Ore Grade Research Articles

Applying Circular Thermoeconomics for Sustainable Metal Recovery in PCB Recycling

The momentum of the Fourth Industrial Revolution is driving increased demand for certain specific metals. These include copper, silver, gold, and platinum group metals (PGMs), which have important applications in renewable energies, green hydrogen, and electronic products. However, the continuous extraction of these metals is leading to a rapid decline in their ore grades and, consequently, increasing the environmental impact of extraction. Hence, obtaining metals from secondary sources, such as waste electrical and electronic equipment (WEEE), has become imperative for both environmental sustainability and ensuring their availability. To evaluate the sustainability of the process, this paper proposes using an exergy approach, which enables appropriate allocation among co-products, as well as the assessment of exergy losses and the use of non-renewable resources. As a case study, this paper analyzes the recycling process of waste printed circuit boards (PCBs) by disaggregating the exergy cost into renewable and non-renewable sources, employing different exergy-based cost allocation methods for the mentioned metals. It further considers the complete life cycle of metals using the Circular Thermoeconomics methodology. The results show that, when considering the entire life cycle, between 47% and 53% of the non-renewable exergy is destroyed during recycling. Therefore, delaying recycling as much as possible would be the most desirable option for minimizing the use of non-renewable resources.

Emission Impacts of Direct Reduced Iron‐Ore Processing Systems: A Systems Thinking Approach in Case Studies of Canada and Peru

This study presents a novel methodology for quantifying CO2 emissions in direct reduced iron (DRI)‐grade iron‐ore processing plants using system dynamics modeling (SDM) with an emphasis on associated uncertainties. Two plants in Canada and Peru are analyzed, where similar ore grades (34.89% and 39.10%) but different ore types (hematite and magnetite) lead to distinct mineral processing systems. By incorporating the breakdown of power grid generation sources, the annual CO2 emissions are quantified, finding significantly higher emissions in Peru (22,241.63 tCO2e ton−1) compared to Canada (2,252.85 tCO2e ton−1). These results highlight the critical impact of local energy grids on emissions, underscoring the need to consider both ore characteristics and regional energy profiles in developing decarbonization strategies. This study offers a structured approach to assessing the CO2 impact of raw materials in low‐carbon steel production. It emphasizes the effect of the spatial distribution of raw materials in the steel‐making process. The analysis reveals that emissions from the plant in Peru are nearly 10 times higher than those in Canada, highlighting the significant influence of the local energy grid. These results underscore the influence of ore characteristics and regional energy profiles in developing effective decarbonization strategies.

Estimating rare earth elements at various scales with bastnäsite indices for Mountain Pass

Numerous researchers are exploring innovative ways to map rare earth elements (REEs) critical to components in high technology devices precisely, and one approach that has made significant advances in recent years involves imaging spectroscopy. This research focuses on the utilization of this technique to map REEs across the Sulfide Queen mine and Birthday claim area located in Mountain Pass, California, where the highest concentrations of REEs within a carbonatite deposit in the United States have been reported. New spectral indices based on reflectance measurements of eleven representative ore samples under visible illumination in a laboratory setting were developed and applied to data collected by eight airborne and spaceborne imaging spectrometers. The results show that these indices can effectively detect REEs in any rock formation where an adequate amount of rare earth fluorocarbonates have accumulated. Identification can be achieved using airborne and spaceborne hyperspectral sensors with a spatial resolution of up to 30 m. Geochemical analyses confirm that a REE+Y ore grade of 3.25 wt% or greater is sufficient for detection using these indices.

