Enhanced adsorption performance of a novel Fe‐Mn‐Zr metal oxide nanocomposite adsorbent for anionic dyes from binary dye mix: Response surface optimization and neural network modeling

A novel adsorbent, Fe‐Mn‐Zr metal oxide nanocomposite was synthesized and investigated for removal of methyl orange (MO) and eosin yellow (EY) dyes from binary dye solution. The magnetic nanocomposite has shown surface area of 143.01 m²/g and saturation magnetization of 15.29 emu/g. Optimization was carried out via response surface methodology (RSM) for optimizing process variables, and optimum dye removal of 99.26% and 99.55% were obtained for MO and EY dye, respectively with contact time 62 min, adsorbent dose 0.45 g/l, initial MO concentration 11.0 mg/l, and initial EY concentration 25.0 mg/l. A feed forward back propagation neural network model has shown better prediction ability than RSM model for predicting MO and EY dye removal (%). Adsorption process strictly follows Langmuir isotherm model, and enhanced adsorption capacities of 196.07 and 175.43 mg/g were observed for MO and EY dye, respectively due to synergistic effects of physicochemical properties of trimetal oxides. Surface adsorption and pore diffusions are the mechanisms involved in the adsorption as revealed from kinetic studies.     

Mixed phase Fe2O3/Mn3O4 magnetic nanocomposite for enhanced adsorption of methyl orange dye: Neural network modeling and response surface methodology optimization

In this research, a novel magnetic mesoporous adsorbent with mixed phase of Fe₂O₃/Mn₃O₄ nanocomposite was prepared by a facile precipitating method and characterized extensively. The prepared nanocomposite was used as adsorbent for toxic methyl orange (MO) dye removal from aqua matrix considering its high surface area (178.27 m²/g) with high saturation magnetization (23.07 emu/g). Maximum dye adsorption occurs at solution pH 2.0 and the electrostatic attraction between anionic form of MO dye molecules and the positively charged nanocomposite surface is the main driving force behind this adsorption. Response surface methodology (RSM) was used for optimizing the process variables and maximum MO removal of 97.67% is obtained at optimum experimental condition with contact time, adsorbent dose and initial MO dye concentration of 45 min, 0.87 g/l and 116 mg/l, respectively. Artificial neural network (ANN) model with optimum topology of 3–5–1 was developed for predicting the MO removal (%), which has shown higher predictive ability than RSM model. Maximum adsorption capacity of this nanocomposite was found to be 322.58 mg/g from Langmuir isotherm model. Kinetic studies reveal the applicability of second‐order kinetic model with contribution of intra‐particle diffusion in this process.     

Adsorption of tartrazine from an aqueous solution by octadecyltrimethylammonium bromide-modified bentonite: Kinetics and isotherm modeling

A modified bentonite was prepared at different surfactant (ODTMA) loadings through ion exchange. The obtained organobentonite adsorbent materials were then used for the removal of an anionic dye, tartrazine, from an aqueous solution. The bentonite was characterized by X-ray diffraction, Fourier transform infrared spectroscopy, thermogravimetric analysis, and Brunauer- Emmett-Teller (BET) method. The modification of organophilic bentonite by ODTMA increases the basal spacing d₀₀₁ from 24.1 to 39.1 Å when the cation exchange capacity increases from 1 to 4. The increase in the spacing, due to the basic organic modifications, was confirmed by the results of thermogravimetric analysis, Fourier transform infrared spectroscopy, and BET. The effects of contact time, initial concentration, and solution pH onto an adsorbed amount of tartrazine were investigated. To predict adsorption isotherm, the experimental data were analyzed using the Langmuir and Freundlich isotherm equations. It was determined that the isotherm data were fitted to the Langmuir isotherm. The adsorption process was also found to follow a pseudo-second-order kinetic model.     

Bio-adsorption of dyes from aqueous solution by powdered excess sludge (PES): Kinetic,isotherm, and thermodynamic study

Over 30 million tons of excess sludge is discharged from rural municipal sewage plants annually in China and it is predicted that this figure will keep increasing. However, most of the excess sludge is dumped in landfills except for minor applications. In this study, based on low-cost and recycling waste, the excess sludge was used to adsorb organic dyes from aqueous solution after being directly dewatered. The powdered excess sludge (PES) presents selective adsorption property to cationic dyes. Statics batch adsorption experiments of malachite green (MG) on PES were performed to evaluate the effects of pH, adsorbent dosage, and initial MG concentration. Results revealed that the bio-adsorption equilibrium of MG on the PES can be quickly achieved at 30 min with maximum percentage adsorption of 84% at pH 7, initial dye concentration of 20 mg L^?1, and adsorbent dosage of 1.5 g L^?1. Moreover, the adsorption kinetics follows a pseudo-second-order pathway, and the equilibrium adsorption data could be described well by the Langmuir isotherm equation. Intra-particle diffusion is not the only rate-controlling step in the entire adsorption process. The adsorption process is endothermic, spontaneous, and random. PES can be used as a low-cost adsorbent for refractory cationic organic dye in effluent.     

