Nickel and iron-based metal-organic frameworks for removal of organic and inorganic model contaminants

Comparative investigation on the adsorption behavior of bromate in aqueous solutions using Zn/Ni/Al-LDH and Ni/Al-LDH: optimization, equilibrium analysis, and mechanistic insights

The presence of bromate in water poses a significant health risk. In order to effectively eliminate bromate from water, this study synthesized a series of ternary Zn-Ni-Al layered double hydroxides with varying Zn/Ni/Al atomic ratios using a co-precipitation method. The adsorbents were characterized using various techniques including XRD, Fourier transform infrared spectroscopy, and N2 adsorption-desorption isotherms. Among them, ZnNiAl-2 exhibited the highest crystallinity and largest specific surface area (316.1 m2 g-1), which was compared to the binary hydrotalcite NiAl-LDH for its ability to adsorb bromate from water. Results demonstrated that the adsorption isotherm of bromate on ZnNiAl-2 followed the Langmuir model, with a maximum adsorption capacity of 120.5 mg g-1, significantly higher than that of NiAl at 75.5 mg g-1, indicating strong adsorption capability and reusability performance. The adsorption kinetics were also found to be in accordance with the pseudo-second-order kinetic model. The mechanism involved both surface adsorption and anion exchange.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40201-025-00932-6.

Applying hollow octahedron PtNPs/Pd-Cu2O nanozyme and highly conductive AuPtNPs/Ni-Co NCs to colorimetric -electrochemical dual-mode aptasensor for AFB1 detection

BACKGROUND

Aflatoxin B1 (AFB1) is a secondary metabolite produced by Aspergillus flavus and Aspergillus parasiticus. This toxin is highly carcinogenic and toxic, posing a serious threat to human and animal health. AFB1 primarily enters the human body through contaminated food, particularly peanuts, corn, nuts, and wheat. These foods are easily contaminated with AFB1 during planting, harvesting, storage, and processing. Therefore, the establishment of an accurate and sensitive method for the detection of AFB1 is essential to safeguard food safety and human health.

RESULTS

This study applied catalytic hairpin assembly (CHA), hybridization chain reaction (HCR), hollow octahedron PtNPs/Pd-Cu2O bifunctional nanozyme, and AuPtNPs/Ni-Co NCs to develop a colorimetric-electrochemical dual-mode aptasensor for AFB1 detection. Here, Pd-Cu2O corner-etched octahedra with cavities and oxygen vacancy defects were first designed, followed by the synthesis of PtNPs/Pd-Cu2O through the loading of PtNPs to enhance the peroxidase-like activity of Pd-Cu2O. PtNPs/Pd-Cu2O effectively catalyzed the generation of blue oxidation products from 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of hydrogen peroxide (H2O2). It also enhances the redox reaction of methylene blue (MB) at the electrode and improves the electrochemical signal. AuPtNPs/Ni-Co NCs possess a large specific surface area and excellent conductivity, enhanced the redox signal of MB. Additionally, the aptasensor combined the enzyme-free amplification strategies of CHA and HCR to improve sensitivity. The aptasensor reached limit of detection (LOD) 0.76 pg/mL in electrochemical mode and 0.49 pg/mL in colorimetric mode.

SIGNIFICANCE

The designed colorimetric-electrochemical dual-mode aptasensor exhibits high selectivity, specificity, stability, and reliability. The dual-mode aptasensor had been successfully applied to the spiked analysis of edible oils, peanuts, and cornmeal, demonstrating excellent recovery rates. Therefore, the dual-mode aptasensor had a wide application prospect in the field of quality supervision and food safety.

The response to shock loads of Ni-MOF and NiO NPs on aerobic granular sludge and algal-bacterial aerobic granular sludge

Currently, the increasing use of nickel metal-organic frameworks (Ni-MOF) and nickel oxide nanoparticles (NiO NPs) has raised concerns regarding their potential environmental impact on wastewater treatment systems. Herein, the responses of aerobic granular sludge (AGS) and algal-bacterial aerobic granular sludge (AB-AGS) to Ni-MOF and NiO NPs were investigated. The results showed that Ni-MOF concentrations of 50, 100, and 200 mg/L significantly reduced nutrient removal in both systems, particularly affecting ammonia, nitrite, and phosphorus removal, while denitrification processes remained stable. AB-AGS exhibited greater tolerance to nickel than AGS, likely due to its higher content of extracellular polymeric substances (EPSs), in which the algae were embedded, indicating a robust bacterial-algal symbiotic system. Conversely, NiO NPs had no adverse effects on bioreactor performance, likely due to their insolubility and integration into the sludge matrix. This research provides valuable insights into the potential future applications of AGS and AB-AGS technologies for treating wastewater contaminated with nickel and other heavy metals, highlighting the superior resilience of AB-AGS to nickel exposure.

