Iron Ore Research Articles

Stabilization of iron ore tailings with fly ash as binder material for sustainable backfill applications: mechanical, environmental, and microstructural assessment

Stabilization of iron ore tailings with fly ash as binder material for sustainable backfill applications: mechanical, environmental, and microstructural assessment

Fe2+/Fe3+ Intervalence Charge Transfer and Enhanced d-d Absorption in Mixed Valence Iron Minerals at Elevated Temperatures

Abstract The absorption of light by Fe/Ti and Fe/Fe intervalence charge transfer (IVCT) bands has previously been found in aluminum oxide and Al2SiO5 aluminosilicate minerals to decrease markedly at elevated temperatures. Given the abundance of iron at depth in the Earth, assessing the generality with which and extent to which IVCT mineral phases become more optically transparent at temperature than they are under ambient conditions has potentially significant implications for the modeling of mantle geophysical processes such as radiative conductivity. A broad experimental survey of the optical absorption spectra at elevated temperatures of various mixed valence iron minerals has been conducted. The minerals considered here are cordierite, chloritoid, lazulite, dumortierite, jeremejevite, beryl, osumilite, biotite (mica), pargasite (amphibole) and aegirine (pyroxene). All samples transiently lose significant Fe/Fe IVCT feature intensity at temperature. In beryl, osumilite, biotite, pargasite and aegirine, spin-allowed Fe2+d-d features also decrease in integral intensity at temperature; in all but beryl, the intensity loss is significant. This trend is consistent with d-d band enhancement via Fe2+/Fe3+ exchange coupling, which has not previously been identified in the majority of these minerals. It is contrasted against the behavior of ordinary spinallowed Fe2+d-d bands in non-IVCT minerals forsterite (olivine) and elbaite (tourmaline). The depletion of Fe/Fe IVCT and enhanced Fe2+d-d band intensity at elevated temperatures may both be important mechanisms by which iron-bearing mineral phases become more optically transparent under conditions at depth.

Iron-mineral-induced visible-light-catalytic degradation of BDE-47 enhanced by low-dose persulfate: Kinetics, mechanisms, and intervention of environmental factors.

Iron-mineral-induced visible-light-catalytic degradation of BDE-47 enhanced by low-dose persulfate: Kinetics, mechanisms, and intervention of environmental factors.

Mechanistic Study of Interface Regulation by Pullulan as an Eco-Friendly Depressant for Selective Flotation of Apatite from Hematite.

The selective flotation of apatite and hematite in high-phosphorus oolitic iron ore is challenging due to the declining selectivity of reagents as the particle size decreases. This study explores pullulan as an eco-friendly depressant in combination with α-bromolauric acid (α-BLA) as a collector. Microflotation experiments showed that while α-BLA exhibited a strong collection ability, its selectivity was poor. Adding pullulan created a hydrophilic layer that suppressed hematite flotation while enhancing apatite recovery. Under optimal conditions (pH 9, α-BLA 28.57 mg/L, pullulan 1.43 mg/L), the phosphorus content in the concentrate decreased from 8.83 to 0.97%, while iron recovery reached 86.83%, confirming the effectiveness of this reagent combination. Interfacial characterization and extended Derjaguin-Landau-Verwey-Overbeek (E-DLVO) calculations revealed that pullulan preferentially adsorbs on hematite, altering its wettability and charge, simultaneously hindering α-BLA adsorption. Additionally, the active site density on the mineral surface influences reagent adsorption and bubble attachment. These results highlight the synergistic effect of α-BLA and pullulan, offering a sustainable phosphorus-containing iron ore beneficiation strategy.

Effect of boron oxide additives on viscosity and melting point of the CaO – SiO2 – Al2O3 – MgO system

The share of local iron ore raw materials of metallurgical enterprises of the Ural region is 50 – 60 %. The rest is brought from Central Russia, the Kola Peninsula and Kazakhstan. The issue of replacing imported raw materials with local, cheaper ones, is very relevant. The extraction of siderite iron ore of the Bakalskoye deposit (Southern Urals), the reserves of which are about 1 billion tons, is many times less than the mining and geological conditions allow because of the insignificant demand for this raw material due to its low quality. The high content of magnesium oxide in the ore makes blast furnace smelting difficult or impossible using more than 20 % of siderites in the charge. The basis of any blast furnace slag is a four-component system CaO – SiO2 – Al2O3 – MgO with the following composition, wt. %: 30 – 40 SiO2 , 31 – 49 CaO, 3 – 18 MgO, 7 – 20 Al2O3 . The melting point of such slags is 1280 – 1320 ℃. At a temperature of 1450 °C, their viscosity is about 0.5 Pa·s. An increase in the magnesium oxide content (>20 %) leads to a sharp increase in melting point of the slags, reduces the crystallization interval and makes them unstable. In this regard, the materials made from siderite ore using various technologies for preparing them for blast furnace smelting (raw ore, roasting-magnetic separation, agglomeration) are introduced into the blast furnace charge only as additives. Their share does not exceed 20 %. The effect of boric anhydride on the viscosity of high-magnesia blast furnace slags containing 15 – 36 % MgO was studied using modern methods of statistical processing of experimental data. It was shown that addition of boric anhydride to the initial charge allows to reduce the melting point of the slag and to increase the crystallization interval. This makes it possible to conduct blast furnace smelting on slags containing about 40 % MgO, which corresponds to a siderite share of 40 – 50 % in the initial charge.

