WO3/Ag/ZnO S-scheme heterostructure thin film spinning disc photoreactor for intensified photodegradation of cephalexin antibiotic.

The presence of antibiotics in wastes and drinking water has led to serious environmental and health concerns, further necessitating the development of an advanced sustainable strategy to eliminate antibiotics from aquatic media. In this context, the present research reports the successful fabrication of a spinning disc photoreactor (SDPR) supported ZnO/Ag/WO3 S-scheme visible-light-driven thin-film photocatalyst to study the degradation of cephalexin (CPX) as a target pollutant under blue light irradiation. The optical, electrochemical and physicochemical characterization of the as-prepared thin-film samples were carried out by XRD, top-view FE-SEM, EDS-mapping, UV-Vis-DRS, contact angle, EIS, transient photocurrent, mott Schottky and AFM techniques. The rod shape morphology of the samples with moderate surface roughness, desirable hydrophobicity, low bandgap and remarkable band structure alignment confirmed the applicability of as-prepared thin-film with an average photon flux of 1.94 × 10-4-8.61 × 10-5 E's m-2 s-1. The use of a rotating catalytic disc impressively declined the photon propagation distance, decremented the probability of light absorption by the solution, and intensified the mass transfer rate. The maximum throughputs of 98.8% efficiencies for CPX degradation were achieved at a rotational speed of 180 rpm, the solution flow rate of 1.0 L min-1, the light intensity of 11 mW cm-2, and initial CPX concentration of 40 mg L-1, illumination time of 80 min, and pH of 6. Damkohler number (Da) value was found to be 1.23 × 10-2 at the optimum conditions, indicating the negligibility of the external mass transfer resistance in the SDPR. The photocatalytic mechanism was elucidated for finding the most operative radical species, suggesting the crucial role of ·O2- in photodegradation of CPX and a drastic improvement of the charge separation by S-scheme heterostructure and facilitation by Ag mediator. Findings indicated that the developed reusable and robust SDPR benefited from an s-scheme photocatalyst can be a promising technology for degradation of the organic compounds.

Spinning disc photoreactor based visible-light-driven Ag/Ag2O/TiO2 heterojunction photocatalyst film toward the degradation of amoxicillin.

The presence of antibiotics in waste and drinking water is causing increasing concern around the world, thereby an advanced sustainable technology needs to be developed to eliminate the antibiotics from water resources. Hence, an efficient spinning disc photoreactor (SDPR) equipped with visible light-activated Ag/Ag2O/TiO2 heterostructure thin film photocatalyst was assessed for the degradation of amoxicillin (AMX) as a typical antibiotic. The surface morphology, optoelectronic and structural features of Ag/Ag2O/TiO2 heterojunction were characterized by TEM, BET, mott Schottky, FESEM, EDS, AFM, XRD, UV-Vis-DRS, and contact angle measurements. Results confirm that Ag and Ag2O have a significant effect on the photocharge carrier separation and transfer of the as-developed photocatalyst system. The operative variables including illumination time, rotational speed, solution flow rate, aeration rate, pH, and initial AMX concentration were optimized by CCD. The results displayed the maximum AMX photodegradation (97.91%) could be achieved at optimal conditions involving illumination time of 80 min, a rotational speed of 225 rpm, the solution flow rate of 0.6 L/min, aeration rate of 20 L/min, pH = 6, and initial AMX concentration of 20 mg/L. Interestingly, more than 79% COD and 64% TOC were removed under optimum conditions during 80 min illumination time, respectively. Active species tests confirmed the dominant role of ·OH and ·O2- in AMX degradation. finally, the XRD pattern confirmed that the reusability assessments of the heterojunction film could successfully retain its stability for six consecutive photocatalytic degradation runs. This work demonstrates the feasibility of utilizing visible-light-driven thin-film photocatalysts in spinning disc photoreactors in treating the tenacious antibiotic pollutants.

Highly selective MXene/V2O5/CuWO4-based ultra-sensitive room temperature ammonia sensor.

