Adsorption Model Research Articles

Unveiling the Potential of Room-Temperature Synthesis of a Mixed-Linker Zeolitic Imidazolate Framework-76 for CO2 Capture

A room-temperature synthesis was used to prepare ZIF-76 by combining the organic linker imidazole and 5-chlorobenzimidazole, with the addition of NaOH as a modulator. The synthesis process was optimized by modifying the existing method, which includes the introduction of heating, different types of solvent, and adjustment to the reactant ratio. The synthesized MOFs were characterized to evaluate their crystallinity, textural properties and surface morphology. The result demonstrated that the introduction of heat led to the formation of ZnO whereas the replacement of DEF–DMF with methanol resulted in the production of amorphous material. Moreover, a change in precursor ratio led to the production of ZIF-76 with a low yield and surface area. Meanwhile, CO2 adsorption was performed in a pressure range of 0–1.2 bar at 298.15 K. Notably, ZIF-76B with a low surface area exhibited a greater CO2 uptake capacity of 1.43 mmol/g compared to ZIF-76A, which recorded 1.29 mmol/g. Furthermore, the isotherm and kinetic models were applied to fit the experimental CO2 adsorption data. The analysis of the adsorption models indicated that the CO2 adsorption was primarily governed by a monolayer formation on a homogeneous surface. Nevertheless, there was a slight diversion in terms of predicted qm with experimental data, which could be attributed to the adsorption not yet reaching equilibrium. Additionally, the kinetic model was applied to the initial stage of adsorption in the pressure range of 0–0.24 bar. The Elovich model was found to fit better with the CO2 uptake capacity data of ZIF-76A and ZIF-76B suggesting that the adsorption process may involve multiple mechanisms.

An exploration of RSM, ANN, and ANFIS models for methylene blue dye adsorption using Oryza sativa straw biomass: a comparative approach

This study focused on simulating the adsorption-based separation of Methylene Blue (MB) dye utilising Oryza sativa straw biomass (OSSB). Three distinct modelling approaches were employed: artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and response surface methodology (RSM). To evaluate the adsorbent’s potential, assessments were conducted using Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The evaluation of RSM, ANN, and ANFIS included the quantification of R2, mean squared error (MSE), root mean square error (RMSE), and mean absolute error (MAE) metrics. The regression coefficients from the process modelling demonstrated that RSM (R2 = 0.9216), ANN (R2 = 0.8864), and ANFIS (R2 = 0.9589) all accurately predicted MB adsorptive removal. However, comparative statistical analysis revealed that the ANFIS model exhibited superior accuracy in data-based predictions compared to ANN and RSM models. The ideal pH for MB adsorption utilizing OSSB was established as 7. Additionally, favourable outcomes were obtained with 60-minute contact durations, 20 mg adsorbent quantities, and temperatures of 30 °C. The pseudo 2nd -order kinetic model for MB adsorption by OSSB was confirmed. The equilibrium data exhibited a superior fit with the Langmuir isotherm model in comparison to the Freundlich model. The thermodynamic adsorption parameters, including (∆G = -9.1489 kJ/mol), enthalpy change (∆H = -1457.2 kJ/mol), and entropy change (∆S = -19.03 J mol−1 K−1) indicated that the adsorption of MB onto the OSSB surface is exothermic and spontaneous under the experimental conditions. This research effectively showcased the potential of RSM, ANN, and ANFIS in simulating dye removal using OSSB. The generated parameter data proved valuable for the design and control of the adsorption process.

Purification of Biodiesel Polluted by Copper Using an Activated Carbon Prepared from Spent Coffee Grounds: Adsorption Property Tailoring, Batch and Packed-Bed Studies

Biodiesel produced via oil transesterification often contains metallic impurities, such as copper, which affects its quality and engine performance. This study explores the use of activated carbon prepared from spent coffee grounds to remove copper from biodiesel. Activated carbon samples were prepared via biomass pyrolysis and chemical activation with KOH and HNO3. The optimal conditions for copper adsorption were determined using a Taguchi L9 design. Maximum adsorption capacities were 13.4 and 17.3 mg/g at 30 and 40 °C, respectively, in batch adsorbers. In packed-bed columns, the axial dispersion reduced the adsorption efficiency obtaining bed adsorption capacities from 1.9 to 5.1 mg/g under tested experimental conditions. Adsorbent characterization and adsorption modeling indicated that copper removal was driven by multi-cationic interactions, where carboxylic groups from carbon surface acted as key active sites. The new adsorbent outperformed commercial bone char, making it a cost-effective alternative to improve biodiesel production contributing to the energy matrix diversification.

