Micro/nanostructured MgO hollow spheres with selective adsorption performance and their application for fluoride monitoring in water

Bibliometric analysis and systematic review of fluoride-containing wastewater treatment: Development, hotspots and future perspectives

Water pollution with fluoride can cause dental fluorosis, skeletal deformities, and other diseases, posing serious harm to human health. To understand the development status, research hotspots, and frontier trends in fluoride-containing wastewater (FCW) treatment, this study employed bibliometric methods to visually analyze 2840 publications related to FCW treatment from the Web of Science Core Collection (WOSCC) database. The "bibliometrix" package in R language, VOSviewer, and CiteSpace visualization software were utilized for the analysis. The results revealed a fluctuating upward trend in the annual number of publications, indicating ongoing deepening and development of research in this field. India and China exhibited the strongest research capacity, forming a cooperation network centered around these two countries. High-impact journals such as Desalination and Water Treatment, Journal of Hazardous Materials, and Chemical Engineering Journal frequently publish research related to FCW treatment. Keyword co-occurrence and burst analysis revealed that the current research hotspots in FCW treatment primarily focus on treatment methods (ion exchange, chemical coagulation/precipitation, adsorption, electrochemical, membrane separation, and fluidized bed crystallization), adsorption mechanism, and adsorbent design and optimization. Future research will likely focus on developing efficient treatment technologies and adsorption materials for FCW, as well as the recovery of fluoride resources from FCW, highlighting a dual approach to environmental sustainability and resource management. By employing bibliometrics, this study outlines the development status of FCW treatment and predicts the field's future trends, providing insights for understanding the development trajectory of this field.

Enhanced removal of phosphate from aqueous solutions by oxygen vacancy-rich MgO microspheres: Performance and mechanism

The efficient removal of phosphate from water environments was extremely significant to control eutrophication of water bodies and prevent further deterioration of water quality. In this study, oxygen vacancy-rich magnesium oxide (OV-MgO) microspheres were synthesized by a simple solvothermal method coupling high-temperature calcination. The effects of adsorbent dosage, contact time, initial pH and coexisting components on phosphate adsorption performance were examined. The physicochemical properties of OV-MgO microspheres and the phosphate removal mechanisms were analyzed by various characterization techniques. The maximum adsorption capacity predicted by the Sips isotherm model was 379.7 mg P/g for OV-MgO microspheres. The phosphate adsorption in this study had a fast adsorption kinetics and a high selectivity. OV-MgO microspheres had a good acid resistance for phosphate adsorption, but their adsorption capacity decreased under alkaline conditions. The electrostatic attraction, ligand exchange, surface precipitation, inner-sphere surface complexation and oxygen vacancy capture were mainly responsible for efficient removal of phosphate from aqueous solutions. This study probably promoted the development of oxygen vacancy-rich metal (hydr)oxides with potential application prospects.

Surface engineering of multifunctional nanostructured adsorbents for enhanced wastewater treatment: A review

Rapid urbanization and industrialization have significantly contributed to the contamination of the environment through the discharge of wastewater containing various pollutants. The development of high-performance surface functional nanostructured adsorbents is of wide interest for researchers. Therefore, we explore the significant advancements in this field, focusing on the efficiency of nanostructured materials, as well as their nanocomposites, for wastewater treatment applications. The crucial role of surface modification in enhancing the affinity of these nanostructured adsorbents towards targeted pollutants, addressing a key bottleneck in the utilization of nanomaterials for wastewater treatment, was specifically emphasized. In addition to highlighting the advantages of surface engineering in enhancing the efficiency of nanostructured adsorbents, this review also provides a comprehensive overview of the limitations and challenges associated with surface-modified nanostructured adsorbents, including high cost, low stability, poor scalability, and potential nanotoxicity. Addressing these limitations is essential for realizing the commercial viability of these state-of-the-art materials for large-scale wastewater treatment applications. This review also thoroughly discusses the potential scalability and environmental safety aspects of surface-modified nanostructured adsorbents, offering insights into their future prospects for wastewater treatment. It is believed that this review will contribute significantly to the existing body of knowledge in the field and provide valuable information for researchers and practitioners working in the area of environmental remediation and nanomaterials.

