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In this research, a novel nanocomposite adsorbent, graphene oxide modified with magnetite nanoparticles and Lauric acid containing ethylenediaminetetraacetic acid (GFLE) has been applied for the eliminate of Cu 2+ ions. Adsorption performance was considered as a function of solution pH, Cu 2+ ions concentration (C Cu 2+ ), and temperature (T) and contact time (t). The levels of each variable were statistically optimized by Central Composite Design (CCD) and the response surface methodology (RSM) procedure to enhance the yield of system design. In these calculations, Y was measured as the response (the secondary concentration of Cu 2+ ions in mg L −1 ). Highest copper adsorption occurred at time of 105 min, temperature of 40 °C, the initial concentration of 280 mg L −1 , and pH = 1. The sorption equilibrium was well demonstrated using the Freundlich isotherm model. The second-order kinetics model suggested that the sorption mechanism might be ion exchange reactions. Thermodynamic factors and activation energy values displayed that the uptake process of Cu 2+ ions was spontaneous, feasible, endothermic and physical in nature. Regeneration studies also revealed that GFLE could be consistently reused up to 3 cycles.

To date, many nanoadsorbents have been developed and used to eliminate heavy metal contamination, however, one of the challenges ahead is the preparation of adsorbents from processes in which toxic organic solvents are used in the least possible amount. Herein, we have developed a new carboxylic acid-functionalized layered double hydroxide/metal–organic framework nanocomposite (LDH/MOF NC) using a simple, effective, and green in situ method. UiO-66-(Zr)-(COOH) 2 MOF nanocrystals were grown uniformly over the whole surface of COOH-functionalized Ni 50 Co 50 -LDH ultrathin nanosheets in a green water system under a normal solvothermal condition at 100 °C. The synthesized LDH/MOF NC was used as a potential adsorbent for removal of toxic Cd(II) and Pb(II) from water and the influence of important factors on the adsorption process was monitored. Various non-linear isotherm and kinetic models were used to find plausible mechanisms involved in the adsorption, and it was found that the Langmuir and pseudo-first-order models show the best agreement with isotherm and kinetic data, respectively. The calculated maximum adsorption capacities of Cd(II) and Pb(II) by the LDH/MOF NC were found to be 415.3 and 301.4 mg g −1 , respectively, based on the Langmuir model (pH = 5.0, adsorbent dose = 0.02 g, solution volume = 20 mL, contact time = 120 min, temperature = 25 ℃, shaking speed 200 rpm).

In the present paper, Graphene Oxide (GO) particles were prepared via Hummer method, and used in synthesis of composite membranes. Polyethersulfone (PES) nanocomposite membranes were synthesized via wet phase inversion technique, and using water as non-solvent. The membrane morphology was investigated using scanning electron microscopy (SEM). Change in the membrane surface hydrophilicity after modification was studied using contact angle measurements. The performance of fabricated PES nanocomposite membranes was measured by evaluating pure water flux, salt rejection, dye retention and heavy metals removal. The results indicated that by increasing the filler percentage up to 5 wt.%, the contact angle between the water droplet and the membrane surface was decreased and the droplet was more dispersed on the membrane surface which implies higher hydrophilicity of the prepared nanocomposite membranes. Moreover, the experimental results corroborated that addition of GO to the membrane significantly improved the pure water flux, salt rejection and heavy metals removal, and can be used as a novel methodology for preparation of high performance membranes in water treatment.

