Antimony (Sb) contamination in water poses serious environmental and health risks. Although various adsorbents have been developed for Sb removal, the oxidation-state-dependent adsorption mechanisms and the respective roles of active metal sites in spinel ferrites remain insufficiently understood. In this study, spinel ferrite CuFe2O4 was synthesized using a solvothermal method and evaluated for its capacity to Sb(III) and Sb(V) through batch adsorption experiments combined with density functional theory (DFT) calculations. Adsorption exhibited a strong pH dependence, with optimal removal of Sb(III) at pH 7.0 and Sb(V) at pH 3.0, achieving Langmuir-fitted maximum adsorption capacities of 215.98 and 502.51 mg·g−1, respectively. Kinetic and isotherm analyses indicated chemisorption on heterogeneous surfaces as the main removal pathway. Common anions (Cl−, NO3− and SO42−) showed only minor effects, whereas PO43− significantly inhibited Sb(V) adsorption through competitive binding. Spectroscopic and microscopic characterizations indicated oxidation-state-dependent adsorption pathways, in which Sb(III) removal involved inner-sphere complexation accompanied by Cu-associated interfacial electron-transfer processes, whereas Sb(V) adsorption was dominated by electrostatic attraction and surface coordination. DFT calculations further identified Fe-O sites as energetically preferred adsorption centers for both Sb species, while Cu-containing sites contributed to interfacial electronic regulation rather than serving as the primary adsorption centers. These findings reconcile the apparent discrepancy between stronger local binding of Sb(III) and the higher macroscopic adsorption capacity of Sb(V). The complementary functions of Fe-centered adsorption and Cu-associated electron transfer provide mechanistic insight into the rational design of spinel ferrite adsorbents for the removal of redox-sensitive oxyanion contaminants.

Antimony (Sb) mobility in acid mine drainage (AMD) is strongly regulated by interactions with secondary Fe minerals and dissolved organic matter (DOM), yet how mineralogical heterogeneity modifies DOM-induced Sb redistribution remains poorly understood. Here, we investigated how DOM concentration and composition regulate Sb(V) retention and mobilization in a naturally derived multicomponent secondary iron mineral assemblage (nmSIM) and representative single Fe minerals, using humic acid (HA), fulvic acid (FA) and L-tryptophan (L-Trp) as representative DOM types. By integrating Sb retention/release measurements with Fe dissolution, mineralogical characterization and surface spectroscopic analyses, we identified a concentration-dependent shift in the relative importance of retention and mobilization processes. At relatively low DOM concentrations, HA and FA generally enhanced Sb(V) retention, whereas at higher concentrations they promoted Fe dissolution and Sb mobilization; L-Trp exerted substantially weaker and less systematic effects. Notably, nmSIM did not consistently exhibit lower initial Sb release than individual minerals. Instead, under HA and FA perturbation, it displayed a distinct temporal response, with relatively high initial Sb mobilization followed by attenuation or stabilization of dissolved Sb, whereas several single-mineral systems showed more sustained release. Mineralogical and surface-chemical evidence indicates that DOM-promoted dissolution of relatively reactive Fe-bearing phases was accompanied by phase evolution toward more crystalline Fe-(oxyhydr)oxide-rich surfaces. The concurrent decline or stabilization of dissolved Sb despite continued Fe release supports the involvement of newly generated Fe-bearing interfaces in subsequent partial Sb re-immobilization, although their mineral-specific contribution cannot be quantitatively resolved by the present data. Overall, the results reveal a two-level regulatory framework in which DOM concentration and composition govern the initial balance between Sb retention and mobilization, whereas mineralogical heterogeneity modulates the subsequent fate of mobilized Sb through coupled dissolution, phase transformation and partial re-immobilization. This framework cautions against directly extrapolating single-mineral behavior to heterogeneous AMD systems and provides a mechanistic basis for assessing Sb mobility and retention under DOM perturbation.