Artificial Neural Network (ANN) Method for Modeling of Sunset Yellow Dye Adsorption Using Nickel Sulfide Nanoparticle Loaded on Activated Carbon: Kinetic and Isotherm Study

In this paper, the NiS nanoparticles are prepared and characterized by x-ray powder diffraction and scanning electron microscopy. The NiS nanoparticles showed the excellent adsorption properties toward sunset yellow (UA) dye. The effect of solution pH, adsorbent dosage (0.005–0.020 g), contact time (0.5–30 minutes), and initial UA concentration (5–40 mg L^?1) on the extent of adsorption was investigated and modeled by artificial neural network. The experimental equilibrium data was analyzed by Langmuir, Freundlich, Tempkin, and D–R isothermal models. It was seen that the data was well presented by Langmuir model with a maximum adsorption capacity of 333.3 mg g^?1 at 26°C. Kinetic studies at various adsorbent dosages and initial UA concentrations show that high removal percentage (>90%) was achieved within 15 minutes. The adsorption of UA follows the pseudo-second-order rate model. The experimental data were applied to train the multilayer feed-forward neural network with three inputs and one output with Levenberg–Marquart algorithm and different numbers of neurons in the hidden layer. The minimum mean square error of 0.0003 and determination coefficient of (R²) 0.99 were found.     

Enhanced Adsorption of Hexavalent Chromium onto Magnetic Calcium Ferrite Nanoparticles: Kinetic,Isotherm, and Neural Network Modeling

Calcium ferrite nanoparticles with super-paramagnetic behavior were synthesized via simple chemical precipitation method for effective removal of hexavalent chromium from aqueous media. The properties of synthesized nanoparticles were studied by X-ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier transform infrared (FTIR) spectroscopy, Brunauer-Emmett-Teller (BET), and vibrating sample magnetometer (VSM) measurements. The ferrite nanoparticles have shown polycrystalline nature and high BET specific surface area (229.83 m²/g) with active functional groups on the surface. The adsorption process follows second-order kinetics with the involvement of intra-particle diffusion and adsorption capacity as much as 124.11 mg/g was determined from the Langmuir isotherm. The thermodynamic analysis revealed that the adsorption process was feasible, spontaneous, and exothermic in nature. A three-layer feed-forward back-propagation artificial neural network (ANN) model was employed to predict the removal (%) of Cr(VI) ions as output. Optimal ANN network (4:8:1) shows the minimum mean squared error (MSE) of 0.00161 and maximum coefficient of determination (R²) of 0.984. The adsorption process is mostly influenced by solution pH and followed by adsorbent dosage, initial Cr(VI) concentration, and contact time as illustrated by sensitivity analysis. With small size and high surface area, biocompatibility, ecofriendly nature, easy magnetic separation, and enhanced adsorption capacity towards Cr(VI), calcium ferrite nanoparticles will find its potential application in wastewater remediation.     

Application of artificial neural network for comparison and modeling of the ultrasonic and stirrer assisted removal of anionic dye using activated carbon supported with nanostructure material

In this study, a green approach has been described for the synthesis of copper sulfide nanoparticles loaded on activated carbon (CuS‐NP‐AC) and usability of it for the removal of sunset yellow (SY) dye by ultrasound‐assisted and stirrer has been compared. In addition, the artificial neural network (ANN) model has been employed for a forecasting removal percentage of SY dye using the results obtained. This material was characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The impact of variables, including initial dye concentration (mg/L), pH, adsorbent dosage (g), sonication time (min) and temperature (°C) on SY removal was studied. Fitting the experimental equilibrium data of different isotherm models such as Langmuir, Freundlich, Temkin and Dubinin–Radushkevich models display the suitability and applicability of the Langmuir model. Analysis of experimental adsorption data of different kinetic models including pseudo‐first and second order, Elovich and intraparticle diffusion models indicate the applicability of the second‐order equation model. The adsorbent (0.005 g) is applicable for successful removal of SY dye (> 98%) in short time (9 min) under ultrasound condition. A three layer ANN models with 8 and 6 neurons at hidden layer was selected as optimal models using stirrer and ultrasonic, respectively. These models displayed a good agreement between forecasted data and experimental data with the determination coefficient (R²) of 0.9948 and 0.9907 and mean squared error (MSE) of 0.0001 and 0.0002 for training set using stirrer and ultrasonic, respectively.     