Enhancing groundwater quality prediction through ensemble machine learning techniques

Groundwater quality is assessed by conducting water sampling and laboratory analysis. Field-based measurements are costly and time-consuming. This study introduces a machine learning (ML)-based framework and innovative application of stacking ensemble learning model, for predicting groundwater quality in an unconfined aquifer located in northern Iran. The groundwater quality index (GWQI) from 250 wells was evaluated and classified. We considered various influential factors such as proximity to residential areas, evaporation, aquifer transmissivity, precipitation values, population density, distance to industrial centers, distance to water resources, and topography. Three different ML classifiers were employed to establish relationships between GWQI and the aforementioned factors: the AdaBoost classifier (ADA), quadratic discriminant analysis (QDA), and stacking ensemble learning (SEL). A novel model was introduced dubbed quadratic-ada-stacking ensemble learning (QA-SEL) to predict GWQI. The performance of these algorithms was evaluated through the receiver-operating characteristic (ROC) and multiple statistical efficiency indicators, including overall accuracy, precision, recall, and the F-1 score. All three ML algorithms displayed a high degree of accuracy in their GWQI predictions. Nonetheless, the QA-SEL method was identified as the most effective model due to its superior accuracy (overall accuracy, precision, recall = 0.95, 0.95, 0.96, ROC = 0.96, respectively). Following model optimization and testing, the QA-SEL model and a GIS were employed to map GWQI classes across the entire area. The produced GWQI map was validated by comparing the measured and predicted GWQI on the map. This study offers an economically efficient model for groundwater quality prediction, which can be replicated in other plains.

Removal of fluoroquinolone antibiotic and sulfonated dye by functionalized Persea americana seed powder: Appraisal on phase transfer kinetics, equilibrium, economics, and applications in rural settings

The study focuses on reactive orange 16 (RO16), a sulfonated dye, and ciprofloxacin (CiP), a fluoroquinolone antibiotic treatment from aquatic surface by adsorption. The functionalized Persea americana seed powder (PASP) was developed by acid hydrolysis technique and investigated for RO16 and CiP removal in batch scale at different concentrations for CiP and RO16, pH (2-8), contact duration and temperature (303-318K). Utilizing a scanning electron microscope (SEM) with energy dispersive X-ray spectroscopy (EDAX), the generated native PASP were assessed for their morphological characteristics. Fourier transform infrared (FTIR) spectroscopy was applied to examine the performing characteristics of PASP. Experimental findings with four kinetic mathematical models allowed the estimation of the process involved in the biosorption. The most effective agreement was explained by the pseudo-second-order model and Sips isotherm (Cip = 34.603 mg/g and RO16 = 30.357 mg/g) at 303K temperature. For Cip Process economics of the biosorbent was done, and it was observed that it was less than the readily market-available activated carbon.

Zwitterionic MOF-embedded alginate beads with polydopamine surface functionalization for efficient doxycycline removal: Optimization and mechanistic study

The adsorptive removal of amphoteric antibiotics like doxycycline (DOX) is a difficult task because of the electrostatic repulsion between these amphoteric molecules and adsorbents. For this purpose, a zwitter adsorbent was fabricated by incorporating zwitter ZIF-67/MIL-88A binary MOF into the matrix of alginate (Alg); in addition, the surface of the beads was modified by polydopamine (PDA). The batch experiments implied the super-high adsorption efficacy of ZIF-67/MIL-88A@Alg@PDA toward DOX attained 384.61 ± 5.08 mg/g at a neutral pH medium, 25 °C, and using 0.02 g. The isotherm analysis implied the physisorption of DOX onto ZIF-67/MIL-88A@Alg@PDA, while the kinetic analysis denoted the chemisorption of DOX. The results of XPS, Zeta potential, and Lab experiments identified the types of physical and chemical interactions between ZIF-67/MIL-88A@Alg@PDA and DOX. The durability of the ZIF-67/MIL-88A@Alg@PDA beads was inspected by the recycling test, clarifying that the DOX adsorption aptitude declined by 12.22 mg/g. In addition, the measured leaching concentrations of cobalt and iron from the leaching test were 0.008 and 0.098 mg/L. The ionic strength of ZIF-67/MIL-88A@Alg@PDA, implying an enhancement in the DOX removal (%) from 83.51 to 93.50 % by raising the NaCl concentration from 0.2 to 1.0 mol/L. Therefore, our study could provide a simple procedure to overcome the electrostatic repulsion that retard the adsorption process of the amphoteric drugs onto charged adsorbents with positive or negative charges. Additionally, this procedure could also generate an electrostatic interaction between the zwitter adsorbents and the amphoteric drugs at specific pH media when they are in a zwitterionic nature.