Iron minerals as catalysts in photo-assisted NO3– reduction in aqueous phase

Iron minerals as catalysts in photo-assisted NO3– reduction in aqueous phase

Debunking the myth of a single Iron Ore Group in the Singhbhum Craton, India

Debunking the myth of a single Iron Ore Group in the Singhbhum Craton, India

Pore network modeling of iron ore agglomerates: Development of a methodology based on X-ray microtomography

Pore network modeling of iron ore agglomerates: Development of a methodology based on X-ray microtomography

Emission characteristics and removal efficiencies of SO2, NOx, particulate matter, and dioxins in iron ore sintering after ultra-low emission transformation

Emission characteristics and removal efficiencies of SO2, NOx, particulate matter, and dioxins in iron ore sintering after ultra-low emission transformation

Challenging paradigms: The advantages and drawbacks of vertical mills in secondary grinding for iron ore processing

Challenging paradigms: The advantages and drawbacks of vertical mills in secondary grinding for iron ore processing

Deciphering Temperature‐Dependent Synergistic Mechanisms in Ammonia‐Mediated Iron‐Ore Reduction: Kinetic Optimization for Carbon‐Neutral Steelmaking

This study examines the direct reduction of iron ore using ammonia as a low‐carbon alternative to coke‐dependent blast furnaces in steelmaking. Experimental and thermogravimetric analyses of goethite (H1) and vanadium‐titanium ore (H2) reveal temperature‐dependent NH3 synergies. H1 undergoes complete reduction at 900 °C with 5% NH3, while reduction at 700 °C requires 30% NH3. High temperatures (>850 °C) favor direct formation of Fe over Fe3O4/Fe4N intermediates, while crystalline water removal at 500 °C impedes reduction through steam generation. Kinetic analysis shows that the reduction degree of H1 is 20% higher than that of H2 at 950 °C/60% NH3. This can be explained by the porous structure of H1, unlike the dense Ti–Fe lattice in H2, where TiO2 induces steric hindrance. The R1 kinetic model [G(α) = −ln(1 − α)] effectively describes the reduction process, demonstrating a linear relationship between the reaction degree and NH3 partial pressure. Specifically, increasing NH3 concentration from 40% to 60% boosts degree constants by 48.4–60.4%. The findings position ammonia as a viable candidate for decarbonizing ironmaking, providing critical insights for optimizing reduction parameters and promoting sustainable steel production through fossil fuel substitution. Overall, this work addresses a critical knowledge gap in low‐carbon metallurgy and suggests actionable strategies for industry implementation.

Effects of different natural organic matter on catalytic properties of green rust: Mechanism and environmental significance.

Effects of different natural organic matter on catalytic properties of green rust: Mechanism and environmental significance.

Studies on characterisation of phosphorous in haematite iron ore

Due to the rapid depletion of high-grade iron ores in the world, the iron production from comparatively lower grade iron ores containing higher amount of gangue or higher impurities like phosphorous is now the main focus for the iron and steel industries. The current study has been carried out to understand the distribution and association of phosphorus in a high-phosphorous iron ores from the eastern part of India containing ∼55.4% Fe and 0.56% phosphorous (P). Mineralogical and thermal characterisation studies were carried out by using advanced characterisation techniques like optical microscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy, thermogravimetric analysis, differential scanning calorimetry, etc. SEM and electron probe micro-analyser study suggests that iron and alumina-rich gangue minerals are mostly associated with the phosphorous content of iron ore. This high-phosphorous iron ore consists of major phosphorus-bearing phase called berlinite (AlPO 4 ). The gangue minerals (alumina) were found to be principally associated with the phosphorous. The size-wise chemical analysis suggests that the presence of phosphorous increases at finer size fractions, phosphorous mineral liberation is possible at finer size factions for better beneficiation. XRD analysis suggests that phosphorus in iron ores is most likely found as a crystalline phase (berlinite AlPO 4 ) rather than as an amorphous phase and the berlinite phase increases with an increase in the phosphorous level of iron ores.