Bisphenol compounds (BPs), widely utilized in industrial production, have raised significant concerns within the scientific community due to their high environmental risks, which pose serious threats to human health and ecological security. Consequently, numerous researchers have dedicated efforts to developing advanced technologies to address BPs pollution. In this study, bibliometric analysis was employed to visually analyze 13,639 publications related to BPs removal from 1994 to 2023, aiming to elucidate the development status, research hotspots, and frontier trends in BPs removal technologies. The consistent upward trend in annual publication numbers underscores the ongoing expansion and deepening of research in this field, with the Chinese Academy of Sciences emerging as the most prominent contributing institution. Keywords burst analysis revealed that advanced oxidative degradation has become a predominant research focus among BPs removal technologies (removal efficiency ranging between 80 and 100). It is anticipated that future research on BPs removal will likely concentrate on developing more efficient and cleaner technologies, emphasizing sustainability and environmental friendliness. Overall, this study offers an objective and comprehensive overview of the research landscape in BPs removal technologies, providing a valuable reference and insightful suggestions for future researchers in the field.

Pyrolysis is a critical step in the thermal conversion of coal. A deep understanding of its mechanisms is essential for accurately predicting product yield and promoting clean, efficient coal conversion. However, the development of technologies for precise product yield prediction has been limited due to the heterogeneity of coal structures and the complexity of pyrolysis processes. Machine learning (ML), with its unique ability to handle complex, multidimensional and nonlinear systems, has attracted growing interest in coal pyrolysis research. This article provides a systematic review of the latest advances in applying ML models to coal and biomass pyrolysis, emphasising their significant potential for data-driven product yield prediction. While the 'black box' nature of ML models enables high-precision modelling, limitations exist in explaining the mechanisms of pyrolysis pathways. Therefore, exploring ML-driven methods to uncover pyrolysis mechanisms is crucial to bridge the gap between predictive modelling and understanding the scientific basis of coal conversion. To address core issues in the current coal pyrolysis field, such as fragmented, multi-source, heterogeneous data, and insufficient cross-scale correlation analysis, we propose constructing a high-throughput pyrolysis characterization platform and innovating data association mining techniques to establish a robust, multidimensional database. This would enable the development of practical ML models suitable for laboratory and industrial settings, reducing the experimental workload and the costs of industrial trial and error.

Stibnite (Sb2S3), the predominant antimony-bearing sulfide mineral, represents a major natural source of antimony (Sb) in mining-impacted environments. Although humic acid (HA) is ubiquitous in mine wastes and surface waters, its influence on the oxidative transformation and mobilization of Sb from Sb2S3 under photochemical conditions remains poorly understood. Here, the coupled effects of HA, controlled ultraviolet irradiation and pH on Sb2S3 weathering and Sb mobilization were systematically investigated through batch dissolution experiments combined with hydroxyl radical (·OH) determination, elemental sulfur (S0) analysis and complementary solid-phase characterization. Sb release increased with increasing pH and was further enhanced by HA, particularly under circumneutral and alkaline conditions. Controlled UV irradiation further increased Sb mobilization under the investigated conditions, with a more pronounced effect in HA-containing systems. The enhanced Sb mobilization was accompanied by increased ·OH production and greater S0 accumulation, indicating increased oxidative activity during weathering. SEM, EDS and FTIR analyses further revealed progressive surface morphological and compositional changes, whereas XRD showed that the bulk crystalline structure of Sb2S3 was largely preserved. XPS revealed the formation of oxidized Sb- and S-containing surface species, providing evidence for progressive surface chemical transformation. These results indicate that HA and controlled photochemical conditions were associated with enhanced Sb mobilization and oxidative transformation at the Sb2S3-solution interface, while the overall weathering remained predominantly surface-confined. The findings highlight the importance of considering natural organic matter, photochemical conditions and pH together when evaluating Sb mobility from sulfide minerals in mining-impacted environments.