Highly stable mesoporous Co/Ni mixed metal-organic framework [Co/Ni(μ3-tp)2(μ2-pyz)2] for Co (II) heavy metal ions (HMIs) remediation

A bimetallic cobalt/nickel-based metal-organic framework (MOF), [Co/Ni(μ3-tp)2(μ2-pyz)2], denoted as Co/Ni-MOF, has been successfully prepared by a hydrothermal method. The MOF was prepared by incorporating mixed O- and N- donor ligands, specifically terephthalic acid (tp) and pyrazine (pyz). The Mesoporous Co/Ni-MOF was comprehensively characterized using various analytical methods such as XRD, BET, FT-IR, TGA (23 % char yields), SEM, and EDS analyses. The synthesized mesoporous Co/Ni-MOF was then used to absorb Co (II) from aquatic areas efficiently. Several critical parameters, such as the beginning Co (II) concentration (25-150 mg/L), the effect of pH (2-10), the duration of time (5-30 min), and the amount of adsorbent (0.003-0.02 g), were systematically investigated. Remarkably, the Mesoporous Co/Ni MOF displayed a significant adsorption capacity of 372.66 mg g-1 in the optimum conditions, including pH = 6, amount of adsorbent = 0.003 g, duration of time = 25 min, and beginning Co (II) concentration = 150 mg/L. Adsorption data from the experimental studies of the mesoporous Co/Ni MOF are matched based on the non-linear pseudo-first-order (PSO) kinetic model (R2 = 0.9999), and a chemical process is suggested for chemisorption. Furthermore, the adsorption isotherms of Co (II) heavy metal ions (HMIs) are an excellent fit with the non-linear Temkin, indicating that they explain the sorbent/sorbate interactions concerning the heat of adsorption. It is evident from the thermodynamic parameters that adsorption is a spontaneous and favorable exothermic process. These results highlight the promising adsorption performance and potential applications of the mesoporous Co/Ni-MOF as an effective adsorbent for Co (II) elimination from aquatic areas. Four-cycle regeneration studies were the most effective for the Co (II) under study.

Amendment of Sargassum oligocystum bio-char with MnFe2O4 and lanthanum MOF obtained from PET waste for fluoride removal: A comparative study

The use of biomass and waste to produce adsorbent reduces the cost of water treatment. The bio-char of Sargassum oligocystum (BCSO) was modified with MnFe2O4 magnetic particles and La-metal organic framework (MOF) to generate an efficient adsorbent (BCSO/MnFe2O4@La-MOF) for fluoride ions (F-) removal from aqueous solutions. The performance of BCSO/MnFe2O4@La-MOF was compared with BCSO/MnFe2O4 and BCSO. The characteristics of the adsorbents were investigated using various techniques, which revealed that the magnetic composites were well-synthesized and exhibited superparamagnetic properties. The maximum adsorption efficiencies (BCSO: 97.84%, BCSO/MnFe2O4: 97.85%, and BCSO/MnFe2O4@La-MOF: 99.36%) were achieved under specific conditions of pH 4, F- concentration of 10 mg/L, and adsorbent dosage of 3, 1.5, and 1 g/L for BCSO, BCSO/MnFe2O4, and BCSO/MnFe2O4@La-MOF, respectively. The results demonstrated that the experimental data adheres to a pseudo-second-order kinetic model. The enthalpy, entropy, and Gibbs free energy were determined to be negative; thus, the F- adsorption was exothermic and spontaneous in the range of 25-50 °C. The equilibrium data of the process exhibited conformity with the Langmuir model. The maximum adsorption capacities of F- ions were determined as 10.267 mg/g for BCSO, 14.903 mg/g for the BCSO/MnFe2O4, and 31.948 mg/g for BCSO/MnFe2O4@La-MOF. The KF and AT values for the F- adsorption were obtained at 21.03 mg/g (L/mg)1/n and 100 × 10+9 L/g, indicating the pronounced affinity of the BCSO/MnFe2O4@La-MOF towards F- than other samples. The significant potential of the BCSO/MnFe2O4@La-MOF magnetic composite for F- removal from industrial wastewater, makes it suitable for repeated utilization in the adsorption process.

