Many studies have been published in recent years focusing on the recovery of rare earth elements (REEs) from coal-related materials, including coal, coal refuse, coal mine drainage, and coal combustion byproducts particularly fly ash. The scientific basis and technology development have been supported by coal geologists and extractive metallurgists, and through these efforts, the concept has progressed from feasibility assessment to pilot-scale production over the last five years. Physical beneficiation, acid leaching, ion-exchange leaching, bio-leaching, thermal treatment, alkali treatment, solvent extraction, and other recovery technologies have been evaluated with varying degrees of success depending on the feedstock properties. In general, physical beneficiation can be a suitable low-cost option for preliminary upgrading; however, most studies showed exceedingly low recovery values unless ultrafine grinding was first performed. This finding is largely attributed to the combination of small RE-bearing mineral particle size and complex REE mineralogy in coal-based resources. Alternatively, direct chemical extraction by acid was able to produce moderate recovery values, and the inclusion of leaching additives, alkaline pretreatment, and/or thermal pretreatment considerably improved the process performance. The studies reviewed in this article revealed two major pilot plants where these processes have been successfully deployed along with suitable solution purification technologies to continuously produce high-grade mixed rare earth products (as high as +95%) from coal-based resources. This article presents a systematic review of the recovery methods, testing outcomes, and separation mechanisms that are involved in REE extraction from coal-related materials. The most recent findings regarding the modes of occurrence of REEs in coal-related materials are also included.

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.

In recent years, acid mine drainage (AMD) has emerged as a promising unconventional source of rare earth elements (REEs) and other critical minerals (CMs) such as cobalt and manganese. In this regard, AMD provides a natural heap leaching effect that extracts and concentrates REE/CM from the host strata creating a partially enriched feedstock suitable for downstream extraction, separation, and recovery. While several prior studies have described processes and approaches for the valorization of AMD, very few have described the supply chain and infrastructure requirements as well as the associated economic assessment. To that end, this paper provides a fundamental economic assessment of REE/CM recovery from AMD using a network sourcing strategy in addition to a robust, flexible feedstock separations and refining facility. The methodology of this paper follows that of a typical techno-economic analysis with capital and operating costs estimated using AACE Class IV (FEL-2) guidelines. To demonstrate the range of possible outcomes, four pricing scenarios were modeled including contemporary prices (September, 2021) as well as the minimum and maximum prices over the last decade. In addition, five production scenarios were considered reflecting variations in the product suite, ranging from full elemental separation to magnet REE and CM production only (i.e., Pr, Nd, Tb, Dy, Y, Sc, Co, and Mn). The results of this analysis show that, with the exception of the minimum price scenario, all operational configurations have positive economic indicators with rates of return varying from 25% to 32% for the contemporary price scenario. The optimal configuration was determined to be production of Co, Mn, and all REEs except for mischmetal, which is not recovered. Sensitivity analysis and Monte Carlo simulation show that capital cost and HCl consumption are the two major factors influencing rate of return, thus indicating opportunities for future technology development and cost optimization. Implications of the study and a cooperative profit-sharing model for sourcing are also described.

Acid mine drainage is a legacy environmental issue and one of the largest pollutants in many mining districts throughout the world. In prior work, the authors have developed a process for the recovery of critical materials, including the rare earth elements, from acid mine drainage using a preconcentration step followed by solvent extraction as a concentration and purification technology. As part of the downstream technology development efforts, we have synthesized a suite of ionic liquid extractants that facilitate greater separation factors leading to lower capital costs and reduced environmental impacts. This article provides a comparison of the conventional extractants D2EHPA, EHEHPA and C572 with their respective ionic liquids [c101][D2EHP,c101][EHEHP] and [c101][C572] for the recovery of rare earth elements from acid mine drainage. In the study, laboratory-scale, multi-contact solvent extraction tests were conducted at high and low extractant/dosages. The results show that the ionic liquids varied in performance, with [c101][D2EHP] and [c101][EHEHP] performing poorer than their conventional counterparts and [c101][c572] performing better. Recommendations for further study on [c101][c572] include stripping tests, continuous pilot testing, and techno-economic analysis.

The design of cell-based flotation circuits is often completed in two distinct phases, namely circuit structure identification and equipment sizing selection. While recent literature studies have begun to address the implications of stochastic analysis, industrial practice in flotation circuit design still strongly favors the use of deterministic metallurgical modeling approaches. Due to the complexity of the available mathematical models, most flotation circuit design techniques are constructed based on deterministic models. Neglecting the impact of various sources of uncertainty may result in the identification of circuit solutions that are only optimal in a narrow region of specific operating scenarios. One promising strategy to address this shortcoming is through the Sample Average Approximation (SAA) methodology, a stochastic approach to handling uncertainty that has been widely applied in other disciplines such as supply chain and facility location management problems. In this study, a techno-economic optimization algorithm was formulated to select the optimal size and number of flotation cells for a fixed circuit structure while considering potential uncertainty in several input parameter including feed grade, kinetic coefficients, and metal price. Initially, a sensitivity analysis was conducted to screen the uncertain parameters. After simplifying the optimization problem, the SAA approach was implemented to determine the equipment configuration (i.e., cell size and number) that maximizes the plant’s net present value while considering the range of potential input values due to parameter uncertainty. The SAA methodology was found to be useful in analyzing uncertainty in flotation kinetics; however, the approach did not provide a useful means to assess the influence of uncertainties in ore grade and metal price, as these values are not significant in determining equipment size but rather influence the optimal circuit structure, which was not considered in this study. Results from an application example indicate that the SAA approach produces optimal solutions not initially identified in a deterministic optimization, and these SAA solutions tend to provide greater robustness to uncertainty and variation in the flotation kinetics.