Antimony (Sb) contamination in water poses significant environmental and health risks due to its high toxicity, persistence and complex redox behavior. Magnetic spinel ferrites (MFe2O4) have shown promise for Sb removal; however, the intrinsic influence of divalent metal species (M2+) in regulating Sb(III)/Sb(V) adsorption performance and interfacial mechanisms remains poorly understood. In this study, MnFe2O4, ZnFe2O4 and NiFe2O4 nanoparticles were synthesized and systematically evaluated to elucidate how M2+ governs Sb immobilization behavior. Batch adsorption experiments revealed pronounced M-dependent selectivity. MnFe2O4 exhibited the highest Sb(III) adsorption capacity (229.89 mg & centerdot;g-1), whereas NiFe2O4 showed superior affinity toward Sb(V) (up to 257.07 mg & centerdot;g-1). Adsorption kinetics for both Sb species followed pseudo-second-order models, indicating chemically controlled processes. Isotherm analyses indicated predominantly monolayer complexation for Sb(III), while Sb(V) adsorption displayed mixed adsorption characteristics, reflecting surface heterogeneity. Mechanistic investigations based on FTIR and XPS analyses suggest that Sb(III) immobilization is dominated by inner-sphere complexation with surface Fe-O/Fe-OH groups, whereas Sb(V) adsorption involves synergistic coordination with both Fe-O and M-O (Mn-O/Ni-O) functional groups. XPS analysis of Sb-loaded ZnFe2O4 revealed the coexistence of Sb(III) and Sb(V) species after Sb(III) adsorption, indicating surface-confined partial oxidation; the extent of solution-phase conversion was not independently quantified. Therefore, the redox process is interpreted as an interfacial phenomenon rather than bulk oxidation in solution. These results clarify that M2+ species influence Sb removal behavior by modulating the reactivity of surface functional groups and interfacial redox characteristics, rather than merely altering adsorption capacity. This work provides spectroscopic insight into M-dependent structure-activity relationships in spinel ferrites and offers a theoretical basis for the rational design of magnetic adsorbents for selective and efficient Sb remediation.

Porous carbon materials (PCMs) have emerged as key players in energy storage and environmental remediation thanks to their highly tunable pore structure parameters. However, traditional empirical approaches for optimizing these parameters are time-consuming and resource-intensive. Herein, a workflow is introduced that integrates machine learning-assisted pore parameters prediction with experimental validation for PCMs, thereby facilitating the identification of candidate PCMs for different application requirements. Coal-based activated carbon (CAC) is first employed to validate the effectiveness of this workflow, given its high tunability and extensive application potential. During the validation process, machine learning models are developed to establish a predictive map linking precursor and preparation parameters to the resulting specific surface area and total pore volume. The proposed strategy for CAC is applied to the design of a high-performance supercapacitor electrode (specific capacitance of 491.2 F g-1 at 0.1 A g-1) and a methylene blue adsorbent (adsorption capacity of 2196.8 mg g-1 at room temperature), demonstrating its effectiveness. Furthermore, the workflow is extended to coal tar pitch-based carbon materials, a more complex system, and demonstrates encouraging outcomes. This work extends the strategies for controlling pore structure parameters of CAC and provides a transferable workflow for exploring other PCMs.

Bisphenol S (BPS) has attracted much attention as an emerging hazardous contaminant due to its endocrine disruption and oncogenic effects. Although white-rot fungi have remarkable bioremediation capabilities for some bisphenols, little is known about their performance in BPS degradation. In this study, the newly discovered Phlebia acerina S-LWZ20190614-6 exhibited high capacity to degrade BPS. To further explore the mechanism of BPS degradation by P. acerina S-LWZ20190614-6, the whole-genome background and degradation pathways were investigated. Five low-toxicity metabolites were detected during the BPS biodegradation process, and a strong correlation was found between this biodegradation process and the interactions between BPS and ligninolytic enzymes. Moreover, transcriptomic analysis revealed that genes related to DNA replication and repair, ABC transporters, and fatty acid metabolism were involved in this BPS degradation process. Overall, this study provides insights into the achievement of BPS biodegradation by white-rot fungi.