Efficient fluoride removal using nano MgO: mechanisms and performance evaluation

In this study, highly efficient fluoride removal of nano MgO was successfully synthesized using a simple hydrothermal precipitation method. Hexadecyl trimethyl ammonium bromide (CTMAB) was utilized as a surfactant. Its long-chain structure tightly wrapped around the precursor crystal of basic magnesium chloride, inhibiting the growth of precursor crystals, reducing their size, and improving crystal dispersion. This process enhanced the adsorption capacity of nano MgO for fluoride. The adsorption performance of nano MgO on fluoride was investigated. The results indicate that pseudo-second-order kinetics and the Langmuir isotherm model can describe the adsorption behavior for fluoride, with a maximum adsorption capacity of 122.47 mg/g. Methods such as XRD, SEM, XPS, and FTIR were employed to study the adsorption mechanisms of the adsorbent. Additionally, factors potentially affecting adsorption performance in practical applications, such as pH and competing ions, were examined. This study enhances our profound understanding of the defluorination effectiveness and mechanisms of nano MgO.

The Constructing of the Oxide Phase Diagram for Fluoride Adsorption on La-Fe-Al: A Collaborative Study of Density Functional Calculation and Experimentation

In recent years, fluoride pollution in water is a problem that has attracted much attention from researchers. The removal of fluoride-containing wastewater by adsorption with metal oxide as an adsorbent is the most common treatment method. Based on this, the effect of the doping ratio of La2O3, Fe2O3, and Al2O3 on the fluoride-removal performance was discussed by constructing a phase diagram. In this study, the adsorption mechanism of nanocrystalline lanthanum oxide terpolymer was investigated by density functional theory calculation and experiment. The optimal pH condition selected in the experiment was three, and the adsorption kinetics of fluoride ions were more consistent with the quasi-second-order kinetic model. The adsorption thermodynamics was more consistent with the Langmuir model. When the La-Fe-Al ternary composite oxides achieved the optimal adsorption efficiency for fluoride ions, the mass synthesis ratio was Al2O3:(Fe2O3:La2O3 = 1:2) = 1:100, resulting in a fluoride ion removal rate of up to 99.78%. Density functional calculations revealed that the La-Fe-Al ternary composite oxides had three important adsorption sites for La, Fe, and Al. Among them, the adsorption capacity for HF was Fe2O3 > La2O3 > Al2O3, and for F- was La2O3 > Al2O3 > Fe2O3. This provided good guidance for designing adsorbents to remove fluoride.

The model and mechanism of adsorptive technologies for wastewater containing fluoride: A review

With the continuous development of society, industrialization, and human activities have been producing more and more pollutants. Fluoride discharge is one of the main causes of water pollution. This review summarizes various commonly used and effective fluoride removal technologies, including ion exchange technology, electrochemical technology, coagulation technology, membrane treatment, and adsorption technology, and points out the outstanding advantages of adsorption technology. Various commonly used fluoride removal techniques as well as typical adsorbent materials have been discussed in published papers, however, the relationship between different adsorbent materials and adsorption models has rarely been explored, therefore, this paper categorizes and summarizes the various models involved in static adsorption, dynamic adsorption, and electrosorption fluoride removal processes, such as pseudo-first-order and pseudo-second-order kinetic models, Langmuir and Freundlich isotherm models, Thomas and Clark dynamic adsorption models, including the mathematical equations of the corresponding models and the significance of the models are also comprehensively summarized. Furthermore, this comprehensive discussion delves into the fundamental adsorption mechanisms, quantification of maximum adsorption capacity, evaluation of resistance to anion interference, and assessment of adsorption regeneration performance exhibited by diverse adsorption materials. The selection of the best adsorption model not only predicts the adsorption performance of the adsorbent but also provides a better description and understanding of the details of each part of the adsorption process, which facilitates the adjustment of experimental conditions to optimize the adsorption process. This review may provide some guidance for the development of more cost-effective adsorbent materials and adsorption processes in the future.