A Schottky junction based on Ti3C2Tx MXene sheet integrated with marigold flower-like V2O5/CuWO4 heterojunction was designed and fabricated for robust ammonia sensing by monitoring the electrical resistance changes in air and ammonia. The electron transport behavior of the sensor was investigated by electrochemical analysis, ultraviolet photoelectron spectroscopy and reflection electron energy loss spectroscopy. Besides, negative zeta potential obtained for sensor components was in consistent with surface functional groups (e.g. OH and F) observed by XPS analysis helping better understanding of the ammonia sensing mechanism. The results desirably confirmed high sensitivity, selectivity, linear range (1-160 ppm), the limit of quantification, repeatability, long-term stability, very short response time (few seconds) and low working temperature (25 °C) of the sensor. The measurements on the resistance changes of the MXene/V2O5/CuWO4-based sensor under the exposure to various types of analytes (Ammonia, Acetone, Benzene, Chloroform, DMF, Ethanol, humidity (80%), Methanol and Toluene as well as NO, NO2, H2S, SO2, CO and CH4) at different concentrations revealed that the fabricated sensor is excellently selective to ammonia with ultra-high sensitivity. Intra-day stability (7 runs a day) and long-term stability (every 10 days over 70 days) as important sensor characteristics were investigated at 51 ppm and ambient temperature, which showed very good repeatability and recoverability in both short and long periods for sensing the ammonia. Overall, MXene/V2O5/CuWO4 was shown to be cost-effective, easy to handle and suitably applicable for simple, ultrafast and extremely efficient trace ammonia detection, which could be of high interest for future exhaled breath analysis and the development of a novel noninvasive diagnostic strategy to monitor chronic kidney disease to stop a large measure of unnecessary invasive testing.

Robust charge carrier by Fe3O4 in Fe3O4/WO3 core-shell photocatalyst loaded on UiO-66(Ti) for urea photo-oxidation.

In this study, a facile four-step hydrothermal method was utilized to deposit a core-shell structure on UiO-66(Zr/Ti) nanoflake (NFs) as a visible-light-driven photocatalyst. The core was magnetic Fe3O4 which served as a charge carrier coated with WO3 shell. The as-prepared photocatalyst was characterized by XRD, VSM, BET, FTIR, FE-SEM, UV-Vis-DRS, and PL techniques which proved successful deposition of Fe3O4@WO3 core/shell particle on UiO-66(Zr/Ti)-NFs. The obtained photocatalyst was subsequently applied for urea photo-oxidation. This magnetically recoverable photocatalyst exhibited superior activity due to its desirable band alignment, high stability, and generation of the photo-induced charge carriers, as well as providing a high surface area with low mass transfer resistance. Fe3O4 core acted as charge-carrier to transport the photogenerated charges of UiO-66(Zr/Ti)-NFs (electron-donor) to WO3 charge-collectors for effective photoconversion. The central composite design was applied to design the experiments matrix in which flow rate, pH, irradiation time, catalyst mass, and initial urea concentration were considered as operational factors. The optimized condition was found by defining the desirability function. 90% degradation percentage was achieved at 550 mL/min solution flowrate, pH = 7, 120 min irradiation time, 0.22 g UiO-66(Zr)-NFs-Fe3O4@WO3, and 40 mg/L of the initial concentration of urea with the desirability value of 0.89. Such a superior photocatalytic activity of UiO-66-Fe3O4@WO3 can be ascribed to the reclamation of Fe3O4 as a low bandgap carrier, which accelerated the conveyance of electrons and followed surpassing charge separation. Our present findings open a new strategy to produce a wide range of core-shell heterogeneous catalysts to be applied in photoreactors scale-up.

UiO-66(Ti)-Fe3O4-WO3 photocatalyst for efficient ammonia degradation from wastewater into continuous flow-loop thin film slurry flat-plate photoreactor.

This work presents the characterization of novel synthesized UiO-66(Ti)-Fe3O4-WO3 magnetic photocatalyst and investigates their photocatalytic activity for the photodegradation of ammonia in a designed continuous flow-loop thin-film slurry flat-plate photoreactor (TFSR). Excellent ammonia degradation efficiency was achieved in the presence of the synthesized catalyst at ambient conditions using no more reactive oxidant species. Several independent variables involving catalyst mass, flowrate, pH, irradiation time and initial ammonia concentration as well as corresponding experiments were analyzed and design using the central composite design (CCD). The influence and significance of each parameter and their binary interactions were then evaluated by applying the analysis of variance. The ammonia degradation efficiency of 91.80 % with the desirability of 0.903 were obtained at optimum values of operational parameters including 550 mL/min,10, 0.125 g/L, 60 min and 30 mg/L for solution flowrate, pH, catalyst mass, irradiation time and initial ammonia concentration, respectively. Furthermore, the liquid phase products of ammonia degradation such as nitrate and nitrite ions were completely removed, and purified water was produced using the combination of reverse osmosis process and mixed resins beds. The photocatalyst mechanism study revealed that [Formula: see text] was the predominant reactive oxygen species in the ammonia photodegradation.

