Prediction of Nanofluid Characteristics and Flow Pattern on Artificial Differential Evolution Learning Nodes and Fuzzy Framework

A combination of a fuzzy inference system (FIS) and a differential evolution (DE) algorithm, known as the differential evolution-based fuzzy inference system (DEFIS), is developed for the prediction of natural heat transfer in Cu-water nanofluid within a cavity. In the development of the hybrid model, the DE algorithm is used for the training process of FIS. For this purpose, first, the case study is simulated using the computational fluid dynamic (CFD) method. The CFD outputs, including velocity in the y-direction, the temperature of the nanofluid, and the nanoparticle content (Ø), are employed for the learning process of the DEFIS model. By choosing the optimum number of inputs and the number of population, the underlying DEFIS variable parameters are studied. After reaching the high value of DEFIS intelligence, in the learning step, a variety of Ø values (e.g., 0.5, 1, and 2) are reviewed. For the full intelligence of DEFIS, the velocity of the nanofluid is predicted in further nodes of the cavity domain. Finally, the velocity of the nanofluid is predicted by using the data at Ø = 0.15, which are absent in the DEFIS process.

Developing Intelligent Algorithm as a Machine Learning Overview over the Big Data Generated by Euler-Euler Method To Simulate Bubble Column Reactor Hydrodynamics

A bubble column reactor is simulated by a combination of Euler-Euler and adaptive network-based fuzzy inference system (ANFIS) method to develop an understanding of the machine learning (ML) technique in describing complex behavior of multiphase flow in bubble column reactors and for deep learning of input and output connections. In the validation stage of simulations, an intelligent bubble column is created that uses artificial intelligence nodes or neural network nodes, and the results of prediction indicated excellent agreement with computational fluid dynamics (CFD) simulation results. The hydrodynamic characteristics of the air bubbles and the amount of stress inside the bubble column reactor are used as the output of the ANFIS method. This study showed that when a three-dimensional bubble column is trained by a ML method, a similar CFD simulation can be created, which is independent of CFD source data. This type of smart simulation also enables us to avoid repeating the simulations with CFD methods that are time-consuming and computationally expensive for process modeling and optimization.

Modification of polyethersulfone membrane using MWCNT-NH2 nanoparticles and its application in the separation of azeotropic solutions by means of pervaporation

In this study, functionalized multi-walled carbon nanotubes (MWCNT-NH₂) were synthesized as an additive for the preparation of mixed matrix membranes (MMMs) and then were investigated by FTIR and FE-SEM techniques. Polyether sulfone (PES) polymeric membrane modified with functionalized MWCNT-NH₂ carbon nanotubes was prepared by phase inversion method. The effect of MWCNT-NH₂ on the morphology and property of the PES membrane was evaluated using scanning electron microscopy. The flux, enrichment factor and swelling properties of modified membranes were also used to investigate the membranes performance. The results showed that the flux and enrichment factor in modified PES membrane containing 5 wt.% of functionalized MWCNT-NH₂ carbon nanotubes were obtained 1.2 L.m^-2h^-1 and 3.3, respectively. The influence of methanol concentration on the flux and enrichment factor was investigated. The results corroborated that the flux didn’t change significantly, while the enrichment factor was decreased.

Thermal and Flow Visualization of a Square Heat Source in a Nanofluid Material with a Cubic-Interpolated Pseudo-particle

Using thermal sources with nanoparticles can change the thermal and velocity distribution and the streamline around solid objects in mechanical devices. In the current study, square-shaped thermal structures are used in the cavity, while the fluid in the domain is fully contaminated with nanoparticles to enhance the heat- and mass-transfer distribution within the system. The connection of thermal elements is installed with equal distance in the domain, and then the nanoparticle is added in the container to improve the heat-transfer rate. The nanofluid is simulated using Cubic-Interpolated Pseudo-particle (CIP) model in the domain with different concentrations. The study shows that the sequence of hot wall structure can disturb the flow as well as thermal distribution. However, a very small streamline can be generated during heat transfer. As a result of thermal structure in the domain, the zero velocity zone in the domain can move to other parts of the cavity. This disturbance can change the heating mechanism in the system, which results in a better rate of heat-transfer characteristics in the system and process engineering. Also, the CIP computing method shows great ability in the modeling of sharp walls/structures with thermal sources.