Water Quality Prediction Based on Machine Learning and Comprehensive Weighting Methods

In the context of escalating global environmental concerns, the importance of preserving water resources and upholding ecological equilibrium has become increasingly apparent. As a result, the monitoring and prediction of water quality have emerged as vital tasks in achieving these objectives. However, ensuring the accuracy and dependability of water quality prediction has proven to be a challenging endeavor. To address this issue, this study proposes a comprehensive weight-based approach that combines entropy weighting with the Pearson correlation coefficient to select crucial features in water quality prediction. This approach effectively considers both feature correlation and information content, avoiding excessive reliance on a single criterion for feature selection. Through the utilization of this comprehensive approach, a comprehensive evaluation of the contribution and importance of the features was achieved, thereby minimizing subjective bias and uncertainty. By striking a balance among various factors, features with stronger correlation and greater information content can be selected, leading to improved accuracy and robustness in the feature-selection process. Furthermore, this study explored several machine learning models for water quality prediction, including Support Vector Machines (SVMs), Multilayer Perceptron (MLP), Random Forest (RF), XGBoost, and Long Short-Term Memory (LSTM). SVM exhibited commendable performance in predicting Dissolved Oxygen (DO), showcasing excellent generalization capabilities and high prediction accuracy. MLP demonstrated its strength in nonlinear modeling and performed well in predicting multiple water quality parameters. Conversely, the RF and XGBoost models exhibited relatively inferior performance in water quality prediction. In contrast, the LSTM model, a recurrent neural network specialized in processing time series data, demonstrated exceptional abilities in water quality prediction. It effectively captured the dynamic patterns present in time series data, offering stable and accurate predictions for various water quality parameters.

Aqueous Pb(II) Removal Using ZIF-60: Adsorption Studies, Response Surface Methodology and Machine Learning Predictions

Zeolitic imidazolate frameworks (ZIFs) are increasingly gaining attention in many application fields due to their outstanding porosity and thermal stability, among other exceptional characteristics. However, in the domain of water purification via adsorption, scientists have mainly focused on ZIF-8 and, to a lesser extent, ZIF-67. The performance of other ZIFs as water decontaminants is yet to be explored. Hence, this study applied ZIF-60 for the removal of lead from aqueous solutions; this is the first time ZIF-60 has been used in any water treatment adsorption study. The synthesized ZIF-60 was subjected to characterization using FTIR, XRD and TGA. A multivariate approach was used to investigate the effect of adsorption parameters on lead removal and the findings revealed that ZIF-60 dose and lead concentration are the most significant factors affecting the response (i.e., lead removal efficiency). Further, response surface methodology-based regression models were generated. To further explore the adsorption performance of ZIF-60 in removing lead from contaminated water samples, adsorption kinetics, isotherm and thermodynamic investigations were conducted. The findings revealed that the obtained data were well-fitted by the Avrami and pseudo-first-order kinetic models, suggesting that the process is complex. The maximum adsorption capacity (q_max) was predicted to be 1905 mg/g. Thermodynamic studies revealed an endothermic and spontaneous adsorption process. Finally, the experimental data were aggregated and used for machine learning predictions using several algorithms. The model generated by the random forest algorithm proved to be the most effective on the basis of its significant correlation coefficient and minimal root mean square error (RMSE).