Natural Source-Based Graphene as Sensitising Agents for Air Quality Monitoring.

Natural carbon powder has been used as a precursor to prepare two main types of sensitising agents of nitrogen-doped carbon nanoparticles (N-CNPs) and nitrogen-doped graphene quantum dots coupled to nanosheets (N-GQDs-NSs) by using simple treatments of chemical oxidation and centrifugation separation. Characterization based on FTIR, XPS, XRD, Raman spectroscopy, FE-SEM, HR-TEM, AFM, UV-Vis and FL, revealed successful doping carbon nanoparticle with nitrogen with an average plane dimension of 50 nm and relatively smooth surface. The versatility of the prepared samples as sensitising agents was developed and established by exploiting its ability for detection of volatile organic compounds via simple optical fibre based sensing configuration. The comparative experimental studies on the proposed sensor performance indicate fast response achieved at a few tens of seconds and excellent repeatability in exposure to the methanol vapour. The low limit of detection of 4.3, 4.9 and 10.5 ppm was obtained in exposure to the methanol, ethanol and propanol vapours, respectively, in the atmosphere condition. This study gives insights into the chemical/physical mechanism of an enhanced economic optical fibre based gas sensor and illustrates it for diverse sensing applications, especially for chemical vapour remote detection and future air quality monitoring.

Carbon dots as absorbance promoter probes for detection of Cu(ii) ions in aqueous solution: central composite design approach.

In this work, the use of carbon dots (CDs) as a complexing agent and sensitizer in a polymeric matrix for determination of copper(ii) by UV-vis spectroscopy is reported for the first time. A new and highly selective Schiff base, namely, (N',N'''E,N',N'''E)-N',N'''-((((2-hydroxypropane-1,3-diyl)bis(oxy))bis(2,1-phenylene))bis(methan-ylylidene))di(isonicotinohydrazide) (NHBMDI), was also incorporated in the polymeric matrix. For the first time, the membrane composition of the proposed optical sensor including NHBMDI as the ionophore, tetraphenylborate (NaTPB) as the anionic additive, dibutyl phthalate (DBP) as the plasticizer and polyvinyl chloride (PVC) as the immobilizer was optimized through central composite design combined with the desirability function approach (DFA) because this method saves material and time consumption and is therefore cost effective. The synthesized CDs were characterized by transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The fluorescence quantum yield of the synthesized CDs was found to be 6.4% by using quinine sulfate as the reference. The characterization of the prepared membrane sensor was investigated by field emission scanning electron microscope (FE-SEM) and atomic force microscopy (AFM).The response of the optode was based on the strong absorbance of NHBMDI and CDs upon exposure to Cu(ii) ions with the maximum wavelength at 371 nm. The proposed sensor exhibited a linear response in the concentration range of 1.2 × 10-6-4.56 × 10-5 mol L-1 with a detection limit of 7.1 × 10-7 mol L-1, which is lower than U.S. Environmental Protection Agency's defined limit (20 µM). Furthermore, the proposed optode displayed good selectivity toward Cu(ii) ions in comparison with common coexisting cations with satisfactory repeatability and reproducibility. The sensor was applied successfully for determination of copper(ii) ions in water samples.

Application of random forest, radial basis function neural networks and central composite design for modeling and/or optimization of the ultrasonic assisted adsorption of brilliant green on ZnS-NP-AC.