Environmental impacts of lithium supply chains from Australia to China

Abstract Lithium (Li) has been widely recognized as an essential metal for clean technologies. However, the environmental impacts and emission reduction pathways of the lithium supply chain haven’t been clearly investigated, especially between Australia and China, where most lithium ore are mined and produced. This study analyzed and compared the environmental and human health implications of six key cross-border Li supply chains from Australia to China through material flow analysis (MFA) and life cycle assessment (LCA) methods. Key findings include: (1) approximately 30% of total Li extraction is lost in the beneficiation stage due to low recovery rates; (2) the Cattlin-Yaan routes exhibit superior environmental and human health performances than other routes attributed to lower diesel consumption, reduced electricity use, and a high chemical conversion rate; (3) the Wodgina production routes have a higher carbon footprint mainly due to low ore grade and significant diesel consumption; (4) the dominant environmental implications in the supply chain are associated with refining battery-grade lithium carbonate, driven by energy use (electricity, coal and natural gas), sulfuric acid, soda ash, and sodium hydroxide. In addition, lithium carbonate refining has the highest water consumption. Overall, the analysis highlights opportunities to improve environmental performance, advance data-poor environmental assessments, and provide insights into sustainable Li extraction.

Applying Knowledge-Based and Data-Driven Methods to Improve Ore Grade Control of Blast Hole Drill Cuttings Using Hyperspectral Imaging

Applying Knowledge-Based and Data-Driven Methods to Improve Ore Grade Control of Blast Hole Drill Cuttings Using Hyperspectral Imaging

Recovery of antimony from acidic and alkaline leaching solution of low-grade antimony ore by electrowinning process

With regards to the global continuous growth in consumption of base metals such as antimony (Sb), mining companies are currently looking to improve the productivity and extraction of Sb from low grade ore in order to economically process it. With this aim, in this study, an efficient protocol was developed to recover metallic Sb from the low grade Fe3Si2O5(OH)4. Sb3O6(OH). Sb2O3 ore of the Sefid-Abe mine in Zahedan province, Iran, utilizing selective acidic or alkaline leaching followed by Sb electrowinning. A process was developed to recover antimony from an Sb2O3 ore source, using selective acidic or alkaline leaching followed by antimony electrowinning. Sb could be leached with an efficiency of 85 % using 5 M NaOH and 87 % using 5 M hydrochloric acid/5 M sulfuric acid as the digestion solution at 80 °C for 8 h. The electrowinning process plays a significant role in recovery of highly pure Sb metal. Relying on this approach, a high deposition rate and current efficiency have been generated at a deposition potential 2 V at 30 °C (80 °C for alkaline medium). This was achieved by using anode electrode made of graphite and cathode electrode made of steel (two steel electrodes were used for alkaline electrowinning). Additionally, for acidic electrowinning, exploitation of Sb from the electrolyte solution was achieved by applying a current of 0.1 A, resulting in the highest yield equal to 89 %. On the other hand, for alkaline electrowinning, the highest efficiency corresponds to the current intensity of 0.5 A, which resulted in 97 % Sb extraction from the electrolyte solution. The XRD and ICP analysis performed for samples obtained from the electrolysis confirmed that the resulting antimony ingot has an exceptionally high purity.

The performance and charge behaviour in melter/smelter for the production of hot metal in hydrogen DRI-based steelmaking

Direct reduced iron (DRI)-based steelmaking requires high-grade iron ore (Fe > 65 wt-%). However, a swift decline in ore grade has forced steelmakers to use lower-grade ores for DRI making, creating challenges in subsequent processes dealing with high gangue content for steelmaking. Hence, an intermediate melting/smelting furnace has been proposed to treat high gangue content from the DRI before transferring hot metal into an electric arc furnace (EAF)/basic oxygen furnace (BOF) for steelmaking. This study investigates and models the performance and charge behaviour in a melter/smelter with respect to the gangue content, DRI carbon content and temperature. The results showed that the specific energy consumption (SEC) and off-gas production increase with increasing temperature, carbon in DRI and gangue content. At 90 wt-% metallisation ratio (MR) using the lowest-grade ore (gangue 16 wt-%), the SEC at 1300 °C was calculated to be 706 kWh/tHM compared to 850 kWh/tHM at 1600 °C using 3.5 wt-% carbon. The MR is predicted to profoundly impact the SEC, as the increasing MR decreases the SEC markedly. At 90 wt-% MR, the SEC using the lowest-grade ore was 805 kWh/tHM, decreasing to 684 kWh/tHM using 100 wt-%MR. Increasing MR, carbon in DRI and temperature decreases slag production consistently while increasing with the increasing gangue. Using hot DRI onsite is predicted to significantly reduce the SEC compared to cold DRI. Overall, the energy demand from cold DRI is predicted to be 120 kWh/tHM higher than hot DRI. Increasing the scrap-to-DRI ratio is predicted to decrease the energy demand, that is, every 1.0 wt-% increase in scrap decreases the SEC by 2.5 kWh/tHM.