Biosorption of Triphenyl Methane Dyes (Malachite Green and Crystal Violet) from Aqueous Media by Alfa (Stipa tenacissima L.) Leaf Powder

This study includes the characterization and exploitation of an abundant agricultural waste in Algeria, Alfa (Stipa tenacissima L.) leaf powder (ALP) as a biosorbent for the removal of hazardous triphenylmethane dyes, malachite green (basic green 4) and crystal violet (basic violet 3), from aqueous media under various operating conditions in batch mode. The effect of experimental parameters such as initial dye concentration (10-40 mg/L), contact time (0-300 min), biosorbent dose (2.5-5.5 g/L), initial pH (2-8), temperature (298-328 K), and ionic strength on dye sorption was investigated. The results of both dyes show that the increase in initial concentration, contact time, temperature, and initial pH of solution leads to an increase in biosorbed quantity, unlike the effect of ionic strength. The biosorption kinetics for triphenylmethane dyes on ALP was analyzed by pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models proposed by the Weber-Morris equation. Equilibrium sorption data were analyzed by six isotherms, namely the Langmuir, Freundlich, Harkins-Jura, Flory-Huggins, Elovich, and Kiselev isotherms. The thermodynamic parameters were evaluated for both dyes. The thermodynamic results suggest that both dyes' biosorption is a typical physical process, spontaneous and endothermic in nature.

Synthesis and Characterization of Porous MgO Nanosheet-Modified Activated Carbon Fiber Felt for Fluoride Adsorption

In the present work, the porous MgO nanosheet-modified activated carbon fiber felt (MgO@ACFF) was prepared for fluoride removal. The MgO@ACFF was characterized by XRD, SEM, TEM, EDS, TG, and BET. The fluoride adsorption performance of MgO@ACFF also has been investigated. The adsorption rate of the MgO@ACFF toward fluoride is fast; more than 90% of the fluoride ions can be adsorbed within 100 min, and the adsorption kinetics of MgO@ACFF can be fitted in a pseudo-second-order model. The adsorption isotherm of MgO@ACFF fitted well in the Freundlich model. Additionally, the fluoride adsorption capacity of MgO@ACFF is larger than 212.2 mg/g at neutral. In a wide pH range of 2-10, the MgO@ACFF can efficiently remove fluoride from water, which is meaningful for practical usage. The effect of co-existing anions on the fluoride removal efficiency of the MgO@ACFF also has been studied. Furthermore, the fluoride adsorption mechanism of the MgO@ACFF was studied by the FTIR and XPS, and the results reveal a hydroxyl and carbonate co-exchange mechanism. The column test of the MgO@ACFF also has been investigated; 505-bed volumes of 5 mg/L fluoride solution can be treated with effluent under 1.0 mg/L. It is believed that the MgO@ACFF is a potential candidate for a fluoride adsorbent.

Simultaneous Recovery of Nitrogen and Phosphorus from Sewage by Magnesium Ammonium Phosphate Method with Magnesium-Loaded Bentonite

Excessive nitrogen (N) and phosphorus (P) result in serious eutrophication of water. In this study, magnesium modified acid bentonite was prepared by the impregnation method, and nitrogen and phosphorus were simultaneously removed by the magnesium ammonium phosphate method (MAP), which solved the problem of the poor adsorption capacity of bentonite. The morphology and structure of MgO-SBt were characterized by XRD, FT-IR, SEM, EDS, XPS, BET, etc. The results show that the acidified bentonite can increase the distance between bentonite layers, the layer spacing is expanded to 1.560 nm, and the specific surface area is expanded to 95.433 m²/g. After Mg modification, the characteristic peaks of MgO appear at 2θ of 42.95°, 62.31°, and 78.72°, indicating that MgO has been successfully loaded and that MgO bonded to the surface and interior pores of the acidified bentonite, boosting adsorption performance. When the dosage of MgO-SBt is 0.25 g/L, pH = 9, and N/P ratio is 5:1, the maximum adsorption capacity of MgO-SBt for N and P can reach 193.448 mg/g and 322.581 mg/g. In addition, the mechanism of the simultaneous adsorption of nitrogen and phosphorus by MgO-SBt was deeply characterized by the kinetic model, isothermal adsorption model, and thermodynamic model. The results showed that the simultaneous adsorption of nitrogen and phosphorus by MgO-SBt was chemisorption and a spontaneous exothermic process.