Introducing the Adsorption Energy Distribution Calculation for Two-Component Competitive Adsorption Isotherm Data.

This work introduces the Adsorption Energy Distribution (AED) calculation using competitive adsorption isotherm data, enabling investigation of the simultaneous AED of two components for the first time. The AED provides crucial insights by visualizing competitive adsorption processes, offering an alternative adsorption isotherm model without prior assuming adsorption heterogeneity, and assisting in model selection for more accurate retention mechanistic modeling. The competitive AED enhances our understanding of multicomponent interactions on stationary phases, which is crucial for understanding how analytes compete on the stationary phase surface and for selecting adsorption models for numerical optimization of preparative chromatography. Here, the two-component AED was tested on both synthetic and experimental data, and a very successful outcome was achieved.

Lithium Recovery from Reverse Osmosis Concentrate of Geothermal Water by Spinel Type λ-MnO2 -Batch Tests

ABSTRACT Powder and granulated forms of lithium selective spinel type manganese oxide adsorbents (λ-MnO2) were evaluated for adsorption of lithium from the reverse osmosis (RO) concentrate of geothermal water. The interaction between lithium ions and λ-MnO2 adsorbents, in terms of adsorption capacity and uptake rate, was investigated by equilibrium and kinetic studies. In terms of adsorption equilibria, Langmuir isotherm adsorption model accurately represented the adsorption of lithium ions by powder and granulated λ-MnO2 adsorbents from the RO concentrate of the geothermal water. The best description of lithium uptake onto powdered and granulated adsorbents was provided by the pseudo-second-order kinetic model. Additionally, research was carried out with an objective of removing the inhibitory impacts of boron and arsenic on separation of lithium. The λ-MnO2 adsorbent showed no affinity for boron uptake from the solution. However, it exhibited some increasing uptake to arsenic with an increase in amount of the λ-MnO2 adsorbent. But it is possible to eliminate arsenic by means of arsenic selective ion exchange resins Lewatit FO36 and ArsenXnp prior to separation of lithium from the RO concentrate of geothermal water.

Electrospinning Membrane with Polyacrylate Mixed Beta-Cyclodextrin: An Efficient Adsorbent for Cationic Dyes.

A simple and non-chemical binding nanofiber (β-CD/PA) adsorbent was obtained by electrospinning a mixture of β-cyclodextrin (β-CD) and polyacrylate (PA). The cationic dyes in wastewater were removed by the host-guest inclusion complex of the β-cyclodextrin and the electrostatic interaction between the polyacrylate and the dyes groups. The influence of the content of β-cyclodextrin on the surface morphology and adsorption capacity of the nanofiber membrane was discussed, and the optimized adsorption capacity of nanofiber adsorption material was determined. The adsorption capacity of nanofiber adsorbents for basic red 9, basic red 14, basic red 46, basic blue 9, basic yellow 19 and basic yellow 28 was 86.71 mg/g, 21.513 mg/g, 18.926 mg/g, 44.525 mg/g, 116.516 mg/g and 155.206 mg/g, respectively. The effects of different initial concentrations and pH values on the adsorption properties of adsorbent materials were studied. The kinetic analysis showed that the adsorption process of nanofibers for cationic dyes was more in line with the pseudo-second-order kinetic adsorption model. Moreover, nanofiber adsorbent could be easily separated from the dye solution and showed high recycling efficiency. These results indicated that the β-cyclodextrin/polyacrylate composite nanofibers are expected to be recyclable adsorbents in dye wastewater treatment.

Monte Carlo Simulation of Aromatic Molecule Adsorption on Multi-Walled Carbon Nanotube Surfaces Using Coefficient of Conformism of a Correlative Prediction (CCCP)

Using the Monte Carlo technique via CORAL-2024 software, models of aromatic substance adsorption on multi-walled nanotubes were constructed. Possible mechanistic interpretations of such models and the corresponding applicability domains were investigated. In constructing the models, criteria of the predictive potential such as the iIndex of Ideality of Correlation (IIC), the Correlation Intensity Index (CII), and the Coefficient of Conformism of a Correlative Prediction (CCCP) were used. It was assumed that the CCCP could serve as a tool for increasing the predictive potential of adsorption models of organic substances on the surface of nanotubes. The developed models provided good predictive potential. The perspectives on the improvement of the nano-QSPR/QSAR were discussed.