Computational Fluid Dynamic Modeling and Simulation of Hydrocracking of Vacuum Gas Oil in a Fixed-Bed Reactor

A four-lump computational fluid dynamic (CFD) model was proposed for the investigation of vacuum gas oil hydrocracking in a trickle-bed reactor. The experiment was conducted at 360-390 °C and 146 bar in the reactor at three different flow rates. It was found that the modeling predictions of vacuum gas oil cracking agreed well with the experimental measurements. Furthermore, the developed model analyzed the effects of the feed flow rate in the reactors on the concentration distribution and product yield. The maximum yields of the products including distillate (31%), naphtha (14%), and gas (3%) were obtained at the lowest feed flow rate. However, the feed flow rate enhancement from 0.1568 to 0.2059 kg·h^-1 led to the increasing feed concentration and reducing the product concentration at the outlet of the reactor. The latter phenomenon was happened due to the decreasing feed residence time with the increasing mass flow rate.

Changes in the Number of Membership Functions for Predicting the Gas Volume Fraction in Two-Phase Flow Using Grid Partition Clustering of the ANFIS Method

A 2D-bubble column reactor (BCR) including gas and liquid phases is simulated, and fluid characteristics such as gas-phase volume fraction and gas-phase turbulence are extracted from the CFD simulations. A type of heuristic algorithm called adaptive network-based fuzzy inference system (ANFIS) is applied here to simulate the gas-phase volume fraction in a physical system. Indeed, the x direction, the y direction, and gas-phase turbulence are considered as the ANFIS inputs. Changes in the number of inputs as well as membership functions are evaluated and studied to obtain a high level of ANFIS intelligence. By implementing the highest ANFIS intelligence, a surface is predicted, which suggests that the gas-phase volume fraction is based on x and y directions. It provides capability to achieve the amount of gas-phase volume fraction in different points of a 2D-BCR.

Prediction of thermal distribution and fluid flow in the domain with multi-solid structures using Cubic-Interpolated Pseudo-Particle model

A nanofluid is a suspension of very small solid particles in a continuous fluid with significant improvement of heat transfer characteristics in the main liquid. In general, in industrial equipment, the heat transfer rate can be improved with optimization of equipment including the domain structure and using the different types of nanofluids. Still, there is a big challenge to analyze the heat transfer and fluid circulation in the domain. Having nanofluids with experimental observation as using sensors and probes are destructive for the liquid stream and they are costly to observe the details of particles and the original fluid. Over the 20 years, different numerical methods have been implemented in the modeling of the heat and fluid distribution in industrial equipment containing nanofluids. Among all mathematical and numerical methods, Cubic-Interpolated Pseudo-Particle (CIP) model provides a strong potential in the prediction of the fluid structure and heat analysis, when there is a complex structure of thermal walls and high concentration of nanoparticles. However, this method is not frequently used by researchers in nanofluids analysis. In this study, the Cubic-Interpolated Pseudo-Particle model is applied to predict the flow in the square domain. different thermal walls (multi-solid structure) and hot cylindrical wall are specifically used to observe the fluid flow and heat distribution in the domain. Additionally, for a better understanding of the flow in the domain, different numbers of cylinders are used and also different amounts of nanofluid in the continuous fluid are added. The results show that adding more walls in the domain causes the change in the vortex structure. Furthermore, using nanofluid results in better heat transfer rate in the system. The CIP method is also a capable tool to predict the heat and fluid flow in the multi-solid structure domain.

Hierarchical multi-shell hollow micro-meso-macroporous silica for Cr(VI) adsorption

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 m² 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).

Meso-architectured siliceous hollow quasi-capsule

Reactive dyes have been identified to be highly hazardous pollutants because they were shown to be more toxic towards mammals than general organic compounds and organic dyes. Accordingly, for the first time, meso-architectured mercapto-modified siliceous hollow quasi-capsules (SH-SHQC) were prepared by a facile, ultrasonic-assisted, and one-step synthesis protocol. Adsorptive removal of rhodamine B (RhB) and methylene blue (MB) onto SH-SHQC in a batch system has been investigated. Isotherm results agreed very well with the Langmuir equation for both dyes. The maximum adsorption capacity of SH-SHQC for RhB and MB was determined with the Langmuir equation and was found to be 147.06 and 119.05 mg g^-1 at 298 K, respectively (pH: 6.0 for RhB and 7.0 for MB; adsorbent dosage: 15.0 mg; the volume of the dye solution: 40.0 mL). Among different kinetic models, the pseudo-first-order equation was better fitted since experimental data agreed very well with theoretical data. SH-SHQC was shown to be a promising adsorbent for adsorptive removal of reactive dyes from aqueous solutions. To date, there has been no report on the adsorption of reactive dye cations by meso-architectured mercapto-modified siliceous hollow quasi-capsules prepared by an ultrasonic-assisted, one-pot, and sol-gel synthesis method.