The development of easier, cheaper, and more effective synthetic strategies for hierarchical multimodal porous materials and multi-shell hollow spheres remains a challenging topic to utilize them as adsorbents in environmental applications. Here, the hierarchical architecture of multi-shell hollow micro–meso–macroporous silica with pollen-like morphology (MS-HMS-PL) has been successfully synthesized via a facile soft-templating approach and characterized for the first time. MS-HMS-PL sub-microspheres showed a trimodal hierarchical pore architecture with a high surface area of 414.5 m 2 g −1 , surpassing most of the previously reported multishelled hollow nanomaterials. Due to its facile preparation route and good physicochemical properties, MS-HMS-PL could be a potential candidate material in water purification, catalysis, and drug delivery. To investigate the applicability of MS-HMS-PL as an adsorbent, its adsorption performance for Cr(VI) in water was evaluated. Important adsorption factors affecting the adsorption capacity of adsorbent were systematically studied and Kinetics, isotherms, and thermodynamics parameters were computed via the non-linear fitting technique. The maximum capacity of adsorption computed from the Langmuir isotherm equation for Cr(VI) on MS-HMS-PL was 257.67 mg g −1 at 293 K and optimum conditions (pH 4.0, adsorbent dosage 5.0 mg, and contact time 90 min).

Hg(II) has been identified to be one of the extremely toxic heavy metals because of its hazardous effects and this fact that it is even more hazardous to animals than other pollutants such as Ag, Au, Cd, Ni, Pb, Co, Cu, and Zn. Accordingly, for the first time, tetrasulfide-functionalized fibrous silica KCC-1 (TS-KCC-1) spheres were synthesized by a facile, conventional ultrasonic-assisted, sol–gel-hydrothermal preparation approach to adsorb Hg(II) from aqueous solution. Tetrasulfide groups (–S–S–S–S–) were chosen as binding sites due to the strong and effective interaction of mercury ions (Hg(II)) with sulfur atoms. Hg(II) uptake onto TS-KCC-1 in a batch system has been carried out. Isotherm and kinetic results showed a very agreed agreement with Langmuir and pseudo-first-order models, respectively, with a Langmuir maximum uptake capacity of 132.55 mg g –1 (volume of the solution = 20.0 mL; adsorbent dose = 5.0 mg; pH = 5.0; temperature: 198 K; contact time = 40 min; shaking speed = 180 rpm). TS-KCC-1was shown to be a promising functional nanoporous material for the uptake of Hg(II) cations from aqueous media. To the best of our knowledge, there has been no report on the uptake of toxic Hg(II) cations by tetrasulfide-functionalized KCC-1 prepared by a conventional ultrasonic-assisted sol–gel-hydrothermal synthesis method.

In this study, heat transfer and entropy generation were investigated in a microchannel containing FMWNT/water nanofluids given the slip condition. The main focus was on utilizing injection technique in the presence of the magnetic field. The injection from the upper high-temperature wall was incorporated into the flow field. Injection at high Reynolds number causes vortex formation, which ultimately reduces local heat transfer in the adjacent injection zone. By applying the magnetic field, the vortex intensity as well as boundary layer thickness was diminished which in turn improved the heat transfer. Based on numerical results, at higher nanoparticle volume fraction, the effect of the magnetic field on heat transfer enhancement was amplified. Moreover, at higher Reynolds numbers, the magnetic field efficacy is more obvious. The highest heat transfer occurred at the highest values of the Hartmann and Reynolds numbers and eventually the nanoparticle volume fraction. Owing to applying the magnetic field on the injectable microchannel containing nanofluid, heat transfer improvement can reach up to 79%. From the second law prospective, the entropy generation intensified by 82.8%.

Heat transfer augmentation of the nanofluids is still an attractive concept for researchers due to rising demands for designing efficient heat transfer fluids. However, the pressure loss arisen from the suspension of nanoparticles in liquid is known as a drawback for developing such novel fluids. Therefore, prediction of the nanofluid pressure, especially in internal flows, has been focused on studies. Computational fluid dynamics (CFD) is a commonly used approach for such a prediction of fluid flow. The CFD tools are perfect and precise in prediction of the fluid flow parameters. But they might be time-consuming and expensive, especially for complex models such as 3-dimension modeling and turbulent flow. In addition, the CFD could just predict the pressure, and it is disabled for finding the relationship of such variables. This study is intended to show the performance of the artificial intelligence (AI) algorithm as an auxiliary method for cooperation with the CFD. The turbulent flow of Cu/water nanofluid warming up in a pipe is considered as a sample of a physical phenomenon. The AI algorithm learns the CFD results. Then, the relation between the CFD results is discovered by the AI algorithm. For this purpose, the adaptive network-based fuzzy inference system (ANFIS) is adopted as AI tool. The intelligence condition of the ANFIS is checked by benchmarking the CFD results. The paper outcomes indicated that the ANFIS intelligence is met by employing gauss2mf in the model as the membership function and x, y, and z coordinates, the nanoparticle volume fraction, and the temperature as the inputs. The pressure predicted by the ANFIS at this condition is the same as that predicted by the CFD. The artificial intelligence of ANFIS could find the relation of the nanofluid pressure to the nanoparticle fraction and the temperature. The CFD simulation took much more time (90–110 min) than the total time of the learning and the prediction of the ANFIS (369 s). The CFD modeling was done on a workstation computer, while the ANFIS method was run on a normal desktop.