Carboxymethyl cellulose sodium/bentonite composite adsorbent for Cd(II) adsorption from wastewater

Severely polluting wastewater containing heavy metal ions has become a pressing issue. To address the current shortcomings of natural bentonite (Bent) and carboxymethyl cellulose sodium (CMC) for Cd(II) adsorption, this study developed a cellulose/bentonite composite adsorbent (CMCMW-Bent) via microwave-assisted synthesis using acrylic acid (AA)-modified CMC and pretreated bentonite (Bent), and the adsorbent was used to remove Cd(II) from wastewater. The results show that the strong interaction between AA and CMC, which successfully entered the bentonite layer, and the bentonite provided excellent structural stability and abundant adsorption sites for the adsorption process. Meanwhile, microwave-assisted heating enhanced this unique structure compared to traditional heating with the aqueous solution. The best adsorption effect occurred at pH = 6–7, with a maximum adsorption capacity of 44.76 mg/g for Cd(II). The isothermal adsorption and kinetic models demonstrate that the adsorption process followed the Langmuir adsorption fitting and pseudo-second-order kinetic equations. The thermodynamic study confirms that the adsorption process was a spontaneous endothermic process and a chemical adsorption process. This study provides a new approach for obtaining efficient adsorbents.

Experimental investigation of pyridine removal using vulcanized oil shale

The study systematically conducted orthogonal and univariate experiments to determine the optimal parameters for pyridine removal using vulcanized oil shale. The findings revealed that the key determinants of pyridine adsorption onto vulcanized oil shale included the pH level of the pyridine solution, contact time, initial pyridine concentration, and the quantity of vulcanized oil shale introduced into the system. Under optimal adsorption conditions, the vulcanized oil shale achieved a 48.00% adsorption efficiency and an equilibrium adsorption capacity of 4.83 mg·g−1. In contrast, the untreated oil shale exhibited a comparatively reduced adsorption efficiency of 22.88% under its respective optimal conditions. The research further examined the adsorption kinetics and isothermal adsorption models for both types of oil shale. The kinetic data indicated that pyridine adsorption followed a pseudo-second-order model. The pyridine adsorption isotherms for both oil shale and vulcanized oil shale were best described by the Freundlich model, compared to the Langmuir model. These findings provide significant insights into the utilization of vulcanized oil shale for the efficient treatment of low-concentration pyridine wastewater, potentially contributing to environmental remediation and pollution control strategies.

Study on stabilization of mercury in wastewater and soil by modified coal-based humic acid residue.

Coal-based humic acid residue (HAS), as a waste generated during humic acid production, has been gaining attention in recent years due to its adsorption capacity and containing nutrients. In this study, to improve the adsorption capacity of HAS for and Hg, phosphate-modified materials (N-HAS) were prepared by a hydrothermal method and HAS and N-HAS were characterized by scanning electron microscopy (SEM), Fourier transforms infrared spectroscopy (FTIR), X-ray fluorescence (XRF); batch adsorption experiments investigated the adsorption capacity of N-HAS on Hg2+ under different pH, and isothermal adsorption model and kinetic model fitted the adsorption process to explore the adsorption mechanism; the effects of various amounts of N-HAS on the Hg content in maize and the effective Hg in the soil under Hg-contaminated soil were investigated by field trial. The results showed that the pseudo-second-order kinetic model (R2=0.9641) and Langmuir isothermal (R2=0.95) adsorption model could better describe the adsorption behavior of N-HAR on Hg2+, the maximum adsorption amount was 124.20 mg/g, and the time to reach adsorption equilibrium was shorter for N-HAS compared to HAS; after 5 times of adsorption-desorption, the removal rate of Hg2+ by N-HAS was still higher than 80%, with stable cyclic adsorption performance; the adsorption mechanism of Hg2+ by N-HAS included physical adsorption, precipitation, and surface complexation, and compared with HAS, the percentage of complexation for Hg2+ adsorption by N-HAS increased by 77.81%, and the percentage of precipitation increased by 7.68%; compared to the control group, it was shown that the addition of N-HAS significantly decreased (p < 0.05) the Hg content of maize kernels by 27.44% ∼ 72.09%, increased biomass by 4.34% ∼ 11.26%, and decreased the available Hg content in soil by 50.00% ∼ 82.80%. In addition, the addition of N-HAS at 0.4 kg/m2 was optimal for the field trial. The study showed that N-HAS not only achieved resource utilization but also demonstrated great potential for treating Hg2+ in water and soil.