Prediction of Nanofluid Temperature Inside the Cavity by Integration of Grid Partition Clustering Categorization of a Learning Structure with the Fuzzy System

In this study, a quadratic cavity is simulated using computational fluid dynamics (CFD). The simulated cavity includes nanofluids containing copper (Cu) nanoparticles. The L-shaped thermal element exists in this cavity to produce heat distribution along with the domain. Results such as fluid velocity distribution in two dimensions and the fluid temperature field were generated as CFD simulation results. These outputs were evaluated using an adaptive neuro-fuzzy inference system (ANFIS) for learning and then the prediction process. In the training process related to the ANFIS method, x coordinates, y coordinates, and fluid temperature are three inputs, and the fluid velocity in line with Y is the output. During the learning process, the data have been classified using a clustering method called grid clustering. In line with the attempt to rise ANFIS intelligence, the alterations in the number of input parameters and of membership structure have been analyzed. After reaching the highest level of intelligence, the fluid velocity nodes were predicted to be in line with y, especially cavity nodes, which were absent in CFD simulations. The simulation findings indicated that there is a good agreement between CFD and clustering approach, while the total simulation time for learning and prediction is shorter than the time needed for calculation using the CFD method.

Effect of graphene oxide on modifying polyethersulfone membrane performance and its application in wastewater treatment

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.

A hierarchical LDH/MOF nanocomposite: single, simultaneous and consecutive adsorption of a reactive dye and Cr(vi)

The design and development of an environmentally benign porous adsorbent for effective simultaneous adsorption of organic dyes and heavy metals from water are important but remain a big challenge. Herein, we have designed a layered double hydroxide/metal-organic framework-based hierarchical nanocomposite (LDH/MOF HNC) by a facile, room-temperature in situ approach. This paper for the first time reports a hierarchical trimodal micro-meso-macroporous LDH/MOF composite with a high surface area (surface area 1282 m2 g-1 and pore volume 0.93 cm3 g-1), synthesised by uniformly growing MOF nanocrystals on the surface of LDH nanosheet ultrathin films. An attempt is made to quantitatively demonstrate the adsorption data via suitable nonlinear kinetic and isotherm equations for single, simultaneous, and consecutive adsorption of the orange II reactive dye and Cr(vi). Experiments were performed at various values of pH (6.0-11.0), adsorbent dosages (1.0-8.0 mg), adsorbate concentrations (5-500 mg L-1), and temperatures (293-323 K). The Langmuir model revealed a satisfactory fit to the equilibrium data of the LDH/MOF HNC (correlation coefficients R2 > 0.98) with a calculated maximum adsorption capacity of 1173 and 733 mg g-1 for orange II and Cr(vi), respectively, in a simultaneous adsorption system. The results of the study demonstrated that LDH/MOF HNCs could potentially be applied as a promising nanoadsorbent for the simultaneous removal and extraction of toxic dyes and metals from water.

Preparation and optimization of activated nano-carbon production using physical activation by water steam from agricultural wastes

Production of activated nano-carbon from agricultural wastes was studied in this work. To obtain the optimum production conditions by a physical activation method, influence of temperature (850, 900, 950 and 1000 °C), activation residence time (30, 60 and 90 min), and mill rotation (200, 300 and 400 rpm) were investigated using three different raw materials including walnut, almond and pistachio shells. To prepare activated nano-carbon, all the samples were heated up to the final activation temperature under a continuous steam flow of 130 cm³ min⁻¹, and at a heating rate of 3 °C min⁻¹, and were held at the different activation temperatures for 30, 60 and 90 minutes. BET surface area of the obtained activated carbons was measured from nitrogen adsorption data in the relative pressure range between 0 to 1. Activated nano-carbon standard indexes were evaluated according to the ASTM standard and the samples were compared. First, the cellulose raw material was heated in the carbonization furnace at 600 °C and then activated in the advanced activation furnace at a temperature between 850 to 1000 °C for 30, 60 and 90 minutes with water vapor. Ash percentage, iodine content, moisture content, specific area, elemental analysis, and FESEM were used for product characterization. The results of the analysis showed that by using the water vapor physical activation method and optimizing the parameters of this process including time and rotation of the mill up to 10 min and 400 rpm, resulted in a significant increase in specific surface area, cavity volume and the iodine number of the final product.

Production of activated nano-carbon from agricultural wastes was studied in this work.

Synthesis and characterization of novel N-methylimidazolium-functionalized KCC-1: A highly efficient anion exchanger of hexavalent chromium