Black phosphorus nanostructures have recently sparked substantial research interest for the rational development of novel chemosensors and nanodevices. For the first time, the influence of alkali metal doping of black phosphorus monolayer (BP) on its capabilities for nitrogen dioxide (NO 2 ) capture and monitoring is discussed. Four different nanostructures including BP, Li-BP, Na-BP, and K-BP were evaluated; it was found that the adsorption configuration on Li-BP was different from others such that the NO 2 molecule preferred a vertical stabilization rather than a parallel configuration with respect to the surface. The efficiency for the detection increased in the sequence of Na-BP < BP < K-BP < Li-BP, with the most significant improvement of + 95.2% in the case of Li doping. The Na-BP demonstrated the most compelling capacity (54 times higher than BP) for NO 2 capture and catalysis (− 24.36 kcal/mol at HSE06/TZVP). Furthermore, the K-doped device was appropriate for both nitrogen dioxide adsorption and sensing while also providing the highest work function sensitivity (55.4%), which was much higher than that of BP (10.4%).

Porous hollow fibres made of polyvinylidene fluoride were employed as membrane contactor for carbon dioxide (CO 2 ) absorption in a gas–liquid mode with methyldiethanolamine (MDEA) based nanofluid absorbent. Both theoretical and experimental works were carried out in which a mechanistic model was developed that considers the mass transfer of components in all subdomains of the contactor module. Also, the model considers convectional mass transfer in shell and tube subdomains with the chemical reaction as well as Grazing and Brownian motion of nanoparticles effects. The predicted outputs of the developed model and simulations showed that the dispersion of CNT nanoparticles to MDEA-based solvent improves CO 2 capture percentage compared to the pure solvent. In addition, the efficiency of CO 2 capture for MDEA-based nanofluid was increased with rising MDEA content, liquid flow rate and membrane porosity. On the other hand, the enhancement of gas velocity and the membrane tortuosity led to reduced CO 2 capture efficiency in the module. Moreover, it was revealed that the CNT nanoparticles effect on CO 2 removal is higher in the presence of lower MDEA concentration (5%) in the solvent. The model was validated by comparing with the experimental data, and great agreement was obtained.

Experimental and computational works were carried out on a new type of mesoporous silica. In the experimental section, functionalized hollow mesosilica spheres were prepared via a facile technique and then evaluated using some analytical techniques (FESEM, TEM, L-XRD, FTIR, BET-BJH, and TGA). The obtained results revealed that the synthesized material had hollow structure with a diamino-grafted porous shell. The molecular separation of crystal Violet (CV) and neutral Red (NR) dyes from water were investigated by adsorption process using the synthesized powder. Influence of adsorbent loading was evaluated as adsorption ability and dyes removal efficiency. Also, the obtained modeling results revealed appropriate fitting of data with non-linear Langmuir model. The theoretical studies were employed to study the adsorption and removal mechanism of cationic (CV and NR) and anionic (orange II (OII)) dyes using molecular dynamics calculations. Moreover, the simulation outcomes provided valuable information about quantum chemical properties including the HOMO–LUMO maps, chemical reactivity, global softness (σ) and hardness (η) for silica-linker-water-dyes components.