Adsorption of Malachite Green by Diatomite: Equilibrium Isotherms and Kinetic Studies

The utilization of diatomite as potential adsorbent to remove malachite green (MG) from aqueous solution was developed. The characterization of the diatomite was evaluated by scanning electron microscope (SEM) and Brurauer Emmerr Teller (BET). The operating variables of pH, diatomite mass, initial MG concentration, and adsorption reaction time were studied. The equilibrium, kinetics, and thermodynamic parameters were investigated as well. It was found that the diatomite was composed of integral and almost circle sieve tray with lots of small pores on it, which afforded the diatomite high specific surface area of 46.09 m² g^?1. The optimum pH and reaction time were 7 and 90 minutes, respectively. The MG removal increased accordingly as the diatomite mass increased. The isotherm results showed that the equilibrium data were fitted to Langmuir model better, indicating the MG adsorption was better characterized by mono-layer. The maximum mono-layer capacity obtained from Langmuir was 23.64 mg g^?1 at 25°C. The kinetic studies indicated that experiment data followed pseudo-second-order model better. It also revealed that intraparticle diffusion was not the only rate-controlling step. The thermodynamic results concluded that the adsorption process was endothermic and more favorable at high temperature. Researches confirmed the applicability of diatomite as an efficient adsorbent and low-cost process to remove hazardous materials.     

Preparation and characterization of activated carbon from pine cone by microwave-induced ZnCl2 activation and its effects on the adsorption of methylene blue

In this work, activated carbon prepared from pine cone (PCAC) with ZnCl₂ as an activation agent under microwave radiation was investigated. The activation step was performed at the microwave input power of 400 W and radiation time of 5 min. The properties of activated carbon were characterized by N₂ adsorption Brunauer–Emmett–Teller (BET), scanning electron microscopy and Fourier transform infrared spectroscopy. Results showed that the BET surface area, Langmuir surface area, and total pore volume of PCAC were 939, 1,486 m²/g and 0.172 cm³/g, respectively. Adsorption capacity was demonstrated by the iodine numbers. The adsorptive property of PCAC was tested using methylene blue dye. Equilibrium data was best fitted by the Langmuir isotherm model, showing a monolayer adsorption capacity of 60.97 mg/g. The pseudo-first- and pseudo-second-order kinetic models were examined to evaluate the kinetic data, and the rate constants were calculated. Adsorption of the dyes followed pseudo-first order kinetics. Thermodynamic parameters such as free energy, enthalpy and entropy of dye adsorption were obtained.     

One-pot synthesis of a novel magnetic activated carbon/clay composite for removal of heavy metals from aqueous solution

Abstract

In the present work, a novel composite consisting of magnetite, activated carbon from spent coffee grounds and natural clay (MACCC) was prepared by a one-pot synthesis method via a simultaneous activation and magnetization processes. Various techniques (XRD, FTIR, SEM, TEM, EDX, BET) were utilized to characterize the synthesized composite before utilizing it as an adsorbent for removal of Cu(II), Ni(II) and Pb(II) ions from aqueous solutions. Conditions for removal of heavy metals were thoroughly optimized as 25?°C, pH of 5.5, adsorbent dosage of 2?g L^?1, and a contact time of 60?min. Three models of pseudo first-, second-order and intraparticle diffusion as well as three models of Langmuir, Freundlich, and Temkin were used to analyze kinetics and isotherms of the adsorption process. Thermodynamics was discussed completely. Regeneration and recyclability of the adsorbent were also evaluated. Based on the analysis of experimental results, a possible adsorption mechanism of heavy metals onto the synthesized composite was proposed. The maximum capacities caculated from Langmuir model followed the order of Pb(II) > Cu(II) > Ni(II) as 143.56, 96.16 and 84.86?mg·g^?1, respectively. The overall results indicated that MACCC is a potential adsorbent for removal of toxic Pb(II), Cu(II) and Ni(II) ions from wastewater due to simple preparation, high removal efficiency and good recyclability.     