Hydrogen reduction studies of low-grade multimetallic magnetite ore pellets

The hydrogen reducibility of pellets made from a low-grade multimetallic magnetite ore (Fe content ∼ 45 %) was investigated in the present study. Pellets were reduced in a horizontal tube furnace at temperatures ranging from 973 K to 1173 K for 1 to 60 min. Pure Hydrogen (H2) gas (99.9 %) at three flow rates of 0.25 L/min, 0.5 L/min, and 1 L/min were blown during the reduction process. A maximum reduction degree of 94.07 %, metallization ratio of 0.925, and H2 gas utilization of 9.01 % were obtained at a temperature and a reduction time of 1173 K and 60 min, respectively. In order to optimize the hydrogen utilization, a reduction temperature of 1173 K, a reduction time of 45 min, and a gas flow rate of 0.25 L/min were selected, resulting in a reduction degree and metallization ratio of 90 % and 0.89, respectively. The cold crushing strength (CCS) of the reduced pellets initially decreased and then increased slightly, exhibiting behavior similar to high-grade ores. Imputities like SiO2, Al2O3, and MgO, present in the low grade ores are found to control the porosity of the pellets, directly affecting the CCS and reducibility of the pellets.

Understanding key mineral supply chain dynamics using economics‐informed material flow analysis and Bayesian optimization

AbstractThe low‐carbon energy transition requires significant increases in production for many mineral commodities. Understanding demand, technological requirements, and prices associated with this production increase requires understanding the supply chain dynamics of many minerals simultaneously, and via a consistent framework. A generalized economics‐informed material flow method, global materials modeling using Bayesian optimization, captures the market dynamics of key mineral commodities. The method relies only on a limited set of widely available historical data as input, enabling quantification of economic relationships (elasticities) for supply chain components where data are sparse, and relationships cannot be obtained via traditional statistical approaches. Building upon established material flow analysis (MFA) and economic modeling techniques, Bayesian optimization was applied to fit an economics‐informed MFA model to global historical demand, supply, and price for aluminum, copper, gold, lead, nickel, silver, iron, tin, and zinc. This approach enables estimates for the evolution of ore grades, mine costs, refining charges, sector‐specific demand, and scrap collection for each commodity. Economic relationships were quantified and compared with a database compiled from the literature, including 1333 values from 213 analyses across 65 publications. Discrepancies in methods and limited coverage make use of these parameters in modeling efforts difficult. This work provides a single, homogeneous, probabilistic approach to identifying economic relationships across mineral supply chains, with uncertainty quantification, a literature database for comparison, and a modeling framework in which to use them. This article met the requirements for a Gold‐Gold JIE data openness badge described at http://jie.click/badges.

Integrating selective flocculation techniques for enhanced efficiency in manufacturing processes: A novel approach through artificial neural network modeling

