Iron Ore Research Articles

Effect of BaSO4 on Phase Transformation and Microstructure of CaOFe2O3TiO2 System During Sintering

The Fe2O3CaOTiO2BaSO4 system is established through miniature sintering experiments to reveal the mechanism of BaSO4 and vanadium‐titanium magnetite (VTM) with the help of X‐ray diffraction, scanning electron microscope and energy dispersive spectroscopy, and thermogravimetry. The results show that in the absence of BaSO4, the phase of the sinter consists of CaFe2O4, TiO2, Fe2O3, CaTiO3, and CaFe2O5. When the content of BaSO4 is 1% and 2%, CaTiO3 decreases and the number of needle‐like CF increases. Some Ba2+ solidly dissolve into CF and CaTiO3 to form trace BaFe12O19 and BaTi2O5. When the content of BaSO4 increases to 4%, the CaSO4 phase appears, the formation of C2F is accelerated, and the content of CF and CaTiO3 continues to decline. The needle‐like calcium ferrate gradually transforms into columnar and lamellar. As the BaSO4 content continues to increase to 6% and 8%, although the trend of each phase is similar to that at 4%, it is almost entirely composed of columnar calcium ferrite, barium ferrite, and incomplete tetragonal and rhombic Fe2O3. The results of the study provide a theoretical basis for the utilization of VTM and barium‐containing iron ores in practical production.

Evaluating Swarm Robotics for Mining Environments: Insights into Model Performance and Application

The mining industry is experiencing a transformative shift with the integration of automation, particularly through autonomous haul truck systems, and further advancements are anticipated with the application of swarm robotics. This study evaluates the performance of four swarm robot models, namely baseline, ant, firefly, and honeybee, in optimizing key mining operations such as ore detection, extraction, and transportation. Simulations replicating real-world mining environments were conducted to assess improvements in operational efficiency, scalability, reliability, selectivity, and energy consumption. The results demonstrate that these models can significantly enhance the precision and productivity of mining activities, especially in complex and dynamic settings. A case study of the Pilbara iron ore mine in Australia is presented to illustrate the practical applicability of these models in an actual mining context. The study also highlights specific enhancements in each model, including role specialization in the ant model, advanced communication in the firefly model, and improved localization combined with hybrid control in the honeybee model. While the honeybee model showed superior performance in high-precision tasks, its reliability was limited under high-error conditions, and it faced a computational resources bottleneck in large-scale operations, highlighting the need for further development. By evaluating these models against performance criteria, the study identifies the most suitable swarm models for various mining conditions, offering insights into achieving more sustainable, scalable, and efficient mining operations.

Sensitization and Mechanical Response of Cu‐Containing Steel Rods

The iron and steel manufacturing sector significantly adds to global greenhouse gas emissions, caused primarily by the carbothermic reduction of iron ore. Recycling scrap steel offers an effective decarbonization strategy but introduces impurities like copper (Cu) that can negatively impact mechanical properties. This study investigates the effects of Cu content and heat treatment on the mechanical performance and sensitization of steel wire rods for tire manufacturing. Steel rods with 0.04 and 0.21 wt% Cu are heated to 1050 or 1200 °C, then air quenched, or furnace cooled. Tensile testing coupled with microscopic analysis is used to evaluate mechanical properties and assess the sensitization effects. Higher Cu content leads to larger sensitized zones with increased Cu precipitation along grain boundaries. Ductility and toughness, crucial for wire drawability, are found to be reduced, despite higher ultimate strength. Slower furnace cooling is seen to result in smaller sensitized zones compared to air quenching, suggesting a pivotal role of cooling rate in sensitization control. The findings provide insights into optimize heat treatment parameters and Cu content limits, balancing mechanical performance and maintaining drawability for enhanced scrap steel recycling in tire production.

Application of SAP to Improve the Handling Properties of Iron Ore Tailings of High Cohesiveness: Could a Reagent Help the Decommissioning Process of a Dam?