Adsorption of tetracycline from aqueous solution by ZIF-8: Isotherms, kinetics and thermodynamics

In this study, ZIF-8 nanoparticles were synthesized using a simple method at room temperature. The ZIF-8 nanoparticles were then characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), BET (Brunauer-Emmett-Teller) specific surface area, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA) and zeta potential. Subsequent batch adsorption experiments evaluated the adsorption performance of ZIF-8 on tetracycline, examining key pa-rameters like reaction time, pH, temperature, and adsorbent dosage. The results revealed a removal rate for TC of up to 90.59%. The adsorption data aligned with the Sips model, showcasing a maximum adsorption capacity of 359.61 mg/g at 303K. Further, the adsorption kinetics adhered to the pseudo-second-order kinetic model with an equilibrium adsorption capacity of 90 mg/g at 303K. The considerable specific surface area of ZIF-8, standing at 1674.169 m2/g, likely enhances the adsorption efficacy. Analysis using XRD and FTIR confirmed the adsorption of TC on the ma-terial's surface. Overall, the predominant driving forces behind the adsorption process were identified as electrostatic interactions and π-π stacking interactions.

Functional MOF-Based Materials for Environmental and Biomedical Applications: A Critical Review

Over the last ten years, there has been a growing interest in metal-organic frameworks (MOFs), which are a unique category of porous materials that combine organic and inorganic components. MOFs have garnered significant attention due to their highly favorable characteristics, such as environmentally friendly nature, enhanced surface area and pore volume, hierarchical arrangements, and adjustable properties, as well as their versatile applications in fields such as chemical engineering, materials science, and the environmental and biomedical sectors. This article centers on examining the advancements in using MOFs for environmental remediation purposes. Additionally, it discusses the latest developments in employing MOFs as potential tools for disease diagnosis and drug delivery across various ailments, including cancer, diabetes, neurological disorders, and ocular diseases. Firstly, a concise overview of MOF evolution and the synthetic techniques employed for creating MOFs are provided, presenting their advantages and limitations. Subsequently, the challenges, potential avenues, and perspectives for future advancements in the utilization of MOFs in the respective application domains are addressed. Lastly, a comprehensive comparison of the materials presently employed in these applications is conducted.

Potential Application of Innovative Aspergillus terreus/ Sodium Alginate Composite Beads as Eco-Friendly and Sustainable Adsorbents for Alizarin Red S Dye: Isotherms and Kinetics Models

Fungi were used as one of the most common bioremediation methods. From this perspective, our study highlights the optimization of Alizarin Red S (ARS) dye adsorption performance for the sodium alginate (SA) by using the fungus Aspergillus terreus (A. terreus) to form a composite bead and the possibility of its reusability. This was accomplished by mixing SA with different ratios of biomass powder of A. terreus, including 0%, 10%, 20%, 30%, and 40%, to form composite beads of A. terreus/SA-0%, A. terreus/SA-10%, A. terreus/SA-20%, A. terreus/SA-30%, and A. terreus/SA-40%, respectively. The ARS adsorption characteristics of these composite mixtures were analyzed at various mass ratios, temperatures, pH values, and initial concentrations. Moreover, sophisticated techniques, such as scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR), were employed to detect the morphological and chemical properties of this composite, respectively. The experimental results revealed that A. terreus/SA-20% composite beads have the highest adsorption capacity of 188 mg/g. Its optimum adsorption conditions were achieved at 45 ∘C and pH 3. Moreover, the ARS adsorption was well explained by the Langmuir isotherm (q_m = 192.30 mg/g) and pseudo-second-order and intra-particle diffusion kinetics. The SEM and FTIR findings corroborated the superior uptake of A. terreus/SA-20% composite beads. Lastly, the A. terreus/SA-20% composite beads can be employed as an eco-friendly and sustainable alternative to other common adsorbents for ARS.