The use of medium and low-grade iron ore is gradually becoming more important due to the depletion of high-grade iron ore reserves and stringent environmental acts/rules. Slimes from iron ore washing were discarded in tailing dams; however, there is currently consideration for recovering iron values from ultra-fines as well. There are enormous fine dumps that are still unutilised. Hence, this study attempt to delve the optimization of iron ore slimes an indeed requirement for manufacturing and design in industries. Leveraging a flocculation process, coupled with the implementation of an Artificial Neural Network (ANN) predictive model, the Kiriburu processing plant serves as the primary source for iron ore slime samples. Chemical analyses of the collected iron samples reveal a composition featuring 58.24 % iron content, 3.47 % Al2O3, 4.72 % SiO2, and 5.18 % LOI (Loss on Ignition). The investigation explores the performance of the flocculation technique under varying pH levels, different pulp densities, and diverse flocculant dosages. Furthermore, the varying parameters selected are pH from 6 to 11, pulp density from 1 % to 15 %, and flocculant dose from 0.03 to 0.27 mg/g. The study's findings showcase a substantial improvement in the Fe grade of iron ore, escalating from 58.24 % to 66.12 %, with an impressive recovery rate of 82.54 % achieved using a flocculant dosage of 0.09 mg/g at pH 10. Additionally, a performance assessment of the selective flocculation method for iron ore slimes is conducted using an ANN predictive model, with recovery as the pivotal parameter. The input parameters for this model encompass pH, pulp density, and flocculant dosages. Employing a three-layer ANN model with a 3–3–1 architecture and utilizing feed-forward back propagation, the study demonstrates a close alignment between predicted values and experimental data, confirming the model's effectiveness for practical manufacturing applications. Information regarding the potential applications of the model's iron ore slime beneficiation efficacy for the manufacturing sector should be considered. This could entail lower waste, more effectiveness, or cost savings. Emphasise any possible ramifications for sustainability or the environment that would make the study pertinent in a larger perspective.

Metal remobilization at the Nibao gold deposit in Youjiang basin, SW China: Implications from mineral texture, trace element and sulfur isotope compositions of sulfides and TiO2 polymorphs

Multistage mineralization overprinting is important for the formation of giant hydrothermal gold deposits. The Youjiang basin in SW China has undergone at least three major deformation phases in the Mesozoic, but their relationship with the large-scale gold accumulation in the region remains enigmatic. Here, we study the large Nibao gold deposit (reserve > 70 t Au) in the northern part of the basin, which has both fault-controlled and stratabound orebodies. We identified a pre-ore stage and syn-ore stage including four tectono-hydrothermal (T-H) substages (i.e., T-H stage 1, 2, 3 and 4) for the local mineralization at Nibao. The pre-ore stage is dominated by coarse-grained pyrite coexisting with TiO2 polymorphs in the Middle-Late Permian basaltic rocks. The T-H substage 1 is characterized in that the sedimentary pyrites are brecciated in bedding-parallel faults. Fluorination and silicification occur in the T-H substage 2, which is re-brecciated at the T-H substage 3 forming the highest gold grade ore in high-angle thrust fault. The T-H substage 4 presents as fault reactivation within minor calcite and pyrite deposition. Mineralogy and in-situ trace element analyses reveal that mineral dissolution and reprecipitation (incl. dolomite, auriferous pyrite and TiO2 polymorphs) is ubiquitous during the multistage tectono-hydrothermal process, and the continuous alteration overprinting may have promoted gold accumulation. This replacement process of different generations of auriferous pyrite is also recorded by their inherited sulfur isotopes, giving a narrow δ34S (−3.1 to + 2.1 ‰) range. Anatase is the main accessory phase of TiO2 polymorphs, as identified with LA-ICP-MS trace element and laser Raman spectroscopic analyses. Moreover, the anatase can been divided into two types (type-I and II) based on their texture, alteration and chemistry. The type-I anatase commonly occurring in the stratabound ore is characterized by higher Zr (mean 1,730 ppm), V (mean 1,412 ppm), and Cr (mean 110 ppm) contents than type-II that coexists with zoned pyrite in the fault-controlled ore (mean 26 ppm, 187 ppm, and 38 ppm, respectively). Additionally, W (mean 636 ppm) and Mg (10,021 ppm) in type-II are much higher than type-I ones (mean 135 ppm W and 476 Mg). These features show that the sedimentary-stage Zr-V-Cr-rich type-I anatase was dissolved via fluid metasomatism, and reprecipitated as the hydrothermal-stage W-Mg-rich and Zr-poor anatase, with gold gradually enriched. Besides, the anatase phase of TiO2 polymorphs also indicates that the Nibao gold deposit was formed under low pressure–temperature condition. Overall, we propose that the Nibao is a Carlin-type gold deposit, dominated by multistage tectono-hydrothermal events.