Two machine learning approach (i.e. Radial Basis Function Neural Network (RBF-NN) and Random Forest (RF) was developed and evaluated against a quadratic response surface model to predict the maximum removal efficiency of brilliant green (BG) from aqueous media in relation to BG concentration (4-20mgL-1), sonication time (2-6min) and ZnS-NP-AC mass (0.010-0.030g) by ultrasound-assisted. All three (i.e. RBF network, RF and polynomial) model were compared against the experimental data using four statistical indices namely, coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE) and absolute average deviation (AAD). Graphical plots were also used for model comparison. The obtained results using RBF network and RF exhibit a better performance in comparison to classical statistical model for both dyes. The significant factors were optimized using desirability function approach (DFA) combined central composite design (CCD) and genetic algorithm (GA) approach. The obtained optimal point was located in the valid region and the experimental confirmation tests were conducted showing a good accordance between the predicted optimal points and the experimental data. The properties of ZnS-NPs-AC were identified by X-ray diffraction; field emission scanning electron microscopy, energy dispersive X-ray spectroscopy (EDS) and Fourier transformation infrared spectroscopy. Various isotherm models for fitting the experimental equilibrium data were studied and Langmuir model was chosen as an efficient model. Various kinetic models for analysis of experimental adsorption data were studied and pseudo second order model was chosen as an efficient model. Moreover, ZnS nanoparticles loaded on activated carbon efficiently were regenerated using methanol and after five cycles the removal percentage do not change significantly.

Application of machine/statistical learning, artificial intelligence and statistical experimental design for the modeling and optimization of methylene blue and Cd(ii) removal from a binary aqueous solution by natural walnut carbon.

Analytical chemists apply statistical methods for both the validation and prediction of proposed models. Methods are required that are adequate for finding the typical features of a dataset, such as nonlinearities and interactions. Boosted regression trees (BRTs), as an ensemble technique, are fundamentally different to other conventional techniques, with the aim to fit a single parsimonious model. In this work, BRT, artificial neural network (ANN) and response surface methodology (RSM) models have been used for the optimization and/or modeling of the stirring time (min), pH, adsorbent mass (mg) and concentrations of MB and Cd2+ ions (mg L-1) in order to develop respective predictive equations for simulation of the efficiency of MB and Cd2+ adsorption based on the experimental data set. Activated carbon, as an adsorbent, was synthesized from walnut wood waste which is abundant, non-toxic, cheap and locally available. This adsorbent was characterized using different techniques such as FT-IR, BET, SEM, point of zero charge (pHpzc) and also the determination of oxygen containing functional groups. The influence of various parameters (i.e. pH, stirring time, adsorbent mass and concentrations of MB and Cd2+ ions) on the percentage removal was calculated by investigation of sensitive function, variable importance rankings (BRT) and analysis of variance (RSM). Furthermore, a central composite design (CCD) combined with a desirability function approach (DFA) as a global optimization technique was used for the simultaneous optimization of the effective parameters. The applicability of the BRT, ANN and RSM models for the description of experimental data was examined using four statistical criteria (absolute average deviation (AAD), mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R2)). All three models demonstrated good predictions in this study. The BRT model was more precise compared to the other models and this showed that BRT could be a powerful tool for the modeling and optimizing of removal of MB and Cd(ii). Sensitivity analysis (calculated from the weight of neurons in ANN) confirmed that the adsorbent mass and pH were the essential factors affecting the removal of MB and Cd(ii), with relative importances of 28.82% and 38.34%, respectively. A good agreement (R2 > 0.960) between the predicted and experimental values was obtained. Maximum removal (R% > 99) was achieved at an initial dye concentration of 15 mg L-1, a Cd2+ concentration of 20 mg L-1, a pH of 5.2, an adsorbent mass of 0.55 g and a time of 35 min.

Nano-sized molecularly imprinted polymer for selective ultrasound-assisted microextraction of pesticide Carbaryl from water samples: Spectrophotometric determination.

Ultrasound-assisted dispersive solid phase microextraction followed by UV-Vis spectrophotometry (UA-DSPME UV-Vis) was designed for the extraction and preconcentration of Carbaryl using nano-sized molecularly-imprinted polymer (MIP-NP). Nano-sized Carbaryl-imprinted polymer was characterized by scanning electron microscopy. A preliminary Plackett-Burman design was applied for screening. Subsequently, central composite design under response surface methodology was used to investigate and model the Carbaryl adsorption as response as well as to optimize this response versus variables such as Carbaryl MIP-NP mass, sonication time, temperature, eluent volume, pH and vortex time. At optimum experimental conditions, UAMSPE-UV-Vis exhibited a linear range of 0.1-1.2mgL-1. The enhancement and preconcentration factors were obtained to be 30.6 and 25.0, respectively, for the extraction of Carbaryl by MIP-NP. In addition, the values of 0.033 and 0.11mgL-1 were obtained for limit of detection and limit of quantification, respectively. The value of 4.3% determined for relative standard deviation for the separation and preconcentration of Carbaryl after 5 repetitions shows the acceptable repeatability of the process. Finally, the developed method was successfully applied for the determination of Carbaryl in water samples.