This work aims to evaluate the use of a superabsorbent polymer (SAP) to provide improvements in the handling properties of iron ore tailings (IOT). The material studied came from the magnetic separation reprocessing of the material discarded at the Gelado Dam, located in Serra dos Carajás in the state of Pará, Brazil. While the concentrate presents reasonable handling conditions, the tailings, with 61.5% iron, 15% moisture, and 39% of the mass, have high cohesiveness and adhesiveness due to their fine nature and the climatic conditions of the Amazon rainforest. However, the tailings can still be considered a product as long as the handling and transportation logistics are feasible. Thus, studies with an SAP and IOT were carried out in a bench rotating drum to promote mixing between them, and the main variables studied were the SAP dosage and the required contact time. The improvement in the physical properties of the IOT were evaluated considering the Hausner ratio, Carr index, Jenike’s flow function index, Atterberg limits, and chute angle. The superabsorbent polymer promoted a significant improvement in the state of consistency of the material, and the best performance was obtained with a dosage of 1000 g t−1. As long as a suitable contact condition was promoted, a contact time of 1 min was enough to achieve the expected benefits. After dosing with the superabsorbent polymer, the material’s handling classification changed from ‘cohesive’ to ‘easy flow’, and the chute angle was reduced from 90° to levels below 60°. It was concluded that the application of the superabsorbent polymer has the potential to improve the fluidity of the material discarded in the magnetic concentration operation, allowing it to be handled throughout the production and transportation chain. The SAP appears to be an important additive for the full use of the material present in the dam (100% recovery), with both economic and socio-environmental benefits.

Hybrid multi-stage steel footprinting unveils a more interdependent material foundation of the global economy

Steel is foundational to modern society, yet tracking its socio-economic metabolism is challenging due to the complex global trade networks. Traditional indicators, such as domestic material consumption (DMC) and consumption-based material footprints (MF), typically focus on metal ore extraction, overlooking the multiple stages of steel production and consumption. To address this, we integrate multi-national anthropogenic steel cycles and international trade networks of steel-containing products into a global monetary multi-regional input-output (MRIO) model. We construct material efficiency indicators based on footprints of iron ores, crude steel, castings, finished steel, and fabricated steel products, comparing them with conventional economy-wide material flow indicators like domestic material production (DMP) and DMC. Our findings reveal that per capita multi-stage MF indicators exhibit more robust log-linear relationships with per capita GDP with an average R2 value of 0.72 compared to 0.10 and 0.18 for DMP and DMC. Shares of Embodied trade in total global production exceed direct trade by 24 percentage points on average, emphasizing the significance of international embodied metal transfers. Using multi-stage MF indicators also reduces disparities in material efficiency between developed and developing countries. This study unravels the intricacies of global steel supply chains and the true interdependencies of steel-containing products among countries.

Crystalline iron oxide mineral (magnetite) accelerates methane production from petroleum hydrocarbon biodegradation

Methane (CH4) emissions are a factor in climate change; in addition, CH4 production may affect reclamation of fluid fine tailings (FFT) in tailings ponds, and end-pit lakes (EPLs). In laboratory cultures, we investigated the effect of crystalline iron mineral (magnetite) on CH4 production from the biodegradation of hydrocarbons added to FFT collected from methanogenically more and less active sites in a demonstration EPL. Magnetite enhanced CH4 production from both sites, having a greater effect in more active FFT, where it increased the CH4 production rate as much as 48% (from 6.67 μmol d−1 to 9.87 μmol d−1) compared to FFT without magnetite. Correspondingly, magnetite hastened biodegradation of hydrocarbons (monoaromatics, n-alkanes and iso-alkanes), with a pronounced effect on o-xylene, ethylbenzene, m/p-xylenes, n-octane, n-nonane, and 2-methyloctane, where biodegradation rates increased by 46, 117, 11, 45, 28 and 37%, respectively, compared to FFT without magnetite. Little FeII was produced, suggesting that magnetite is not being used as an electron acceptor but rather functions as a conduit for electron transfer. Thus, magnetite may be a suitable amendment to enhance bioremediation of anaerobic environments contaminated with hydrocarbons. Importantly, our observations imply that magnetite may increase CH4 emissions from terrestrial ecosystems, thus affecting carbon budget estimations.