Estimation of Fe Grade at an Ore Deposit Using Extreme Gradient Boosting Trees (XGBoost)

Estimating the spatial distribution of ore grade is one of the most critical and important steps to continue investment decision on the deposit. Kriging is the most widely used method to estimate the ore grade while alternative techniques are being developed. Machine learning algorithms can be used as alternative methods to classical kriging. In this paper, Fe grade of a deposit is estimated with XGBoost algorithm, and results are compared with kriging estimation results. For estimation processes, samples collected from the drillholes are used. To mitigate the effect of varying sampling length, both estimations use composites of these samples. Due to the different nature of the estimation methods, different steps have been taken to perform estimations. Results show that XGBoost estimates produced higher ranged estimates which is a desired result in ore grade estimation while minimum and maximum of the estimates were lower and higher than the kriging estimates, respectively. However, like kriging estimates, estimation results were smoother than composites while variance of the XGBoost estimates were lower than variance of composites. This means that even though estimation with XGBoost mitigates the smoothing effect, estimation results suffer from smoothing effect like kriging.

Process Design for Direct Production of Battery Grade Nickel Sulfate

The clean energy transition has increased the global demand of nickel sulfate used in the Li-ion batteries. A short-term solution is to refine the nickel sulfate product from nickel intermediates. In the long-term, new direct nickel sulfate production technologies are needed. This research focused on the modeling-based concept development of a novel direct hydrometallurgical nickel sulfate process consisting of chemical leaching, impurity removal by precipitation, solvent extraction, and crystallization as an alternative to the conventional nickel sulfate production route via a nickel matte intermediate. The conventional process route with the studied nickel concentrate had lower chemical consumption and waste production compared to direct hydrometallurgical process where approximately 60% of iron was leached consuming oxygen, and the following iron precipitation step consuming calcium carbonate resulted in a high amount of iron precipitate together with gypsum. However, hydrometallurgical alternatives are often suitable for lower ore grades or volumes and can recover copper as by-product metal. The biggest impacts on carbon footprint from chemical consumption in the direct hydrometallurgical process were generated in iron precipitation and oxygen use in leaching. With the studied nickel concentrate, pyrrhotite played a key role in both oxygen use and iron precipitation. In the leaching step, 68% of total oxygen consumption was related to pyrrhotite leaching, while in iron removal 73% of total iron originated from pyrrhotite. Thus, especially pyrrhotite removal prior to leaching needs to be developed to reduce the carbon dioxide footprint, when the pyrrhotite content in the material is high.Graphical

Spatial diffusion of potentially toxic elements in soils around non-ferrous metal mines

This study focuses on the diffusion patterns of principal ore-forming elements (Pb and Zn) and associated elements (Cd, Cu, Cr, and As) in lead-zinc ore. Sampling points in upwind and downwind directions of lead-zinc ore areas at various densities (1 N/km2 – 4 N/km2) were categorized. This study analyzed the statistical relationship between the content of PTEs in the soil around lead-zinc ore and the source strength and dominant wind direction, constructed one-dimensional and two-dimensional diffusion model, and simulated the EER scope caused by PTEs. The findings indicate that: (1) concerning source strength, the content of PTEs in soils of high-density ore aggregation areas is significantly higher than in low-density ore aggregation areas. However, the impact of source strength decreases with decreasing ore grade, with a difference in Pb content of 1.71 times among principal ore-forming elements and almost consistent Cd content among associated elements. (2) Regarding the transport pathways, for most PTEs, the inverse proportion coefficients downwind are higher than upwind, approximately 1.18–3.63 times, indicating greater migration distances of PTEs downwind due to atmospheric dispersion. (3) By establishing a two-dimensional risk diffusion model, the study simulates the maximum radius of risk diffusion (r = 5.7 km), the 50% probability radius (r = 3.1 km), and the minimum radius (r = 0.8 km) based on the maximum, median, and minimum values statistically obtained from the EER. This study provides a scientific basis for implementing preventive measures for PTEs accumulation in soil within different pollution ranges. Different risk prevention and control measures should be adopted for PTEs accumulation in soil within the three ranges after cutting off pollution sources. Subsequent research should further investigate the impact and contribution of atmospheric transmission and surface runoff on the diffusion of PTEs in areas with high risk near lead-zinc ore.