H2S adsorption onto Cu-Zn-Ni nanoparticles loaded activated carbon and Ni-Co nanoparticles loaded γ-Al2O3: Optimization and adsorption isotherms.

The nanocomposites based on copper, zinc and nickel were loaded on activated carbon (Cu-Zn-Ni-NPs-AC) and cobalt and nickel nanoparticles was loaded on γ-alumina (Ni-Co-NPs-γAl2O3) and applied for removal of hydrogen sulfide (H2S) from natural gas and their efficiency were compared. Cu-Zn-Ni/AC and Ni-Co/γ-Al2O3 was characterized using different techniques such as energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD) and field emission scanning electron microscopy (FE-SEM). The effects of variables such as amount of adsorbent, flow rate, temperature, pressure and volume of gas on H2S removal were examined and optimum values were found to be 0.3g adsorbent, and flow rate of 0.15L/min and 15°C and 7Psi for both adsorbent and also 5.5 and 6.5L of sample by Cu-Zn-Ni/C and Co-Ni/γ-Al2O3, respectively. Setting conditions at the above optimum conditions lead to achievement of maximum removal of H2S (94% and 91.6%) by Cu-Zn-Ni/AC and Co-Ni/γ-Al2O3. The negative value of ΔG° and its numerical value confirm physisorption nature of adsorption. The experimental equilibrium data with high efficiency were explained and represented by Langmuir model for both adsorbents with the highest correlation coefficients.

Simultaneous removing of Pb2+ ions and alizarin red S dye after their complexation by ultrasonic waves coupled adsorption process: Spectrophotometry detection and optimization study.

Funthenalized chitosan (CS) was composited with mesoprous SBA-15 and characterized via. different techniques such as FT-IR and FE-SEM. Subsequently, this new material was applied for simulations ultrasound-assisted adsorption of Pb2+ ion and alizarin red S (ARS) dye after their complexation. Efficient conventional variables in adsorption process such as initial ARS and Pb2+ concentration, adsorbent mass and sonication time were studied by small central composite design (CCD) and optimized with desirability function approach. Lack of fit testes and model summary statistics for linear, 2FI, quadratic and cubic models were investigated and according to the insignificant lack of fit and maximizing the R-squared (R2), adjusted R-squared and the predicted R-squared quadratic model was selected for other step analysis for removal of ARS dye, while, for Pb2+ ions 2FI model was selected as best model. Quadratic model ANOVA for ARS dye removal shows the F-value parameter (683.91), very low p-value model (<0.0001) and p-value lack of fit (0.0568) that implied this model was highly significant. Also, 2FI model ANOVA for Pb2+ ions removal shows the F-value parameter (282.51), very low p-value model (<0.0001) and p-value lack of fit (2.05). According to desirability function approach maximum removal percentage of ARS (87.61%) and Pb2+ ions (83.54%) was shown at optimum of condition that were set as at: 25 and 25mgL-1, 0.028g and 11.8min for initial ARS and Pb2+ ions concentration, adsorbent mass and sonication time, respectively. Finally, it was found that the equilibrium and kinetic of adsorption process follow the Langmuir isotherm and pseudo-second-order kinetic model, respectively. From the Langmuir isotherm, maximum monolayer capacity (qmax) was obtained 50.25 and 57.14mgg-1 for ARS and Pb2+ ions removal, respectively.

Central composite design and genetic algorithm applied for the optimization of ultrasonic-assisted removal of malachite green by ZnO Nanorod-loaded activated carbon.

Maximum malachite green (MG) adsorption onto ZnO Nanorod-loaded activated carbon (ZnO-NR-AC) was achieved following the optimization of conditions, while the mass transfer was accelerated by ultrasonic. The central composite design (CCD) and genetic algorithm (GA) were used to estimate the effect of individual variables and their mutual interactions on the MG adsorption as response and to optimize the adsorption process. The ZnO-NR-AC surface morphology and its properties were identified via FESEM, XRD and FTIR. The adsorption equilibrium isotherm and kinetic models investigation revealed the well fit of the experimental data to Langmuir isotherm and pseudo-second-order kinetic model, respectively. It was shown that a small amount of ZnO-NR-AC (with adsorption capacity of 20mgg(-1)) is sufficient for the rapid removal of high amount of MG dye in short time (3.99min).