Transformation of iron-minerals from natural aquifer media by sulfate-reducing bacteria: Behavior, mechanism, and Cr(VI) removal

Sulfate-reducing bacteria (SRB) and iron minerals are widespread in subsurface environments, where their mediated Fe and S transformations are crucial for contaminant immobilization. However, the mechanism mediated by SRB to transform natural iron minerals into reduced iron–sulfur compounds and the contaminant removal capacity of the transformation products remain unclear. Herein, the mechanism of native SRB-mediated transformation of iron-minerals from natural aquifer media into biogenic ferrous sulfide (FeS) was revealed and the Cr(VI) removal performance of the transformation product was evaluated. The results showed that Fe2+ production, sulfate reduction, and sulfide production occurred sequentially (rather than simultaneously) in the liquid phase. This suggests new processes and mechanisms for iron-mineral transformation: first, iron minerals dissolve to produce Fe2+ under enzymatic action rather than sulfide reduction; then, the generated Fe2+ accelerates sulfate reduction by SRB, producing sulfide in large amounts; finally, sulfide combines rapidly with Fe2+ to produce FeS. Elevated temperatures markedly shortened the required transformation time to start: maximum Fe production occurred at 18–24 days, 6–12 days, and 0–6 days at 10 °C, 20 °C, and 35 °C, respectively. Ambient temperature strongly affected SRB community composition, with Desulfosporosinus dominant at 10 °C and 20 °C and Desulfotomaculales prevalent at 35 °C. Sequential extraction, scanning electron microscopy, X-ray photoelectron spectroscopy, and X-ray diffraction analyses confirmed FeS as the main transformation product, which exhibited a highly efficient Cr(VI) removal capacity. Extending transformation time or increasing transformation temperature enhanced the Cr(VI) removal capacity of the transformation product. In column experiments, in-situ stimulation of SRB growth in aquifer media is able to form FeS, the Cr(VI) removal capacity of FeS reached up to 90.1 mg(Cr(VI))/kg(media). These findings suggest that biostimulation of SRB to mediate the in-situ transformation of iron-minerals to FeS has great potential for remediation of contaminated groundwater.

Sustainable practices in steel manufacturing: Substitution elasticities between waste, raw materials, and energy for greenhouse gas emission reduction

This study investigates the potential of waste utilization to mitigate greenhouse gas (GHG) emissions within the steel manufacturing industry. Utilizing a translog production function, we analyze the substitution elasticities among scrap steel, iron ore, and energy, exploring their roles in carbon reduction. Our approach incorporates the Resource Efficiency and Climate Change Mitigation model to simulate the impact of various waste utilization strategies on GHG emissions. The findings highlight that scrap steel and iron ore exhibit substitution dynamics. Iron ore and energy exhibit complementary relationship, and there is also a complementary relationship between scrap steel and energy but with lower elasticity, indicating that increasing scrap steel usage can significantly reduce emissions while decreasing iron ore demand. Specifically, enhancing the input efficiency of scrap steel in secondary steel production can reduce GHG emissions by over 8.3 tons for each additional ton produced—surpassing the impact of merely increasing the volume of reused material, which offers a reduction of more than 2.2 tons per ton. The strategies centered on reduction and recycling demonstrate even lower GHG reduction efficiency. The findings advocate for governmental intervention to promote and support waste reuse initiatives, highlighting the potential environmental benefits and efficiency gains from such policies.