Enhanced Measurement and Verification Practices in Deep-Level Mines: The Current State

This article explores operational challenges in mining, with a focus on energy management amid depleting ore grades and rising costs. The urgent need for innovative energy management systems and strategies is highlighted by analyzing the unexplored landscape of mine energy budgeting and forecasting and identifying gaps in current practices. Drawing from the literature, this paper offers new insights into energy budgeting and the evaluation of energy efficiency initiatives by integrating traditional and advanced measurement and verification (M&V) techniques. M&V practices are crucial for energy management, particularly in deep-level mines, with a focus on practical knowledge and advanced methodologies. Key findings from this study show that integrating advanced M&V techniques with unplanned events is crucial to improve the financial management of mines. By leveraging these key findings, this article proposes a roadmap of the next seven milestones needed in advanced M&V research to aid effective energy management in a mining environment. If executed successfully, a practical method for applying advanced M&V processes to deep-level mining operations can be constructed. Such a generic method will enhance mining companies’ energy efficiency initiatives and improve financial management practices on a global scale.

Process modelling for the production of hydrogen-based direct reduced iron in shaft furnaces using different ore grades

This process modelling study explored the behaviour of hydrogen-based direct reduced iron (DRI) manufacturing in a shaft furnace. Various performance parameters such as metallisation ratio (MR), consumption of hydrogen per tonne of DRI, production of by-products, reactor energy demand and total energy demands for the process have been analysed with respect to temperature, ore grade (gangue content), and reactant conditions. The HSC Chemistry (H: enthalpy, S: entropy and C: heat capacity) SIM (simulation) module was employed for the modelling coupled with the Gibbs energy minimisation calculation. The shaft furnace was divided into three zones to model the three-step reduction of iron ore in a counterflow arrangement. Results show that temperature and hydrogen supply have a significant effect on the metallisation of DRI. Increasing temperature and hydrogen flow rate were predicted to increase the MR or reducibility. A full metallisation can be achieved with hydrogen supply of 130, 110, 100 and 90 kg/tDRI at 700, 800, 900 and 1000°C, respectively, using the best-grade ore (Fe 69 wt.%, gangue 5.2 wt.%). However, the hydrogen consumption in full metallisation was calculated to be 54 kg/tDRI (tonne of DRI). At full MR, the reactor energy consumption (supplementary electrical energy) was calculated to be 0.56 to 0.59 MWh/t Fefeed using the reactor temperature from 700 to 1000°C. Ore grade or gangue content has a significant impact on reactor energy demand. For example, at 900°C, the top-grade ore was calculated to consume 0.69 MWh/tDRI compared to 0.88 MWh/tDRI using the lowest grade ore. A certain percentage of CO (i.e. 15%) blended with hydrogen was predicted to be beneficial for metallisation, hydrogen consumption, and overall energy demand. However, increasing CO would increase CO2 emissions significantly.