Sonochemical assisted hydrothermal synthesis of ZnO: Cr nanoparticles loaded activated carbon for simultaneous ultrasound-assisted adsorption of ternary toxic organic dye: Derivative spectrophotometric, optimization, kinetic and isotherm study.

Chromium doped zinc oxide nanoparticles (ZnO: Cr-NPs) was synthesized by ultrasonically assisted hydrothermal method and characterized by FE-SEM, XRD and TEM analysis. Subsequently, this composite ultrasonically assisted was deposited on activated carbon (ZnO: Cr-NPs-AC) and used for simultaneous ultrasound-assisted removal of three toxic organic dye namely of malachite green (MG), eosin yellow (EY) and Auramine O (AO). Dyes spectra overlap in mixture (major problem for simultaneous investigation) of this systems was extensively resolved by derivative spectrophotometric method. The magnitude of variables like initial dyes concentration, adsorbent mass and sonication time influence on dyes removal was optimized using small central composite design (CCD) combined with desirability function (DF) approach, while pH was studied by one-a-time approach. The maximized removal percentages at desirability of 0.9740 was set as follow: pH 6.0, 0.019g ZnO: Cr-NPs-AC, 3.9min sonication at 4.5, 4.8 and 4.7mgL(-1) of MG, EY and AO, respectively. Above optimized points lead to achievement of removal percentage of 98.36%, 97.24%, and 99.26% correspond to MG, EY and AO, respectively. ANOVA for each dyes based p-value less than (<0.0001) suggest highly efficiency of CCD model for prediction of data concern to simultaneous removal of these dyes within 95% confidence interval, while their F-value for MG, EY and AO is 935, 800.2, and 551.3, respectively, that confirm low participation of this them in signal. The value of multiple correlation coefficient R(2), adjusted and predicted R(2) for simultaneous removal of MG is 0.9982, 0.9972 and 0.9940, EY is 0.9979, 0.9967 and 0.9930 and for AO is 0.9970, 0.9952 and 0.9939. The adsorption rate well fitted by pseudo second-order and Langmuir model via high, economic and profitable adsorption capacity of 214.0, 189.7 and 211.6mgg(-1) for MG, EY and AO, respectively.

Sonophotocatalytic degradation of trypan blue and vesuvine dyes in the presence of blue light active photocatalyst of Ag3PO4/Bi2S3-HKUST-1-MOF: Central composite optimization and synergistic effect study.

An efficient simultaneous sonophotocatalytic degradation of trypan blue (TB) and vesuvine (VS) using Ag3PO4/Bi2S3-HKUST-1-MOF as a novel visible light active photocatalyst was carried out successfully in a continuous flow-loop reactor equipped to blue LED light. Ag3PO4/Bi2S3-HKUST-1-MOF with activation ability under blue light illumination was synthesized and characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), photoluminescence (PL) and diffuse reflectance spectra (DRS). The effect of operational parameters such as the initial TB and VS concentration (5-45mg/L), flow rate (30-110mL/min), irradiation and sonication time (10-30min), pH (3-11) and photocatalyst dosage (0.15-0.35g/L) has been investigated and optimized using central composite design (CCD) combined with desirability function (DF). Maximum sonophotodegradation percentage (98.44% and 99.36% for TB and VS, respectively) was found at optimum condition set as: 25mg/L of each dye, 70mL/min of solution flow rate, 25min of irradiation and sonication time, pH 6 and 0.25g/L of photocatalyst dosage. At optimum conditions, synergistic index value was obtained 2.53 that indicated the hybrid systems including ultrasound irradiation and photocatalysis have higher efficiency compared with sum of the individual processes.

A hybrid model of support vector regression with genetic algorithm for forecasting adsorption of malachite green onto multi-walled carbon nanotubes: central composite design optimization.