CO2 capture in pilot-scale unit using solid adsorbent in biomass fluidised bed boiler flue gas

The search for methods to capture carbon dioxide (CO2) emissions from solid fuel combustion processes has led to the development and subsequent testing of alternative innovative CO2 capture technologies. Vacuum Pressure Swing Adsorption (VPSA) method is a promising technology for efficient CO2 capture using solid sorbents. This article introduces CO2 capture using the VPSA technology, providing description of the selected VPSA method and the construction of a pilot-scale unit for VPSA CO2 capture. The main goal of this article is to present experimental results, including a description of the pilot-scale unit used for the VPSA adsorption tests using zeolite 13X, an industrially proven sorbent for CO2 capture. The measured adsorption values were compared with theoretical isotherms, allowing the assessment of VPSA method efficiency and accuracy in practical conditions. Results indicated discrepancies between the experimental unit and the theoretical adsorption models, attributed to non-ideal conditions, non-optimised processes, incomplete drying of the sorbent, and temperature variations affecting the adsorption efficiency. The conclusion confirms the VPSA lab unit’s ability to adsorb CO2 using solid sorbents, suggesting that further research and additional tests with new alternative sorbents is needed.

Methane Adsorption in Heterogeneous Potential Wells of Coal: Characterization Model and Applications.

In terms of the phenomenon of nonuniformity adsorption energy between methane and a natural heterogeneous coal surface, a heterogeneous potential well model is established in this study based on adsorption science and molecular dynamics theories. This model describes the methane adsorption positions in coal pores as a three-dimensional space composed of adsorption equipotential surfaces with varying depths of potential well, which emphasizes the heterogeneous distribution of methane adsorption potential well depths in coal and accurately describes the spatial distribution and energy states of methane molecules during methane adsorption and desorption in naturally heterogeneous coal. By taking the residual sum of squares (RSS) and Pearson correlation coefficient as indicators, the fitting accuracies of the Langmuir model and the heterogeneous potential well model for isothermal adsorption and desorption curves are compared so that the superiority of the heterogeneous potential well model in describing the adsorption and desorption of methane in natural coal is confirmed. According to this new model, a method to calculate the potential well distribution of coal by using isotherm adsorption and desorption curves was proposed. Taking the number of potential wells, the average potential well depth, and the variance of potential well depth as statistical indicators, the potential well distribution characteristics of coal in different ranks in the processes of methane adsorption and desorption under different temperatures were analyzed. In addition, the effects of temperature increase on the changes of the occupation rate of potential wells and methane desorption amount of coal with different potential well depth distributions are studied, which confirmed the necessity of evaluating the thermal recovery rate of coalbed methane based on the potential well depth distribution of coal seams.

Mathematical modelling of flow and adsorption in a gas chromatograph

Mathematical modelling of flow and adsorption in a gas chromatograph

Predictive modeling of microplastic adsorption in aquatic environments using advanced machine learning models.

This study addresses the critical environmental concerns surrounding microplastics, aiming to elucidate the intricate factors influencing their behavior and interactions with organic pollutants. Utilizing advanced artificial neural network modeling techniques, including GRU, LSTM, RNN, and CNN, a comprehensive analysis of microplastic sorption capacity and underlying mechanisms is conducted. The research relies on a meticulously curated dataset encompassing fundamental parameters such as organic compound composition, n-octanol/water partition coefficient, covalent acidity, covalent basicity, molecular polarizability to volume ratio, and the logarithm of the partition coefficient. Findings underscore the significance of understanding the n-octanol/water distribution coefficient (Log D) in predicting organic pollutant fate in aquatic environments, with compounds displaying higher Log D values exhibiting heightened affinity for microplastics, posing substantial ecological and human health risks. Additionally, the study highlights the importance of selecting appropriate models to accurately capture complex sorption processes, especially in varied aquatic environments. Furthermore, the profound impact of acidity, molecular polarizability to volume ratio, and covalent basicity on microplastic behavior is elucidated. Notably, machine learning models and CNNs demonstrate remarkable speed in prediction generation. A comparative analysis of four robust machine learning models establishes fundamental alignment between model predictions and empirical findings. Particularly noteworthy is the RNN model, emerging as the most accurate with an impressive accuracy of 0.967 and a minimum absolute error of 0.38. These results underscore the efficacy of the RNN model in predicting microplastic dynamics, holding promise for significant contributions to addressing microplastic pollution.