Fast and highly efficient removal of anionic organic dyes with a new Cu modified nanoclinoptilolite

Adsorption of anionic dyes onto most of zeolites with net negative charge may be restricted. In this article, a natural nanoclinoptilolite was modified with Cu and the obtained nanomaterial was used as an effective adsorbent for removal of methyl red as an anionic model azo dye up to 90% in 20 min.This new adsorbent was characterized utilizing X-ray diffraction, Fourier transform infrared spectroscopy, field emission scanning electron microscopy and energy-dispersive X-ray spectroscopy. Also, effects of methyl red concentration, mass of sorbent and pH on the removal percent were examined. Moreover, the adsorption mechanism was investigated by plotting the Langmuir and Freundlich adsorption isotherms. The results showed that the data can be fitted with both models. The most adsorption capacity obtained from Langmuir isotherm was about 200 mg/g. Moreover, the Cu modified nanoclinoptilolite was successfully employed for adsorption of another anionic dye, bromothymol blue. The results confirmed that this new adsorbent can be effectively applied for removing of anionic dyes from waste waters.     

Adsorption of cadmium and lead from palm oil mill effluent using bone-composite: optimisation and isotherm studies

The adsorption of Cd and Pb ions from palm oil mill effluent on a mesoporous-activated cow bone composite powder has been investigated. Adsorbent was developed from cow bones, coconut shells and zeolite. The composite examined in the present work has a BET surface area of 248.398 m²/g. The optimisation of the removal efficiency of the heavy metals was investigated using central composite design and analysed using response surface methodology. The analysis of variance of the quadratic model signified that the model suitably predicted the uptake of the heavy metal ions at a 95% confidence level. The optimal operating condition was recorded at pH 4, 50 rpm, within 24 h and 1 mm of particle size and 12.5 gL^?1 of adsorbent dosage. The characteristics of the composite were investigated using the Fourier transform irradiation. The morphology and chemical composition of composite was examined using the scanning electron microscopy equipped with energy dispersive x-ray. Characterisation study was conducted before and after the adsorption process. The results obtained illustrated that the removal of cadmium and lead from POME was influenced by the functional groups available on the surface of the composite. The carboxyl and hydroxyl groups are mainly responsible for the removal of cadmium and lead through chelating process. The point of zero charge (pH_pzc) revealed that the adsorbent contained acidic sites with negatively charge surface which influenced the adsorption process. The experimental data of the heavy metals of Cd and Pb investigated were fitted to the Langmuir and Freundlich models. The result revealed that the adsorption equilibrium data fitted better to the Langmuir model for the adsorption Cd and to the Freundlich model for the adsorption of Pb.     

A versatile amphiprotic cotton fiber for the removal of dyes and metal ions

Adsorption is an efficient method to combat the important issues of water pollution caused by dyes and metal ions. However, due to the surface charge diversity of pollutants, there is a pressing need to develop an all-round, efficient, cheap and environmentally friendly adsorbent. To this end, this work synthesized an amphiprotic adsorbent based on cotton fibers, which were chemically modified with a cationic monomer (3-chloro-2-hydroxypropyl trimethyl ammonium chloride) and anionic monomer (2-acrylamide-2-methyl propane sulfonic acid) respectively. The resultant amphiprotic cotton (AP-cotton) can cope with both of anionic and cationic pollutants. Its adsorption behavior as influenced by the pH value, adsorption time and initial concentration of various adsorbates was investigated. The results demonstrate that the adsorption equilibrium was reached within 4 h for Congo red (CR) and methylene blue (MB), 2 h for Cu²⁺ and 3 h for Pb²⁺, respectively. Adsorption kinetics showed that the adsorption rate was well fitted with the pseudo-second-order rate model, and the best adsorption isotherms fitted the Langmuir model. The Langmuir maximum adsorption capacities were 175.1 mg/g for CR, 113.1 mg/g for MB, 88.9 mg/g for Cu²⁺ and 70.6 mg/g for Pb²⁺, respectively, and the adsorption capacities could be maintained above 90 % after six regenerations. The all-round adsorption capacity and good regeneration performance of AP-cotton benefited from its hollow, flat-banded structure and amphiprotic characteristic. Therefore, AP-cotton exhibited a much better application potential compared with many other reported adsorbents based on natural materials.     