The understanding of white-rot fungi (WRF) and their role in degrading recalcitrant environmental pollutants has significantly advanced due to developments in bioremediation research. Considerable progress has been made in elucidating the degradation capabilities of WRF against lots of environmental pollutants. In this review, research hotspots on the degradation of WRF were identified through bibliometric analysis. Key findings from systematic studies on the degradation of polycyclic aromatic hydrocarbons (PAHs) and bisphenols by WRF are synthesized and discussed. Furthermore, insights into the molecular and genetic basis underlying the enzymatic systems responsible for the degradation of PAHs and bisphenols are highlighted. Advancements and challenges in understanding the degradation capabilities and degradation mechanisms are examined in order to identify opportunities for developing more effective strategies to harness the bioremediation potential of WRF.

Anaerobic digestion methane production is an important chemical means of waste recycling. Although the process route has been mature, there are still some difficultie, such as complex construction process, many variables, and difficult to find the influence law of the process parameters. Because traditional anaerobic digestion modeling is complex, the production volume can be predicted just and the influence mechanism of raw material characteristics and process parameters of the product is not clear. Accurate prediction of methane production and optimization of reaction process parameters are essential for the understanding the reaction mechanisms and optimizing the process parameters of anaerobic digestion process. Using Machine learning can skip the tedious process and select key features directly to predict methane production. In this work, First, model ADM1 as a relatively accurate anaerobic digestion prediction model, it provides data set for machine learning, addreses data quality and data quantity in anaerobic digestion process. Then,different machine learning algorithms were used to predict methane production and optimize process parameters. Finally, the most suitable machine learning algorithm for predicting the anaerobic digestion process was found. Using LightGBM and BPNN both can achieve more than 98% accuracy in predicting methane production and optimizing process parameters,. shortening the reaction time step, more accurate results can be obtained for LightGBM and BPNN. This work is a successful application of machine learning to anaerobic digestion processes. Applying AI can solve the common problems of energy production process and provide new ideas for the development of smart energy and smart engineering.

The increasing reliance on lithium-ion batteries (LIBs) has raised significant concerns regarding the disposal of spent batteries, particularly regarding the recovery of critical metals such as nickel (Ni), cobalt (Co), and lithium (Li). This study presents a novel hydrometallurgical strategy integrating selective leaching and bio-based adsorption for the efficient recovery of Ni, Co, and Li from LiNiCoAlO2 (NCA) cathode material, which contains aluminum (Al) impurities that are challenging to separate. A reagent-optimized leaching process using a stoichiometric H2SO4-H2O2 system enabled the efficient extraction of 98.4 % Li, 99.5 % Co, 99.1 % Ni, and 91.5 % Al under mild conditions. Subsequently, a novel 3D macroporous xanthate-functionalized wood flour (WT) adsorbent derived from waste biomass. At pH 5.5, WT enabled highly selective adsorption of Ni and Co (both >99 %), while Al was removed via pH-controlled precipitation and Li remained in solution, allowing for complete downstream recovery. Furthermore, the adsorbed Co and Ni ions were easily desorbed using a weak acid, facilitating adsorbent regeneration. Lithium in the leachate was subsequently recovered as high-purity Li2CO3 (99.2 %) through Na2CO3 precipitation. Mechanistic insights were obtained through FTIR, SEM, XPS, and XRD. This environmentally friendly, bio-based approach offers a cost-effective and scalable strategy for critical metal recovery, minimizing reagent consumption and secondary waste generation, thereby contributing to sustainable battery recycling and resource conservation.