A key challenge in adsorption process of toxic organic and inorganic species is the design and development of adsorbent materials bearing an abundance of accessible adsorption sites with high affinity to achieve both fast adsorption kinetics and elevated adsorption capacity for toxic contaminants. Herein, a novel anion-exchange adsorbent based on fibrous silica nanospheres KCC-1 was synthesized by a facile hydrothermal-assisted post-grafting modification of KCC-1 with 1-methyl-3- (triethoxysilylpropyl)imidazolium chloride for the first time. Silica fibers with micro-mesoporous structure display the proper combination of features to serve as a potential scaffold for decorating adsorption sites to create desired ion-exchange adsorbent. The obtained N-methylimidazolium-functionalized KCC-1 (MI-Cl-KCC-1) with fibrous nanosphere morphology showed a high surface area (∼241 m² g^-1) and high pore volume (0.81 m² g^-1). The adsorption behaviors of toxic hexavalent chromium from aqueous media by the MI-Cl-KCC-1 were systematically studied using the batch method. The adsorption rate was relatively fast, and MI-Cl-KCC-1 possesses a high capacity for the adsorption of Cr(VI). The maximum Cr(VI) adsorption was obtained at pH 3.0-4.0. Different non-linear isotherm equations were tested for choosing an appropriate adorption isotherm behavior, and the adsorption data for MI-Cl-KCC-1 were consistent with the Langmuir model with a maximum adsorption capacity of 428 ± 8 mg g^-1.

Applicability of BaTiO3/graphene oxide (GO) composite for enhanced photodegradation of methylene blue (MB) in synthetic wastewater under UV-vis irradiation

Methylene blue (MB) is a dye pollutant commonly present in textile wastewater. We investigate and critically evaluate the applicability of BaTiO₃/GO composite for photodegradation of MB in synthetic wastewater under UV-vis irradiation. To enhance its performance, the BaTiO₃/GO composite is varied based on the BaTiO₃ weight. To compare and evaluate any changes in their morphologies and crystalline structures before and after treatment, BET (Brunauer-Emmett-Teller), XRD (X-ray diffraction), FTIR (Fourier transform infrared spectroscopy), SEM (scanning electron microscopy) and TEM (transmission electron microscopy) tests are conducted, while the effects of reaction time, pH, dose of photocatalyst and initial MB concentration on its photodegradation by the composite are also investigated under identical conditions. The degradation pathways and removal mechanisms of MB by the BaTiO₃/GO are elaborated. It is evident from this study that the BaTiO₃/GO composite is promising for MB photodegradation through ·OH. Under optimized conditions (0.5 g/L of dose, pH 9.0, and 5 mg/L of MB concentration), the composite with 1:2 dose ratio of BaTiO₃/GO has the highest MB degradation rate (95%) after 3 h of UV vis irradiation. However, its treated effluents still could not comply with the discharge standard limit of less than 0.2 mg/L imposed by national environmental legislation. This suggests that additional biological treatments are still required to deal with the remaining oxidation by-products of MB, still present in the wastewater samples such as 3,7-bis (dimethyl-amino)-10H-phenothiazine 5-oxide.

Design of Controlled Release System for Paracetamol Based on Modified Lignin

The influence of lignin modification on drug release and pH-dependent releasing behavior of oral solid dosage forms was investigated using three different formulations. The first formulation contains microcrystalline cellulose (MCC 101) as the excipient and paracetamol as the active pharmaceutical ingredient (API). The second formulation includes Alcell lignin and MCC 101 as the excipient and paracetamol, and the third formulation consists of carboxylated Alcell lignin, MCC 101 and paracetamol. Direct compaction was carried out in order to prepare the tablets. Lignin can be readily chemically modified due to the existence of different functional groups in its structure. The focus of this investigation is on lignin carboxylation and its influence on paracetamol control release behavior at varying pH. Results suggest that carboxylated lignin tablets had the highest drug release, which is linked to their faster disintegration and lower tablet hardness.

Facile one-pot synthesis of thiol-functionalized mesoporous silica submicrospheres for Tl(I) adsorption: Isotherm, kinetic and thermodynamic studies

For the first time, thiol-modified mesoporous silica submicrospheres (TMS-SMSs) have been applied to remove extremely high toxic Tl(I) ions from aqueous solution by an adsorption approach. TMS-SMSs as a silica-based material is basically environmentally benign, with combined advantages of porosity and functionality. XRD measurement and TEM images clearly exhibited a parallel arrangement of mesopores in TMS-SMSs with a combination of both semi-long-range ordering and wormhole-like motif structures. The batch adsorption of Tl(I) onto TMS-SMSs showed a typical Langmuir adsorption isotherm (among various non-linear isotherm models) with the maximum adsorption capacity of 452.8 mgg^-1. TMS-SMSs show a fast adsorption rate, and pseudo-second-order kinetic model provides the best correlation between experimental data. The thermodynamic constants indicated that the adsorption of Tl(I) ions was an endothermic (ΔH° = 24.80 kJ  mol^-1), entropy driven (ΔS° = 0.161 kJ  mol^-1K^-1), and spontaneous process (ΔG° = 23.15-27.95 kJ mol^-1). This study provides an exciting opportunity to advance our knowledge of functionalized-mesoporous silica submicrospheres as a promising adsorbent for the removal of toxic Tl(I) ions from aqueous solution using adsorption approach.