A combination of XGBoost and neural network in LIBS spectrum processing for precise determination of critical elements in 620 iron ore samples of various origins

China is the worldwide largest importer of iron ores for supplying its iron and steel industries. The necessary inspections of iron ores not only concern total iron content but also involve minor elements, such as silicium, aluminum, magnesium, and calcium. Laser-induced breakdown spectroscopy (LIBS) promises in situ and on-site detection and analysis capabilities, which is required for efficient, reliable, and large-scale impartation inspections. Such opportunity represents at the same time, a challenge for the technique in terms of the quantitative analysis ability. A fundamental issue corresponds to the matrix effect in LIBS analysis due to a large diversity of iron ores in terms of mineralogical and chemical compositions. Demonstrated as effective to deal with the matrix effect in LIBS analyses of geological materials, the machine learning approach needs to be implemented within an optimized data processing pipeline, combining algorithms carefully chosen and tested. In this work, we developed a sequentially connected combination of an extreme gradient boosting (XGBoost) model and a back propagation neural network (BPNN) model, to effectively fit the functional relation between the concentrations and the spectra. The specificity of the approach consists in fitting the linear, low-order nonlinear, and high-order nonlinear terms in a sequential way to substantially improve the model prediction performances. The method has been developed and tested with a significant set of 620 collected iron ore samples of eight production countries and 35 different commercial brands, with a wide range of matrices in terms of mineralogical and chemical compositions. The samples underwent prior characterization using conventional laboratory analysis methods to establish the reference elemental concentrations. The results from this necessary step of laboratory investigation, with root mean square error for prediction (RMSEP) of 0.407 wt%, 0.372 wt%, 0.085 wt%, 0.131 wt%, and 0.114 wt%, respectively for total iron (TFe), SiO2, Al2O3, MgO, and CaO, show the potential for on-site inspections.

Study on single particle compression crushing characteristics of iron ore with five different particle sizes

The mechanical properties of particulate materials are among the main factors affecting the grinding and crushing of ball mills. To quantitatively describe the relationship between the breakage characteristics and the stress intensity of irregular particulate materials, this study takes iron ore particles as the research object. It selects five particle size grades of iron ore particles (−4.75 + 3.35, −6.7 + 4.75, −9.5 + 6.7, −13 + 9.5, and −16 + 13 mm) for single particle strength tests. The results showed that the iron ore particles were irregular with certain slenderness and flatness characteristics. The larger the particle size, the lower the sphericity, and the greater the degree of irregularity. As the size of the iron ore particles increased, the number of peak points on the pressure–displacement curve of the particles increased significantly, and the crushing load increased. The single-particle strength of the iron ore particles followed a Weibull distribution, and the Weibull modulus parameter ranged between 2.03 and 2.49.

Sintering enhancement process based on fluidity and bonding phase strength

The sintering process is influenced by complex low-grade ores. This study used seven types of imported iron ore, A–F and domestically produced iron ore, G, as raw materials to study their chemical composition, as well as the liquid fluidity and bonding strength of the mixed ore after single and optimised ore blending. The high-temperature characteristic test values of mixed ores are positively correlated with the weighted calculated values of individual ores. Under the sintering cup conditions, the optimal ore mixing includes a 9% increase in liquid fluidity and a 6% increase in bonding strength. The latter significantly improved the sintering yield and drum strength, reaching 75.89% and 65.67%, respectively. In addition, the consumption of solid fuel has slightly decreased by 0.06 kg·t−1, and the utilisation coefficient has slightly increased. In addition, the sintering yield and quality indicators of the scheme have been comprehensively improved. Compared with the benchmark scheme, through liquid fluidity optimisation, an increase in magnetite phase, a decrease in haematite, and a significant decrease in acicular calcium ferrite were observed, interwoven with magnetite. The silicate-bounding iron oxide also showed an increase in this optimisation. In the optimisation of bonding strength, the corrosive structure interwoven with magnetite and needle shaped ferrite significantly increases, while the iron oxide bound with silicate decreases. The improvement effect of liquid phase fluidity and bonding phase strength optimisation on sintering process and mineralisation behaviour was verified through sintering cup test and mineral phase analysis.