Flow-electrode capacitive deionization (FCDI) shows promise for desalination; however, conventional electrode materials often exhibit limited heavy metal ions adsorption capacity and low removal efficiency. This study investigates the use of watermelon rind-derived biochar, which is recognized for its strong heavy metal adsorption capability and favorable electrochemical properties, in an FCDI system for the concurrent removal of thallium (Tl+) and cadmium (Cd2+) ions. The results demonstrate enhanced FCDI performance under higher direct current voltages (up to 2.4 V) and prolonged reaction times (up to 11 d). Elevated initial metal concentrations (50 mg/L) increased the average removal rates to 1.60 g/(m2 & sdot;h) for Tl+ and 1.23 g/(m2 & sdot;h) for Cd2+, with maximum adsorption capacities reaching 597.4 mg/g for Tl+ and 177.0 mg/g for Cd2+. While Tl+ charge efficiency decreased at higher voltages, Cd2+ charge efficiency peaked at 0.8 V. The system maintained consistent and effective removal of both Tl+ and Cd2+ over ten consecutive reuse cycles. The removal mechanisms for Tl+ primarily involved electroadsorption, concentration gradient-driven diffusion, cation exchange, and surface complexation, whereas Cd2+ removal was further facilitated by chemical precipitation and cation-It interactions. Ion selectivity was influenced by system resistance, with higher resistance favoring the removal of lower-valence Tl+, whereas lower resistance enhancing the removal of higher-valence Cd2+. These findings provide valuable insights for optimizing Tl+ and Cd2+ removal from wastewater using biochar-enhanced FCDI systems.

Utilizing plant wastes to treat Pb(II)-polluted water bodies offers a sustainable solution, but concerns over adsorption ability and separation efficiency limit its application. This study investigates the preparation and application of three-dimensional macroporous network-structured modified wood flour (WTX and TZX) for efficient Pb(II) removal. The adsorbents were synthesized through xanthate modification of defatted (TZ) and non-defatted (WT) wood flour, followed by lyophilization to achieve a stable porous structure. The optimal preparation condition involved mixing 1.0 g of original wood flour with 2 mL of CS2 in a strong base environment at 25 degrees C for 3 h. Both WTX and TZX exhibited similar three-dimensional structure and good solid-liquid separation performance. Pb(II) removal rates reached 61 % for WTX and 54 % for TZX within 45 min. The maximum adsorption capacities were 221.73 mg/L for WTX and 210.53 mg/g for TZX, significantly higher than untreated wood flour. Despite similar appearances and maximum Pb(II) removal abilities, the defatting pretreatment did not enhance mechanical properties or adsorption performance. Pb(II) immobilization occurred via electrostatic attraction, complexation and precipitation, with functional groups like -O-C (=S)-SNa, -OH, -NH2 and -COOH playing key roles. An economic assessment highlighted the cost-effectiveness of the adsorbents, with an estimated treatment cost of 3.21 US$/ton of wastewater. The study underscores the potential of waste wood flour biomass as a sustainable, low-cost solution for heavy metal remediation.

Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are recognized as persistent emerging pollutants worldwide, and long-term exposure will seriously harm natural ecosystems and human health. However, as the largest producer and consumer of fluorochemicals, China has limited research on the environmental fate and influencing factors of PFOA and PFOS in surface waters. To address this gap, a meta-analysis was conducted using 34 articles related to PFAS pollution in China’s surface waters, published between 2000 and 2023, selected from the PubMed and Web of Science databases. Existing investigations indicate that the average concentrations of PFOA and PFOS in the surface water from industrial areas in southeast China are 1615.17 ng/L and 8.41 ng/L, respectively, with industrial wastewater being the primary pollution source. Meanwhile, the analysis revealed that PFOA and PFOS concentrations are positively correlated with surface water pH but negatively correlated with dissolved oxygen, total organic carbon of sediment, and salinity. Additionally, monitoring data show that PFOA/PFOS pollution levels in European countries have declined since 2015, which is attributed to restrictive measures on the usage of PFAS. In conclusion, this study provides a scientific basis for developing PFOA/PFOS pollution control and management strategies for surface water in China.

Imidaclothiz (IMZ), an innovative neonicotinoid insecticide, has attracted significant interest due to its environmental persistence and consequent ecological implications. In this research, the white-rot fungus Phanerochaete sordida YK-624 was used to degrade IMZ, unveiling a novel fungal degradation mechanism. The results demonstrated that IMZ was efficiently degraded by P. sordida YK-624. Transcriptomic analysis revealed that IMZ-induced stress triggered a cascade of enzymatic and cellular defense responses that are instrumental in facilitating its biodegradation. Through inhibitor experiments and enzyme activity profiling, cytochrome P450 and manganese peroxidase (MnP) were identified to play crucial roles in IMZ biodegradation. Additionally, three metabolites were isolated and identified by NMR, and two innovative degradation pathways involving hydroxylation and nitro reduction were proposed. Toxicity assessment suggested the reduced environmental risk of IMZ after its degradation by P. sordida YK-624. These findings provided insights into the IMZ degradation mechanism and highlighted the potential of white-rot fungi in neonicotinoid bioremediation.