Uranium removal from nitric acid raffinate solution by solvent immobilized PVC cement

The present work deals with uranium removal from a nitric acid raffinate (waste) solution using prepared solvent (tri-butyl phosphate, TBP) immobilizing PVC cement (SIC) as a suitable adsorbent. The studied relevant factors affecting uranium adsorption onto SIC adsorbent involved; contact time, solution molarity, initial uranium concentration and temperature. The obtained adsorption isotherm of uranium onto the SIC adsorbent was fitted to Langmuir, Freundlich and Dubinin–Radushkviech (D–R) adsorption models. The results showed that the obtained equilibrium data fitted well the Langmuir isotherm. Additionally, it was found that the adsorption process obeys the pseudo second-order kinetic model. On the other hand, the calculated theoretical capacity of our prepared SIC adsorbent reached about 17 g U/kg SIC. Uranium adsorption from the studied raffinate solution was carried out applying the attained optimum conditions. The obtained data showed that 58.4 mg U/5 g SIC were adsorbed. However, using of 2 M HNO₃ solution as an eluent, 93 (54.3 mg U) from the adsorbed amount were eluted.     

Characterization and Mechanism Elucidation of Dye Adsorption Using Cuprous Selenide Nanoparticles from Aqueous Solutions

The removal of cationic dyes, methylene blue(MB) and rhodamine B(RB), and anionic dyes, methyl or-ange(MO) and eosin Y(EY), from aqueous solutions by adsorption using Cu₂Se nanoparticles(Cu₂SeNPs) was studied. The effects of the initial pH values, adsorbent doses, contact time, initial dye concentrations, salt concentrations, and operation temperatures on the adsorption capacities were investigated. The adsorption process was better fitted the Langmuir equation and pseudo-second-order kinetic model, and was spontaneous and endothermic as well. The adsorption mechanism was probably based on the electrostatic interactions and π-π interactions between Cu₂SeNPs and dyes. For an adsorbent of 0.4 g/L of Cu₂SeNPs, the adsorption capacities of 23.1(MB), 22.9(RB) and 23.9(EY) mg/g were achieved, respectively, with an initial dye concentration of 10 mg/g(pH=8 for MB and pH=4 for RB and EY) and a contact time of 120 min. The removal rate of MB was still 70.4% for Cu₂SeNPs being reused in the 5th cycle. Furthermore, the recycled Cu₂SeNPs produced from selenium nanoparticles adsorbing copper were also an effective adsorbent for the removal of dyes. Cu₂SeNPs showed great potential as a new adsorbent for dyes removal due to its good stability, functionalization and reusability.     

Effective removal of anionic dyes from aqueous solutions by novel polyethylenimine-ozone oxidized hydrochar (PEI-OzHC) adsorbent

The adsorption behavior of the anionic dyes Remazol Brilliant Blue R (RBBR) and Reactive Black 5 (RB5) from aqueous solutions by polyethylenimine ozone oxidized hydrochar (PEI-OzHC) was investigated. The adsorption capacities of both dyes increased with functionalization of PEI in the hydrochar adsorbent. The results of surface characterization (FTIR, BET, TGA, elemental analysis, and SEM) showed that PEI modification greatly enhanced the adsorbent surface chemistry with a slight improvement of adsorbent textural properties. In addition, the adsorption kinetics data showed an excellent adsorption efficiency as reflected in the high removal percentages of the anionic dyes. The Isotherm results indicated that RBBR and RB5 dye adsorption occurred via monolayer adsorption, and chemisorption was the rate-controlling step. The PEI-OzHC adsorbent possesses higher maximum Langmuir adsorption capacity towards RBBR (218.3 mg/g) than RB5 (182.7 mg/g). This increase in adsorption capacity is attributed to the higher number of functional groups in RBBR that interact with the adsorbent. This study reveals the potential use of adsorbents derived from pine wood hydrochar in municipal as well as industrial wastewater treatment. Furthermore, surface chemistry modification is proven as an effective strategy to enhance the performance of biomass-derived adsorbents.     