Efficient Metal Extraction from Dilute Solutions: A Review of Novel Selective Separation Methods and Their Applications

Notable increases in metal consumption and declining ore grades in recent decades have stressed the significance of dilute solutions as secondary sources of valuable metals. Moreover, environmental considerations and the imperative of sustainable development have further emphasized their treatment. Therefore, finding an efficient solution for separating metals from dilute solutions has attracted the attention of numerous researchers. This paper reviews the purification processes of dilute solutions and highlights key achievements of published research works. Although this study focuses on evaluating the efficiency of recently developed aqueous-phase purification methods, such as immobilized ligands, ionic liquids, and air-assisted solvent extraction, the application of conventional processes to treat these solutions, such as solvent extraction, ion exchange, membranes, chemical precipitation, and adsorption are also briefly outlined. To provide a comprehensive assessment, more than 200 research articles were reviewed, and their key findings are stated in this study. This research contributes to the advancement of knowledge of metal recovery from dilute solutions and sheds light on the dynamic evolution of this field.

Green supply chain for steel raw materials under price and demand uncertainty

The scientific formulation of procurement and inventory plans is an important topic in the steel industry, when considering both economic and environmental impacts in an uncertain market environment. Robust optimization methods offer an effective solution to this problem. This study has investigated a multi-echelon and multi-period front-end supply chain centered on a steel enterprise under uncertain purchase prices and demand. The goal is to minimize the costs associated with mining, processing, transportation, procurement, and inventory along with the corresponding carbon emission costs. To address this issue, we present a robust rolling horizon model (RRHM) that considers the inventory capacity constraints of steel enterprise and incorporates ore grade requirements. Subsequently, the RRHM was reformulated into a solvable mixed-integer linear programming model, and the relationship between the robust model and a specific deterministic model was established. Finally, the model was validated by generating instances based on real scenarios. The results demonstrate that the robust rolling horizon model proposed in this paper outperforms both the Sample Average Approximation (SAA) strategy and the (s, S) strategy in terms of cost and robustness. In addition, a sensitivity analysis of the key parameters was conducted. The findings reveal that the unit inventory, mining, and carbon emission costs have a limited impact on the total cost, highlighting the robustness of the model. These findings provide valuable insights into the green and sustainable development of the steel industry, enabling the formulation of effective strategies to mitigate the impacts of uncertainties.

A lithium ore grade measurement based on the neutron & X-ray bi-modal imaging system

The grades of the minerals significantly affects the energy consumption and chemical pollution along with the beneficiation process for extracting lithium element from the ores. Based on the large neutrons’ macro cross section of the Li2O cluster inside the ores, the grades of lithium ores could be analyzed by the thermal neutron penetrating information. In this work, a bimodal imaging method, which utilizes both the information of penetrating neutrons and X-rays delivered by the same electron linear accelerator driven photoneutron system, was proposed to investigate the lithium concentration of each ore. A linearity R-square value of 0.991 between the results obtained with this method and those from the chemical method has been achieved. The average error in lithium concentration estimation is approximately 0.2 wt percent (wt%). The underlying principles and the experimental results will be elaborated on in this study.

The race for critical minerals in Africa: A blessing or another resource curse?

There is currently an exponential growth in the global demand for critical minerals, particularly lithium, to meet clean energy and decarbonisation objectives. However, sustainable supply of these minerals is at risk due to declining ore grades, available extraction and processing technologies, socio-environmental concerns, and geopolitical challenges. Africa hosts substantial critical minerals resources, and the continent is currently being positioned as a major global player in the critical minerals supply chain. As a result, there is a rush for Africa's critical mineral resources through investment in exploration activities and license acquisition by foreign mining companies. Drawing on the case of lithium mining in Africa, we analysed the urgency claims of critical minerals in the African context and assessed the inherent socio-ecological impacts. We found that the urgency claims of critical minerals largely serve the geostrategic and economic interests of western countries and China. The rush for Africa's critical minerals is producing significant socio-ecological impacts, including driving loss of rich biodiversity, displacement of communities and breeding new forms of illegalities in the resource sector. Based on our findings, we argue that the current race for Africa's critical mineral resources does not serve the interest of Africa and it is likely to create adverse long-term socio-ecological impacts rather than benefits for the continent unless appropriate sustainable measures, including strategic planning, are carefully considered, and fully implemented. Our findings have implications for policies seeking to promote sustainable and responsible mining in Africa, and elsewhere with similar challenges.