Organic compounds and heavy metals constitute two major classes of aquatic contaminants. Their prolonged simultaneous presence facilitates complexation reactions, which can generate novel toxicants with enhanced biological hazards. Therefore, developing advanced remediation technologies for the concurrent elimination of these remains imperative. As a carbon-rich material, biochar is considered an environmentally friendly and cost-effective adsorbent. Over the past decade, modification of biochar has emerged as a hot research topic. Strategic architectural and physicochemical modifications enable tailored surface properties and enhanced adsorption mechanisms, substantially expanding potential applications across environmental remediation domains. Despite emerging literature on the simultaneous removal of heavy metals and organic pollutants through engineered biochar, most research still focuses on the removal of single pollutants. This review examines the simultaneous removal of heavy metals and organic contaminants using functionalized biochar. Firstly, remediation efficiency, mechanistic pathways, and practical applications of engineered biochar are investigated for complex pollution matrices in aqueous environments. Secondly, physicochemical processes governing simultaneous contaminant capture through surface-modified carbon architectures are elucidated. Thirdly, performance across diverse wastewater treatment scenarios are evaluated, and environmental deployment viability assessed. This comprehensive analysis not only advances scientific understanding but also facilitates technological implementation of engineered biochar for the simultaneous removal of heavy metals and organic pollutants from wastewater.

Heavy metal pollution, especially from Pb(II) and Cd(II), poses significant risks due to its persistence and bioaccumulation potential. Traditional removal methods face challenges like high costs and secondary pollution. This study developed a novel three-dimensional porous adsorbent XBS, derived from xanthate-modified Phanerochaete sordida YK-624 (a white-rot fungus), for the rapid and efficient removal of Pb(II) and Cd(II) from wastewater. Characterization showed that XBS has a sponge-like structure with abundant functional groups, significantly enhancing its adsorption capacity and kinetics. XBS achieved 96% Pb(II) and 32% Cd(II) removal within 1 min at a 0.25 g/L dose, reaching over 95% of the maximum adsorption capacity within 30 min for Pb(II) and 240 min for Cd(II). The maximum capacities were 224.72 mg/g for Pb(II) and 82.99 mg/g for Cd(II). Kinetic and thermodynamic analyses indicated a chemisorption-driven process, which was both endothermic and spontaneous. XBS exhibited high selectivity for Pb(II) over Cd(II) and other metals (Tl(I), Cu(II)), attributed to stronger covalent interactions with sulfur- and nitrogen-containing groups. Mechanistic analyses (XRD, FTIR, and XPS) revealed that removal occurs via ion exchange, complexation, and precipitation, forming stable compounds like PbS/CdS and PbCO3/CdCO3. Given its cost-effectiveness, scalability, and high efficiency, XBS represents a promising adsorbent for heavy metal remediation, particularly in Pb(II)-contaminated wastewater treatment applications.

In the context of the "Double First-Class" initiative,advancing the deep integration of industry,academia,research,and application in curriculum teaching is an effective strategy to enhance the quality of graduate education,thereby meeting the evolving demands for high-level talents in the new era. This paper explores the reform of curriculum teaching in the backdrop of this integrated educational approach,focusing on the environmental functional materials course. It addresses the challenges currently faced in the course's instruction and proposes reforms in various aspects such as the integrated teaching mechanism,content,modes,methods,as well as evaluation systems. The objective of this teaching reform is to enhance the pedagogical efficacy of the "environmental functional materials" course while simultaneously strengthening the cultivation of students' professional,scientific research,and practical abilities. This reform seeks to offer valuable insights for facilitating the effective alignment of comprehensive,high-quality talent training with social talent needs.