Synergistic release of Cd(II) and As(V) from ternary sorption systems containing ferrihydrite nanoparticles: The role of binary and ternary surface complexes

Cadmium (Cd) and arsenic (As) generally exhibit mutually beneficial co-sorption behavior on iron oxyhydroxides through multiple mechanisms, including surface precipitation, ternary surface complexes, and electrostatic interactions. However, the numerous factors that control the immobilization of Cd and As in turn complicated the processes and mechanisms involved in their co-desorption from iron minerals, which hindered the full understanding of their geochemical behaviors. Here, the simultaneous release of Cd(II) and As(V) from newly precipitated ferrihydrite nanoparticles by either Ca or P was investigated through kinetics and isothermal desorption experiments. We showed that the Cd(II) and As(V) present two-phase desorption processes (rapid desorption and slow desorption) in both binary (Fe–Cd or Fe–As alone) and ternary systems (Fe–Cd–As co-presence). Compared to their binary counterparts, Cd(II) and As(V) in the ternary systems are more prone to detachment from ferrihydrite. Further desorption of Cd(II) and As(V) at different co-presence scenarios (different initial concentrations) demonstrated mutual promotion behaviour towards their counterparts; the co-presence of Cd(II) facilitates the desorption of As(V), while the co-presence of As(V) also promotes the desorption of Cd(II). XPS and FTIR results demonstrated that either Ca or P showed minor effects on the binding environment of Cd and As. Further results from the in-situ ATR-FTIR experiment and second derivative peak fitting analysis indicate that the enhanced detachment of Cd(II) and As(V) from the ternary system may be due to the synergistic desorption of the ternary surface complexes and other surface complex species. Our results provide new insights into the prediction of the environmental behaviour of the coexistence of Cd(II) and As(V) in iron-rich geological settings. The potential environmental risks of iron-based remediation methods should be considered due to the enhanced bioavailability of Cd(II) and As(V) in co-presence circumstances.

Contribution to the numerical modelling analysis of displacements caused by tunnel construction in discontinuous rock masses

This paper presents a comprehensive study of the stability conditions of a rock mass surrounding a tunnel, using numerical modelling analysis of displacements induced by the tunnel construction. The case study focuses on the Boukhadra iron ore mine in Algeria. This research employs empirical equations from literature based on geomechanical classifications to provide the most appropriate geotechnical input data for simulation. In addition to those equations, a novel correlation equation relating the rock mass ratio (RMR) and the rock quality index (Q) was developed. This equation gives a high regression coefficient, revealing a strong correlation (R2) of 0.878. It gives a better estimation of the rock mass characteristics: Young’s moduli (E), Poisson’s ratio (υ), cohesion (C), and friction angle (φ), compared to the existing literature-based correlation equations. The estimated parameters were used to pass from a discontinuous to a continuous equivalent medium, making the numerical modelling easier with the finite element method. Compared with intact rock and direct equations, the numerical simulation results based on the new equation fit well with the in-situ observations and provide a more reliable comprehension of rock mass behaviour. The new equation proposed in this paper provides a substantial evaluation of the rock mass parameters needed in the design process of underground structures once used with respect to their acceptable ranges.

Isothermal Reduction and Avrami–Erofeev Kinetic Model for Reducing Iron Ore Pellets in a 70% N2–30% H2/CO Atmosphere

Isothermal Reduction and Avrami–Erofeev Kinetic Model for Reducing Iron Ore Pellets in a 70% N2–30% H2/CO Atmosphere

High-modulus engineered cementitious composites: Design mechanism and performance characterization

