative importance of different heterogeneous nucleation sites – specifically spinodal decomposition and Cu clustering – on precipitation of Ni-Si-Mn particles during long term thermal aging. Precipitation of Ni-Si-Mn particles in duplex stainless steels and ferritic steels during thermal aging and irradiation is known to have profound effect on mechanical properties. Using duplex stainless steels with custom modified compositions along with atom probe tomography characterization and first-passage kinetic Monte Carlo (FPKMC) simulations it is revealed that while the interface between Cr and Fe formed during spinodal decomposition can be a pathway for diffusion of Ni, Si, Mn, and Cu, it is not a site that encourages precipitation of Ni-Si-Mn rich particles. Instead, the presence of a higher concentration of Cu in these steels leads to formation of small Cu clusters with high energy interfaces that act as nucleation sites for Ni-Si-Mn particles because of its strong interaction particularly with Ni increasing the chemical driving force for precipitation. These results will help inform predictive models for the use of duplex stainless steels and other precipitation-hardened alloys for extended operation at high temperatures.
Duplex stainless steel, Thermal aging, Precipitati↗
A Hybrid Experimental and Theoretical Approach to Optimize Recovery of Rare Earth Elements from Acid Mine Drainage Precipitates by Oxalic Acid Precipitation
The development of processing techniques for the extraction of rare earth elements and critical minerals (REE/CM) from acid mine drainage precipitates (AMDp) has attracted increased interest in recent years. Processes under development often utilize a standard hydrometallurgical approach that includes leaching and solvent extraction followed by oxalic acid precipitation and calcination to produce a final rare earth oxide product. Impurities such as Ca, Al, Mn, Fe and Mg can be detrimental in the oxalate precipitation step and a survey of the literature showed limited data pertaining to the REE precipitation efficiency in solutions with high impurity concentrations. As such, a systematic laboratory-scale precipitation study was performed on a strip solution generated by the acid leaching and solvent extraction of an AMDp feedstock to identify the optimal processing conditions that maximize REE precipitation efficiency and product purity while minimizing the oxalic acid dosage. Given the unique chemical characteristics of AMDp, the feed solution utilized in this study contained a moderate concentration of REEs (440 mg/L) as well a significant concentration (>7000 mg/L total) of non-REE contaminants such as Ca, Al, Mn, Fe and Mg. Initially, a theoretical basis for the required oxalic acid dose, optimal pH and predicted precipitation efficiency was established by solution equilibrium calculations. Following the solution chemistry calculations, bench-scale precipitation experiments were conducted and these test results indicate that a pH of 1.5 to 2, a reaction time of more than 2 h and an oxalic acid dosage of 30 to 40 g/L optimized the REEs recovery of at ~95% to nearly 100% for individual REE species. The test results validated the optimal pH predicted by the solution chemistry calculations (1.5 to 5); however, the predicted dosage needed for complete REE recovery (10 g/L) was significantly lower than the experimentally-determined dosage of 30 to 40 g/L. The reason for this discrepancy was determined to be due to the large concentration of impurities and large number of potential metal complexes that cause inaccuracies in the solution equilibrium calculations. Based on these findings, a hybrid experimental and theoretical approach is proposed for future oxalic acid precipitation optimization studies.
oxalic acid precipitation↗