Measurement uncertainty of the mass fraction of total iron in iron ores, concentrates, agglomerates, and pellets

The paper considers the measurement of the mass fraction of total iron by the titrimetric method. A description of the measurement technique is given. It is shown that a special feature of the titrimetric method is the need to use a certified reference material with a known value of the mass fraction of total iron, which in this case acts as a reference measure with the value of which the corresponding value in the sample of the substance under consideration is compared. When implementing the measurement technique, two consistent input quantities are measured – the mass of the sample and the volume of the titrated solution; therefore, to determine both the titre and the mass fraction of total iron, the reduction method is used. In this case, it is necessary to separately evaluate the combined instrumental uncertainty of the measurements and the standard uncertainty of repeatability, based on which it is possible to calculate the standard and expanded uncertainty of the measurand. Procedures for the uncertainty evaluation of the titre and mass fraction of total iron measurements have been developed. Uncertainty budgets for these quantities have been evaluated. Examples of the uncertainty evaluation of the titre and mass fraction of total iron measurements based on real laboratory data and metrological characteristics of the measuring equipment used are considered.

An Evaluation of Carbon Emissions Based on the Hidden Markov Model

To address the challenge of assessing carbon emissions in the iron ore sintering process, characterized by dynamic complexity, strong temporal correlations, and multi-stage coupling, this study innovatively introduces the Hidden Markov Model (HMM) into the field of carbon emission analysis. We propose a method for process stage identification and carbon emission modeling based on a Gaussian Hidden Markov Model (Gaussian HMM). The model defines the four stages of the sintering process as hidden states and uses six-dimensional flue gas monitoring data (temperature, SO2 concentration, NO concentration, NOx concentration, O2 content, CO concentration) as the observation sequence, with Gaussian distributions describing the emission characteristics of each stage. The research employs the Random Forest algorithm to impute missing values and correct outliers in the raw data, followed by standardization to eliminate scale differences. Model parameters are initialized using Maximum Likelihood Estimation (MLE) and iteratively optimized via the Forward-Backward and Baum-Welch algorithms to enhance the model's fitting capability for complex temporal data. The Viterbi algorithm dynamically decodes the hidden state sequence, enabling an online "predict-until-cooling" monitoring strategy. This strategy accurately determines the optimal cooling timing to balance combustion efficiency with the reaction endpoint. This approach prevents incomplete iron ore combustion and low raw material utilization, while simultaneously reducing emissions of harmful gases and greenhouse gases, thereby achieving the goal of lowering carbon emissions. It provides technical support for the refined management of carbon emissions.

Assessment of whole-body vibration exposures among dumper operators in iron ore mines: a comparative investigation of haul truck activity

This study aimed to fill the research gap on whole-body vibration (WBV) exposure of dumper operators in India, conducting a comprehensive investigation into specific phases of dumper operations. Results indicated that 59% of operators exceeded lower limits, with 90.8% exposed to vibration levels surpassing the lower limit for A(8) and VDV(8) values. Frequency analysis identified peaks aligning with crucial body parts, corroborating epidemiological findings. Statistical analysis (ANOVA) demonstrated significant differences in WBV exposure across activity groups (p < 0.001), dumper speeds (p < 0.001), and haul road conditions (p < 0.001). Optimising driver speed, improving haul road surfaces, and regular vehicle maintenance are some recommendations to reduce WBV exposure among dumper operators.

Study on Quantitative Color Characterization and Color‐Property Relationships of Finished Iron Ore Pellets

The color of pellet ores is quantitatively characterized based on the colorimetric method. Multiscale structural characterization and detection experiments clarified the coloring mechanism and the color–structure–property relationship of iron ore pellets. The results reveal that the chromatic difference originates from the competition between surface optical reflection and internal reflection of hematite. Fully roasted blue pellets exhibit a bluish‐gray hue dominated by specular reflection due to densified surfaces (low porosity and high crystallinity), while under‐roasted red pellets display a reddish‐brown coloration amplified by internal reflection from porous structures (high porosity, surface roughness) and grain boundary defects. Quantitative colorimetry demonstrates that blue pellets possess significantly higher luminance (L*) and lower red/yellow chromaticity (a*, b*) compared to red pellets, confirming the correlation between color parameters and microstructure. Tests indicate that blue pellets exhibit 700–900 N/pellet higher compressive strength, yet their dense structure restricts CO diffusion, leading to 4–7% lower reduction swelling and 1–5% decreased reducibility. Linear regression models based on colorimetric parameters validate the feasibility of using optical characteristics to predict compressive strength (R2 = 0.794–0.823, p &lt; 0.01). This work provides theoretical insights into optimizing pellet roasting processes and balancing color–structure–performance.

Leveraging machine learning for monitoring afforestation in mining areas: evaluating Tata Steel's restoration efforts in Noamundi, India.

