Rare Earth Elements Recovery from Primary and Secondary Resources Using Flotation: A Systematic Review

Julapong, Pongsiri; Numprasanthai, Apisit; Tangwattananukul, Ladda; Juntarasakul, Onchanok; Srichonphaisarn, Palot; Aikawa, Kosei; Park, Ilhwan; Tabelin, Carlito Baltazar; Phengsaart, Theerayut

doi:10.3390/app13148364

Cited by 13 publications

(4 citation statements)

References 147 publications

(205 reference statements)

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“…Despite this advantage, these ore bodies' non-renewable nature and limitations underline the need to explore sustainable alternatives for sustaining REE production. Urban processing seems to be a potential alternative; thus, tapping into these secondary sources ensures a more sustainable supply of REEs [7,8]. A simple overview in Figure 1 depicts the flowsheets of both conventional and urban processing concepts.…”

Section: Introductionmentioning

confidence: 99%

Exploring the REEs Energy Footprint: Interlocking AI/ML with an Empirical Approach for Analysis of Energy Consumption in REEs Production

Pathapati,

Singh,

Free

et al. 2024

Processes

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Rare earth elements (REEs including Sc, Y) are critical minerals for developing sustainable energy sources. The gradual transition adopted in developed and developing countries to meet energy targets has propelled the need for REEs in addition to critical metals (CMs). The rise in demand which has propelled REEs into the spotlight is driven by the crucial role these REEs play in technologies that aim to reduce our carbon footprint in the atmosphere. Regarding decarbonized technologies in the energy sector, REEs are widely applied for use in NdFeB permanent magnets, which are crucial parts of wind turbines and motors of electric vehicles. The underlying motive behind exploring the energy and carbon footprint caused by REEs production is to provide a more complete context and rationale for REEs usage that is more holistic. Incorporating artificial intelligence (AI)/machine learning (ML) models with empirical approaches aids in flowsheet validation, and thus, it presents a vivid holistic picture. The energy needed for REEs production is linked with the source of REEs. The availability of REEs varies widely across the globe. REEs are either produced from ores with associated gangue or impurities. In contrast, in other scenarios, REEs can be produced from the waste of other mineral deposits or discarded REEs-based products. These variations in the source of feed materials, and the associated grade and mineral associations, vary the process flowsheet for each type of production. Thus, the ability to figure out energy outcomes from various scenarios, and a knowledge of energy requirements for the production and commercialization of multiple opportunities, is needed. However, this type of information concerning REEs production is not readily available as a standardized value for a particular material, according to its source and processing method. The related approach for deciding the energy and carbon footprint for different processing approaches and sources relies on the following three sub-processes: mining, beneficiation, and refining. Some sources require incorporating all three, whereas others need two or one, depending on resource availability. The available resources in the literature tend to focus on the life cycle assessment of REEs, using various sources, and they focus little on the energy footprint. For example, a few researchers have focused on the cumulative energy needed for REE production without making assessments of viability. Thus, this article aims to discuss the energy needs for each process, rather than on a specific flowsheet, to define process viability more effectively regarding energy need, availability, and the related carbon footprint.

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Section: Introductionmentioning

confidence: 99%

Exploring the REEs Energy Footprint: Interlocking AI/ML with an Empirical Approach for Analysis of Energy Consumption in REEs Production

Pathapati,

Singh,

Free

et al. 2024

Processes

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“…In recent times, the focus has been on environmental issues, including transition to clean energy aimed at implementing renewable energy technologies [5] and defining stringent carbon dioxide emission restrictions. This topic has been addressed in terms of both coals [6] and metallic ores [7,8].…”

Section: Introductionmentioning

confidence: 99%

Development of an Integrated Model for Open-Pit-Mine Discontinuous Haulage System Optimization

Čelebić,

Bajić,

Bajić

et al. 2024

Sustainability

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The selection of the optimal equipment for discontinuous haulage systems is one of the most important decisions that need to be made when an open-pit mine is designed. There are a number of influencing factors, including natural (geological and environmental), technical, economic, and social. Some of them can be expressed numerically, in certain units of measure, while others are descriptive and can be stated by linguistic variables depending on the circumstances of the project. These factors are characterized by a high level of uncertainty, associated with both exploration and mining operations. The experience, knowledge, and expert judgment of engineers and specialists are of key importance for the management of mining processes, consistent with the issues stemming from the dynamic expansion of open-pit mines in space over time. This paper proposes an integrated model that translates all the criteria that affect the selection of the optimal solution into linguistic variables. By employing the multiple-criteria decision-making method and combining it with fuzzy logic, we developed an algorithm that addresses all the above-mentioned uncertainties inherent in various mining processes where the experience of experts forms the basis. The fuzzy analytic hierarchy process is used in order to deal with trending decision problems, such as mining equipment and management system selection. The entire algorithm was applied to a real case study—the Ugljevik East 1 open-pit mine.

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“…Clean energy transition tends to define strict CO 2 emission limits as a form of combat against climate change by integrating more green and renewable energy technology [7]. Many authors have published papers on this topic in the area of coal [8] and metal ore [7,9,10] processing.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Model for Optimisation of Waste Dump Design and Site Selection in Open Pit Mining

Doderovic,

Stepanovic

et al. 2023

Minerals

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Waste management is an unavoidable technological operation in the process of raw material extraction. The main characteristic of this technological operation is the handling of large quantities of waste material, which can amount to several hundred million cubic metres. At the same time, this operation must comply with all administrative and environmental standards. Therefore, optimising waste rock management (particularly haulage and dumping) has the potential to significantly improve the overall value of the project. This paper presents a hybrid model for the optimisation of waste dump design and site selection. The model is based on different mathematical methods (Monte Carlo simulation, genetic algorithm, analytic hierarchy process and heuristic methods) adapted to different aspects of the problem. The main objective of the model is to provide a solution (in analytical and graphical form) for the draft waste dump design, on the basis of which the final waste dump design can be defined. The functioning of the model is verified using an example of an existing open pit. In the case study, 2250 members of the initial population (different waste dump variants) were generated, and a total of 110 optimised solutions were obtained using 15 optimisations. The solution with the best value of the objective function is adopted, and the final waste dump design is created.

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Rare Earth Elements Recovery from Primary and Secondary Resources Using Flotation: A Systematic Review

Cited by 13 publications

References 147 publications

Exploring the REEs Energy Footprint: Interlocking AI/ML with an Empirical Approach for Analysis of Energy Consumption in REEs Production

Exploring the REEs Energy Footprint: Interlocking AI/ML with an Empirical Approach for Analysis of Energy Consumption in REEs Production

Development of an Integrated Model for Open-Pit-Mine Discontinuous Haulage System Optimization

Hybrid Model for Optimisation of Waste Dump Design and Site Selection in Open Pit Mining

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