Evaluation of machine learning algorithms for groundwater quality modeling

Groundwater quality is typically measured through water sampling and lab analysis. The field-based measurements are costly and time-consuming when applied over a large domain. In this study, we developed a machine learning-based framework to map groundwater quality in an unconfined aquifer in the north of Iran. Groundwater samples were provided from 248 monitoring wells across the region. The groundwater quality index (GWQI) in each well was measured and classified into four classes: very poor, poor, good, and excellent, according to their cut-off values. Factors affecting groundwater quality, including distance to industrial centers, distance to residential areas, population density, aquifer transmissivity, precipitation, evaporation, geology, and elevation, were identified and prepared in the GIS environment. Six machine learning classifiers, including extreme gradient boosting (XGB), random forest (RF), support vector machine (SVM), artificial neural networks (ANN), k-nearest neighbor (KNN), and Gaussian classifier model (GCM), were used to establish relationships between GWQI and its controlling factors. The algorithms were evaluated using the receiver operating characteristic curve (ROC) and statistical efficiencies (overall accuracy, precision, recall, and F-1 score). Accuracy assessment showed that ML algorithms provided high accuracy in predicting groundwater quality. However, RF was selected as the optimum model given its higher accuracy (overall accuracy, precision, and recall = 0.92; ROC = 0.95). The trained RF model was used to map GWQI classes across the entire region. Results showed that the poor GWQI class is dominant in the study area (covering 66% of the study area), followed by good (19% of the area), very poor (14% of the area), and excellent (< 1% of the area) classes. An area of very poor GWQI was observed in the north. Feature analysis indicated that the distance to industrial locations is the main factor affecting groundwater quality in the region. The study provides a cost-effective methodology in groundwater quality modeling that can be duplicated in other regions with similar hydrological and geological settings.

Porous adsorbent derived from acid activation of food waste biochar: A sustainable approach for novel removal chlorophenol in wastewater

In this study, porous biochar (PBC) was prepared by acid activation of biochar derived from food waste (FWBC) and used as a suitable approach for the removal of 4-chlorophenol (CP) in wastewater. The characterization of PBC and the influent of different experimental conditions are determined. After the acid activation process, the surface area, porosity, and functional groups of PBC were developed. The removal performances of CP (1 mg/L) by PBC and FWBC were archived at 97.8 and 82.1%, respectively. Adsorption kinetics and isotherms of CP were followed by the second-order and Langmuir models, respectively. The maximum capacities of CP uptake onto mono-layer of FWBC and PBC based on the Langmuir model were determined at 79.8 and 108.7 mg/g, respectively. Besides, PBC could remove more than 89% CP from wastewater within 45 min of reaction time and it is suitable to reuse 8 times with over 60% adsorption efficiency of CP. In addition, the adsorption mechanism and environmental impact were discussed in detail. This work could bring a sustainable approach to the treatment of CP in wastewater as well as the management of food waste in Vietnam.

Metal(loid)s removal by zeolite-supported iron particles from mine contaminated groundwater: Performance and mechanistic insights

Iron-based materials have been widely investigated because of their high surface reactivity, which has shown potential for the remediation of metal(loid)s in groundwater. However, the disadvantages of structural stability and economic feasibility always limit their application in permeable reactive barrier (PRB) technology. In this study, zeolite-supported iron particles (Zeo-Fe) were synthesized by an innovative low-cost physical preparation method that is suitable for mass production. The removal efficiency and mechanism of typical metal(loid)s (Pb²⁺, Cd²⁺, Cr⁶⁺ and As³⁺) were subsequently investigated using various kinetic and equilibrium models and characterization methods. The results of scanning electron microscopy and energy dispersive spectrometry (SEM-EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) confirmed that zero valent iron (Fe⁰) and oxidation product (Fe₃O₄) were successfully loaded and efficiently dispersed on zeolite. The synthesized Zeo-Fe exhibited excellent adsorption and redox capacities for the cations Pb²⁺, Cd²⁺ and anions Cr⁶⁺, As³⁺. The increase in the pH resulting from Fe⁰ corrosion also enhanced the precipitation of Fe-metal(loid)s. The maximum removal capacity for Pb²⁺, Cd²⁺, Cr⁶⁺ and As³⁺ was up to 70.00, 9.12, 2.35 and 0.36 mg/g, respectively. The removal processes were well described by the pseudo-second-order kinetic model for Pb²⁺ and Cd²⁺, Lagergren pseudo first-order kinetics model for As³⁺ and double phase first order kinetics model l for Cr⁶⁺. Cr⁶⁺ was rapidly reduced to Cr³⁺ by the Fe⁰ stabilized on Zeo-Fe, and the oxidation of As³⁺ to As⁵⁺ was attributed to the Fe^0/Fe²⁺ oxidation process at the interface over time, which was further demonstrated by the mineral phase and element valence analyses of reacted Zeo-Fe. The removal mechanism for metal(loid)s was a combination of physical and chemical processes, including adsorption, co-precipitation and reduction-oxidation. Conclusively, Zeo-Fe has been shown to have potential as an effective and economical material for removing various metal(loid)s used in PRB.