Mining activities have long been associated with significant environmental impacts, including deforestation, habitat degradation, and biodiversity loss, necessitating targeted strategies like afforestation to mitigate ecological damage. Tata Steel's afforestation initiative near its Noamundi iron ore mining site in Jharkhand, India, spanning 165.5 hectares with over 1.1 million saplings planted, is a critical case study for evaluating such restoration efforts. However, assessing the success of these initiatives requires robust, scalable methods to monitor land use changes over time, a challenge compounded by the need for accurate, cost-effective tools to validate ecological recovery and support environmental governance frameworks. This study introduces a novel approach by integrating multiple machine learning (ML) algorithms, classification and regression tree (CART), random forest, minimum distance, gradient tree boost, and Naive Bayes, with multi-temporal, multi-resolution satellite imagery (Landsat, Sentinel-2A, PlanetScope) on Google Earth Engine (GEE) to analyze land use dynamics in 1987, 2016, and 2022. In a novel application to such contexts, high-resolution PlanetScope data (3m) and drone imagery were leveraged to validate classification accuracy using an 80:20 training-testing data split. The comparison of ML methods across varying spatial resolutions and temporal scales provides a methodological advancement for monitoring afforestation in mining landscapes, emphasizing reproducibility and precision. Results identified CART and Naive Bayes classifier classifiers as the most accurate (83% accuracy with PlanetScope 2022 data), effectively mapping afforestation progress and land use changes. These findings highlight the utility of ML-driven remote sensing in offering spatially explicit, cost-effective monitoring of restoration initiatives, directly supporting Environmental, Social, and Governance (ESG) reporting by enhancing transparency in ecological management.

Food Porridges Based on Quinoa, Amaranth and Cañahua Complemented with More Flavoring Milk Powder, for a Children&amp;apos;s Population Under 2 Years Old

Children&amp;apos;s nutrition is affected by the great changes produced by the lifestyles of populations. The nutritional status in children was ignored for quite a long time; today many countries are looking for solutions to the problems of malnutrition and poor nutrition, causing nutritional deficit in children due to various factors, such as economic, social, cultural and food availability. Scientific evidence has shown that adequate nutrition can help the population promote optimal health. Therefore, the objective is the “Biological study of food porridge based on quinoa, amaranth and cañahua complemented with more flavored milk powder, for a child population under 2 years of age.” Through processes of obtaining flour, formulation, production, biological evaluation and analysis of iron and zinc minerals in mixtures of food porridge, liver, thymus and femur. The result of the theoretical formulation for the Standard Diet presents 11,7 g of protein and 419 kcal, iron 0,1 mg, zinc 1,5 mg, for the food mixtures based on Andean grains plus flavoring have a range of 11,6-12,1 g of protein, 380,6-389,6 kcal, iron 6,4-10,4 mg, 0,0-2,9 mg of zinc. The biological parameters for the Standard Diet present a IP of 142,8, REP 2,7 and %Da 89,2; for the food mixtures based on Andean grains plus flavoring, they fluctuate from 26,8-72,9 for the IP, the REP with 1,0-1,9 and %Da 65,4-81,9, lower than the Standard Diet. For the food mixtures based on Andean grains plus flavoring and milk powder, they present values in a range of 11,6-11,7 g of protein, 382,3-388,0 kcal, iron 2,8-4,9 mg and zinc 1,0-2,4 mg, the IP of 173,3-185,6, REP 2,9-3,5 and %Da of 79,2-85,8 higher than the Standard Diet in terms of IP and REP. In conclusion, the proposed food mixtures based on Andean grains plus flavoring and milk powder are excellent for the preparation of food porridges.

The limitations of flotation technique in processing complex Um Nar BIF: exploring sustainable alternatives

Abstract Iron is essential for industry and the economy. It is used in construction, transport, and manufacturing. However, its extraction remains challenging due to geological complexity. Iron ore is tightly interlocked with silica, which limits the efficiency of conventional beneficiation methods. This study investigated the upgrading of the Um Nar Banded Iron Formation using froth flotation, including micro-scale tube and column flotation. Both anionic and cationic reverse flotation routes were explored. It was found that using anionic reverse flotation is more effective than cationic reverse flotation for upgrading the Um Nar Banded Iron Formation (BIF). Under optimal conditions (i.e. collector type: oleic acid, dosage: 1 kg t−1; calcium oxide dosage: 0.25 kg t−1 (as activator); pH 11; and starch dosage: 0.75 kg t−1 (as depressant)), a concentrate with 58 % total Fe grade, 71 % total Fe recovery, and 10.75 % SiO2 was produced at superficial air flow rate of 2.00 cm s−1, which was attributed to the intricate mineralogy of the ore. To overcome the limits of flotation, the study used reduction roasting with biomass sawdust as a green reductant. After roasting, a low-intensity wet magnetic separation was applied. This two-step process yielded improved results, achieving a Fe grade of 59.55 %, a Fe recovery of 78 % and a SiO2 content of 5 % in the concentrate, rendering it suitable for processing complex iron ores.