Adsorption properties and competitive adsorption mechanism exhibited by carbon-nanotube-modified biochar for removal of crude oil and Ni(II) pollutants from water.

Carbon-nanotube-modified biochar (CNT3-CBC) with a nanostructured surface was prepared by using cattle manure as the raw material via the impregnation method. This modified biochar was then used to adsorb petroleum and Ni(II) from aqueous solutions. Various physicochemical characterization techniques were employed, including SEM, BET analysis, FTIR, and XPS. Kinetic and isothermal adsorption characteristics were analyzed. The influence of different biochar dosages, solution pH levels, and number of adsorption cycles on the efficiency of removal of crude oil and Ni(II) was meticulously evaluated. Results indicated that modified biochar had a higher surface area, a greater number of surface functional groups, and higher interaction forces compared to biochar. Adsorption kinetics and isotherms showed that modified biochar had a strong adsorption capacity. The experimental data conformed closely to the Elovich, Langmuir, and Freundlich adsorption models, underscoring the significant contributions of both physical and chemical adsorption mechanisms. Competitive adsorption of modified biochar in the co-sorption of petroleum and nickel solutions exists, and the modified biochar demonstrated high capacities for crude oil and Ni(II) in the competitive adsorption. The modified biochar prepared at a pyrolysis temperature of 800°C exhibited a superior adsorption performance, and the adsorption capacities of crude oil and Ni(II) were 303.03 mg·g-1 and 32.87 mg·g-¹ , respectively. Modified biochar has better regeneration potential after crude oil and Ni(II) adsorption, with the removal efficiency remaining above 50 % in the fourth cycle. As an efficient and environmentally friendly adsorbent, modified biochar shows great potential for removing crude oil and Ni(II) pollutants from water.

Revisiting the persulfate activation performance of seaweed derivied biochars: The composition and origin of pollutant degradation activity

A steady increase in seaweed production necessitates effective strategies to manage its post-production waste and its assosicated CO2 emission. Biochar formation stand out as a promising option, offering significant advantage for persulfate-activated water remediation processes. Herein, we investigated and compared the performance of two seaweed-derived biochars, focusing on their physical characteristics, heteroatoms, and chemical composition in activating persulfate (PS). Although, both seaweeds (Capsosiphon fulvescens (CF) and Undaria pinnatifida (SW)) that studied are edible, they exhibit unique catalytic behavior in the degradation of simazine (SMZ). The differences in simazine degradation activity observed in these biochars were primarily attributed to the description of metal active sites rather than the complex composition and specific surface area of the biochars. The identification of these active sites was achieved through various physical characterization tools (XRD, XPS, BET) and by examining the adsorption models and degradation patterns of simazine under different conditions. Our results demonstrate that the biochar derived from CF (100% removal) seaweed having metal active centres is more catalytic than SW (58.4% removal) derived biochar. ROS quantification and electrochemical studies suggest that simazine degradation occurs through different mechanisms in these biochars. Therefore, the CF-derived biochar catalytic system was optimized for simazine oxidation, with studies focusing on its degradation pathway, intermediate toxicity, and catalytic stability. This comprehensive study outlines the significance of selection of seaweed biomass for optimal activity in the persulfate-based oxidative system.

Poly(acrylic acid) and Poly(acrylic acid-b-acrylamide) via RAFT: Effect of Composition on Ni2+ Binding Capacity

Two poly(acrylic acid-b-acrylamide) copolymers, and a poly(acrylic acid) homopolymer were synthesized via reversible addition-fragmentation chain transfer (RAFT) polymerization and tested for nickel removal from aqueous media. RAFT was used for better interchain composition homogeneity and to facilitate the synthesis of the block copolymers. Liquid-phase polymer-based retention (LPR) was used to compare the nickel binding capacity. Uptake tests were carried out at pH 3.0, 4.0, and 5.0. Nickel adsorption isotherms in the range of 1 to 7 mmol L-1 were achieved and the Langmuir adsorption model was applied. Maximum binding capacity (Qm) of Ni2+ at 298 K depended on the composition of the copolymers and pH. The polyacid block (PAA) was the major structural feature responsible for high values of nickel binding. All materials presented better uptake at higher pH, probably due to polyacid deprotonation and the increase in the electrostatic interactions. Up to approximately 100 mg of nickel per gram of homopolymer could be retained at pH = 5.0. Even though the presence of a poly(acrylamide) block decreases the binding capacity compared to PAA, that block has a specific contribution to nickel binding and can also provide better features to the material as better solubilization, and others.