Design and evaluation of functionalized multi-walled carbon nanotubes by 3-aminopyrazole for the removal of Hg(II) and As(III) ions from aqueous solution

Carboxylated multi-walled carbon nanotubes (MWCNTs-COOH) were chemically modified with 3-aminopyrazole (MWCNTs-f) and applied as an efficient adsorbent to mercury and arsenic adsorption from aqueous solutions. The adsorbents were characterized by FT-IR, EDX, FE-SEM, TGA, and BET. The effects of pH, adsorbent dose, and initial ions concentration on the adsorption efficiency and the optimum conditions were investigated by central composite design. The optimum conditions were obtained at pH 7.6–7.9, adsorbent dose 20 mg, and initial ions concentration 20 ppm. So the maximum adsorption efficiencies in these conditions were 80.5 and 72.4% for the removal of Hg(II) and As(III) by MWCNTs-f, respectively. The quadratic model was used for the analysis of variance and indicated that adsorption of metal ions strongly depends on pH. Also, the pseudo-second-order model has been achieved from the adsorption kinetic studies. Furthermore, the experimental data were well fitted to the Langmuir isotherm and the maximum adsorption capacities obtained were 112 and 133 mg g^?1 for the adsorption of Hg(II) and As(III) by MWCNTs-f, respectively. Moreover, a thermodynamic study revealed that the adsorption reactions were spontaneous and endothermic with the increase in randomness. In addition, a desorption study showed the favorable regeneration ability of MWCNTs-f even after three adsorption–desorption cycles. Therefore, the MWCNTs-f adsorbent has good potential for the removal of Hg(II) and As(III) pollutants from aqueous solutions.     

Removal of cadmium(II) and lead(II) ions from model aqueous solutions using sol–gel-derived inorganic oxide adsorbent

A study was conducted concerning the preparation and application of a novel synthetic oxide adsorbent of MgO-SiO₂ type. The material was prepared via a sol–gel route, utilizing magnesium ethoxide and tetraethoxysilane as precursors of magnesium oxide and silica respectively, and ammonia as a catalyst. The powder was comprehensively analyzed with regard to chemical composition (EDS method), crystalline structure, morphology, characteristic functional groups, electrokinetic stability and porous structure parameters (BET and BJH models). The synthesized oxide adsorbent is amorphous, with irregularly shaped particles, a relatively large surface area of 612 m²/g, and negative surface charge over almost the whole pH range. Comprehensive adsorption studies were performed to investigate the adsorption of Cd(II) and Pb(II) ions on the MgO–SiO₂ oxide adsorbent, including evaluation of adsorption kinetics and isotherms, the effect of pH, contact time and mass of adsorbent. It was shown that irrespective of the conditions of the adsorption process, the synthesized MgO–SiO₂ adsorbent exhibits slightly better affinity to lead(II) than to cadmium(II) ions (sorption capacity of 102.02 mg(Pb²⁺)/g and 94.05 mg(Cd²⁺)/g). The optimal time for removal of the analyzed metal ions was 60 min, although adsorption reached equilibrium within 10 min for Pb(II) and within 15 min for Cd(II) ions, which was found to fit well with a type 1 pseudo-second-order kinetic model. Additionally, adsorption efficiency was affected by the pH of the reaction system—better results were obtained for pH ≥7 irrespective of the type of metal ion.     

Ultrasound-aided rapid and enhanced adsorption of anionic dyes from binary dye matrix onto novel hematite/polyaniline nanocomposite: Response surface methodology optimization

In recent times, polyaniline (PANI), a conducting polymer, has been studied widely for environmental remediation application due to its controllable electric conductivity with high surface area, which makes it a suitable adsorbent material. But lower mechanical stability of PANI is considered to be a serious drawback for its large-scale industrial application. To improve the mechanical strength of PANI, in this study, hematite nanoparticles were impregnated onto PANI by oxidative polymerization method in order to fabricate a novel organometallic nanocomposite (hematite-PANI-NC). The hematite-PANI-NC was used as adsorbent for removal of methyl orange (MO) and eosin yellow (EY) dye from binary dye matrix under ultrasonic-assisted adsorption. Excellent MO and EY dye removal (more than 98%) was observed from binary matrix at a wide solution pH from 2.0 to 6.0, and under ultrasound wave the adsorption equilibrium was achieved within 15 min only. Both MO and EY dyes adsorption experimental data strictly followed Langmuir isotherm, and maximum monolayer adsorption capacity of 126.58 mg/g and 112.36 mg/g was observed for MO and EY dye, respectively. The uptake mechanism of MO and EY dyes onto hematite-PANI-NC is governed by electrostatic interaction, π-π bonding and hydrogen bonding between dye molecules and nanocomposite. Response surface methodology analysis reveals maximum MO and EY removal of 98.43% and 99.35% at optimum experimental conditions. This study implies that the hybrid organometallic material hematite-PANI-NC has high potential for quick and enhanced sono-assisted uptake of anionic dyes from water near neutral solution pH.