Engineered cementitious composites features with high tensile performance while relatively weak compressive stiffness. This study endeavors to address the inherent trade-off between tensile properties and elastic modulus in conventional Engineered Cementitious Composites (ECC). Utilizing the distinctive characteristics of iron ore aggregates, known for their relatively stiff nature, smooth surface and rounded shape, an Iron Sand-based ECC (IS-ECC) emphasizing both high elastic modulus and ductility is formulated. Guided by micromechanical design theory and multiscale homogenization model, this study systematically explores the impacts of aggregate types, water-to-binder (w/b) ratios, sand-to-binder (s/b) ratios, and sand particle sizes on ECC properties. Compared with Quartz Sand-based ECC (QS-ECC), IS-ECC exhibits notably enhanced matrix fluidity and elastic modulus, reduced matrix toughness, and more robust strain-hardening behavior. The proposed three-level multiscale homogenization model accurately predicts the elastic modulus of ECC and provides insights into the underlying mechanism contributing to the enhanced elastic modulus of IS-ECC. With a resulting high elastic modulus of 33.3–48.6 GPa and superior tensile properties, IS-ECC holds promise for widespread applications in structural engineering.

Effect of calcite on the thermal decomposition of pyrite: Thermodynamics, phase transformation, microstructure evolution and kinetics

Pyrite, a common iron mineral in refractory iron ores, emits SO2 during oxidative roasting, contributing to environmental pollution. This study investigated the effect of calcite on the thermal decomposition of pyrite, focusing on thermodynamics, phase transformation, microstructural evolution, and non-isothermal kinetics, with emphasis on SO2 formation inhibition. Results showed that pyrite decomposed first to pyrrhotite, then to magnetite and hematite, with SO2 as the primary gaseous product. Higher temperatures and lower oxygen concentrations favored S2 gas formation. Non-isothermal decomposition of pyrite occurred between 400–725°C, initiated at the particle surface, and significantly increased product porosity, resulting in butterfly-shaped hematite. The addition of calcite resulted in the reaction of SO2 with calcite to form anhydrite on the particle surface, inhibiting the release of SO2. Initially, the thermal decomposition of pyrite proceeded with a low apparent activation energy, making the reaction relatively easy. However, the presence of calcite significantly increased the apparent activation energy and inhibited the thermal decomposition reaction.

Effects of residual elements on the microstructure and mechanical properties of a Q&P steel

Producing steel requires large amounts of energy to convert iron ores into steel, which often comes from fossil fuels, leading to carbon emissions and other pollutants. Increasing scrap usage emerges as one of the most effective strategies for addressing these issues. However, typical residual elements (Cu, As, Sn, Sb, Bi, etc.) inherited from scrap could significantly influence the mechanical properties of steel. In this work, we investigate the effects of residual elements on the microstructure evolution and mechanical properties of a quenching and partitioning (Q&P) steel by comparing a commercial QP1180 steel (referred to as QP) to the one containing typical residual elements (Cu+As+Sn+Sb+Bi<0.3wt%) (referred to as QP-R). The results demonstrate that in comparison with the QP steel, the residual elements significantly refine the prior austenite grain (9.7μm vs. 14.6μm) due to their strong solute drag effect, leading to a higher volume fraction (13.0% vs. 11.8%), a smaller size (473 nm vs. 790 nm) and a higher average carbon content (1.26 wt% vs. 0.99 wt%) of retained austenite in the QP-R steel. As a result, the QP-R steel exhibits a sustained transformation-induced plasticity (TRIP) effect, leading to an enhanced strain hardening effect and a simultaneous improvement of strength and ductility. Grain boundary segregation of residual elements was not observed at prior austenite grain boundaries in the QP-R steel, primarily due to continuous interface migration during austenitization. This study demonstrates that the residual elements with concentrations comparable to that in scrap result in significant microstructural refinement, causing retained austenite with relatively higher stability and thus offering promising mechanical properties and potential applications.