A "cyclodextrin-salicylic acid-chitosan" bifunctional monomer magnetic hydrophilic imprinted sandwich gel for targeted adsorption and slow release of ginkgolic acid.

This study aims to address the challenge of detoxifying ginkgolic acid and transform it from waste into a valuable resource. By using pseudo-template molecular imprinting technology to chemically modify polysaccharide materials, we developed a polysaccharide-based molecular imprinted material (MMCC-CD/CS-MIP) for the targeted separation and controlled release of ginkgolic acid. Under optimal conditions, MMCC-CD/CS-MIP demonstrated excellent adsorption performance (Qmax=47.786mgg-1) and desorption performance (QD=42.33mgg-1), with a desorption rate of 88.58%. In addition, the material exhibited outstanding selectivity, stability, recyclability, antibacterial activity, and sustained-release properties, with a cumulative release rate of 95.57% over 72h. The release data followed the Korsmeyer-Peppas model, while the adsorption behavior fit a multi-layer heterogeneous adsorption model (Freundlich model) and conformed to a second-order kinetic model. Thermodynamic analysis confirmed that the adsorption of ginkgolic acid by MMCC-CD/CS-MIP is both feasible and spontaneous. MMCC-CD/CS-MIP provides a promising solution for the detoxification of medicinal components.

Tetracycline removal from aqueous media and hospital wastewater using a magnetic composite of mango lignocellulosic kernel biochar/MnFe2O4/Cu@Zn-BDC MOF.

This study explored the use of mango lignocellulosic kernel biochar (MKB) modified with MnFe2O4 magnetic nanoparticles and a Cu@Zn-BDC metal-organic framework (MOF) (MKB/MnFe2O4/Cu@Zn-BDC MOF) for tetracycline (TC) removal from aqueous solutions and hospital wastewater. The modified biochar exhibited strong magnetic properties (19.803 emu/g) and a specific surface area of 30.456 m2/g, facilitating easy separation after adsorption. Using Response Surface Methodology-Central Composite Design (RSM-CCD), the adsorption model demonstrated high accuracy (F-value: 315.510, p < 0.0001, R2 = 0.9959). Thermodynamic analysis indicated that the process was endothermic and spontaneous, driven by physical interactions, with positive enthalpy and negative Gibbs free energy values. The pseudo-second-order kinetic model best described the adsorption, highlighting significant chemical interactions, while the Freundlich isotherm suggested adsorption on heterogeneous surfaces. The maximum TC adsorption capacities for MKB and its magnetic composite were 27.050 mg/g and 42.670 mg/g, respectively. The RL, n, and E parameters confirmed the desirability and physical nature of the interactions (0-1,〉1, and < 8 kJ/mol, respectively). The intraparticle diffusion model indicated multiple mechanisms were involved, and the biochar maintained excellent performance across reuse cycles, making it a highly effective and reusable adsorbent for water and wastewater treatment.

One‐Pot Synthesis of Magnetically Recyclable Fe3o4@Uio‐66 Composite with Enhanced Oxytetracycline Adsorption Capacity

AbstractAs one of the most stable metal‐organic frame materials (MOFs), UiO‐66 has attracted extensive attention in the adsorption field. However, the application of UiO‐66 is still constrained by the weak electron‐hole charge separation capability and the low accessibility of micropores. In this study, the mesoporous defects of UiO‐66 were constructed with acetic acid and doped with Fe3O4 to prepare magnetically recyclable Fe3O4@UiO‐66. The doping of Fe3O4 resulted in the formation of denatured mesoporous defects in UiO‐66, which was conducive to adsorption oxytetracycline (OTC) in water. The crystal structure and physicochemical characteristics of Fe3O4@UiO‐66 were examined. By using the static adsorption technique, the adsorption characteristics and mechanism of OTC on Fe3O4@UiO‐66 were investigated. The results reveal that Fe3O4@UiO‐66 has an adsorption capacity of 210 mg g−1 and an OTC removal ratio of 84.0%. The pseudo‐second‐order kinetics, Elovich, and Langmuir isothermal adsorption models were all applicable to the adsorption process. The adsorption process increased entropy and was an endothermic reaction. Solution pH has a little effect on the adsorption performance. This study provides the possibility of one‐step synthesis of MOFs that can efficiently adsorb tetracycline antibiotics in water with low cost and excellent recyclability and reusablity.