Two-way role of iron-carbon in biochemical reactions: microelectrolysis and enhanced activity of aerobic granular sludge for efficient refractory wastewater treatment

Industrial wastewater contained a large amount of refractory organics, and single treatment processes had limitations. This study investigated the mechanism of refractory organics removal using iron-carbon built-in coupled activated sludge (ICAS) and explored the role and function of iron-carbon (IC) within the ICAS system. The aerobic granular sludge (AGS) cultivated with IC exhibited a loose surface and a tight interior structure. Iron in the AGS concentrated near the outer layer to form a crust, which protected the inner microorganisms. IC promoted EPS secretion and regulated the abundance of positive and negative signaling molecules to maintain AGS stability. Experiments using quinoline as a model refractory organic showed that both physical adsorption by IC and biological adsorption by sludge rapidly fixed a large amount of pollutants, providing a buffer capacity for the system. The iron mineral crust on the AGS surface enhanced quinoline adsorption. Hydroxylation was the first step in quinoline degradation, with IC upregulating the genes iorA/B, qorB, and wrbA involved in this process, and the relative abundances of quinoline-degrading bacteria. Both pyridine ring opening and benzene ring cleavage occurred in the single IC system, and the microelectrolysis process produced •OH and [H], which made degradation pathway for quinoline through IC more complex than microbial degradation. Although the IC-mediated pathway accounted for only a small part of overall quinoline removal in the ICAS system, the ICAS system not only preserved the microelectrolysis process but also enhanced microbial metabolic activity. This work provided insights into the synergistic removal of pollutants and maintenance of AGS stability by the ICAS process, ensuring efficient treatment of refractory organic wastewater.

Molecular fractionation mediates genotoxicity evolution of hydrochar-derived dissolved organic matter at the iron oxyhydroxides-water interface

Adsorption fractionation of dissolved organic matter (DOM) induced by soil minerals is a common geochemical process, which has been widely documented on natural DOM. Hydrochar is a promising functional material in soil remediation but can continuously release abundant endogenic DOM with potential biotoxicity. However, adsorption fractionation at molecular level and its influence on toxicity evolution of hydrochar-derived DOM (HDOM) at genetic level at the soil-water interface remain poorly understood. Herein, we investigated the molecular fractionation of HDOM on three typical soil iron minerals (i.e., ferrihydrite, goethite, and hematite). Results from ultrahigh-resolution mass spectrum showed that HDOM molecules with high molecular weight and high contents of unsaturated oxidized or aromatic structures (e.g., unsaturated phenolic compounds, polyphenols, and organic acids) were preferentially absorbed by iron oxyhydroxides, while aliphatic molecules and poorly oxygenated compounds (e.g., hydrocarbon, phenols, and alcohols) were retained in aqueous phase. Furthermore, we quantitatively evaluated their genotoxicity variation using a toxicogenomics assay using green fluorescence protein-fused whole-cell array, and results showed that oxidative, protein, membrane, and DNA stresses were primary responses upon exposure to original HDOM. Interface fractionation induced by iron oxyhydroxides significantly reduced genotoxicity of HDOM, especially for oxidative, membrane and DNA stresses. Overall, the selective absorption of HDOM molecules by iron oxyhydroxides shifted its biotoxicity, which might change the ecological effects of hydrochar amendment, e.g., microbial community structure, environmental pollutant transformation, and even the ecological function of terrestrial and aquatic ecosystems. These findings would contribute to unraveling the environmental geochemistry process of HDOM in the natural soil-water interface and provide a new insight into the biotoxicity of hydrochar usage to terrestrial and aquatic environments.

A knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes

Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes. The number of structural planes and rock blocks were reduced in previous studies. This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks. In this paper, a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed. Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately. The proposed novel paradigm consists of (1) representing rock slopes as graph-structured data based on complex systems theory, (2) identifying key nodes in the graph-structured data using graph deep learning, and (3) mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope. Verification experiments and real-case applications are conducted by the proposed method. The verification results demonstrate excellent model performance, strong generalization capability, and effective classification results. Moreover, the real case application is conducted on the northern slope of the Yanqianshan Iron Mine. The results show that the proposed method can accurately identify key blocks in complex rock slopes, which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes, thereby ensuring the stability of rock engineering and the safety of life and property.