The aim of this work is the study of the predictive ability of a hybrid model of support vector regression with genetic algorithm optimization (GA-SVR) for the adsorption of malachite green (MG) onto multi-walled carbon nanotubes (MWCNTs). Various factors were investigated by central composite design and optimum conditions was set as: pH 8, 0.018 g MWCNTs, 8 mg L(-1) dye mixed with 50 mL solution thoroughly for 10 min. The Langmuir, Freundlich, Temkin and D-R isothermal models are applied to fitting the experimental data, and the data was well explained by the Langmuir model with a maximum adsorption capacity of 62.11-80.64 mg g(-1) in a short time at 25 °C. Kinetic studies at various adsorbent dosages and the initial MG concentration show that maximum MG removal was achieved within 10 min of the start of every experiment under most conditions. The adsorption obeys the pseudo-second-order rate equation in addition to the intraparticle diffusion model. The optimal parameters (C of 0.2509, σ(2) of 0.1288 and ε of 0.2018) for the SVR model were obtained based on the GA. For the testing data set, MSE values of 0.0034 and the coefficient of determination (R(2)) values of 0.9195 were achieved.

Novel nanorose-like Ce(III)-doped and undoped Cu(II)-biphenyl-4,4-dicarboxylic acid (Cu(II)-BPDCA) MOSs as visible light photocatalysts: synthesis, characterization, photodegradation of toxic dyes and optimization.

A novel nanorose-like metal organic system (MOS) based on Cu(II) and biphenyl-4,4-dicarboxylic acid (Cu-BPDCA) was hydrothermally synthesized and characterized via EDS, FE-SEM, XRD, DRS and FT-IR analysis. This novel nanomaterial was found to be of narrow energy band gap (1.24 eV) and thus it was applied as a photocatalyst driven by visible light for the degradation of the rose bengal (RB) and eosin Y (EY) dyes. For further improvement in the photocatalytic performance of Cu-BPDCA, it was doped with a trace amount of Ce(III) in a simple way followed by characterization. The achieved improvement is due to the formation of a large number of O2⁻˙ and ˙OH radicals compared to the case of undoped Cu-BPDCA. The influence of important variables such as initial dye concentration, photocatalyst dosage and time of irradiation on the photocatalytic degradation efficiency was studied and optimized using central composite design. The optimum condition for the photodegradation of RB was found to be 40 min, 4.0 mg L(-1) and 0.015 g, corresponding to the irradiation time, RB concentration and photocatalyst mass, respectively. The photodegradation of EY was optimized at 4.0, 76 min, 5.9 mg L(-1) and 0.015 g corresponding to the pH, irradiation time, EY concentration and photocatalyst mass, respectively. At these optimum conditions, the photocatalytic degradation percentages of RB and EY with a desirability of 0.95 and 1.0 were found to be 78.90% and 67.63%, respectively. Kinetics study showed that the Langmuir-Hinshelwood kinetics model suitably fits the experimental data. From the Langmuir-Hinshelwood kinetics model, a significantly high photodegradation to surface adsorption ratio was obtained which is the great advantage of this work in addition to applying visible light.

Ultrasonically assisted hydrothermal synthesis of activated carbon-HKUST-1-MOF hybrid for efficient simultaneous ultrasound-assisted removal of ternary organic dyes and antibacterial investigation: Taguchi optimization.

Activated carbon (AC) composite with HKUST-1 metal organic framework (AC-HKUST-1 MOF) was prepared by ultrasonically assisted hydrothermal method and characterized by FTIR, SEM and XRD analysis and laterally was applied for the simultaneous ultrasound-assisted removal of crystal violet (CV), disulfine blue (DSB) and quinoline yellow (QY) dyes in their ternary solution. In addition, this material, was screened in vitro for their antibacterial actively against Methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa (PAO1) bacteria. In dyes removal process, the effects of important variables such as initial concentration of dyes, adsorbent mass, pH and sonication time on adsorption process optimized by Taguchi approach. Optimum values of 4, 0.02 g, 4 min, 10 mg L(-1) were obtained for pH, AC-HKUST-1 MOF mass, sonication time and the concentration of each dye, respectively. At the optimized condition, the removal percentages of CV, DSB and QY were found to be 99.76%, 91.10%, and 90.75%, respectively, with desirability of 0.989. Kinetics of adsorption processes follow pseudo-second-order model. The Langmuir model as best method with high applicability for representation of experimental data, while maximum mono layer adsorption capacity for CV, DSB and QY on AC-HKUST-1 estimated to be 133.33, 129.87 and 65.37 mg g(-1) which significantly were higher than HKUST-1 as sole material with Qm to equate 59.45, 57.14 and 38.80 mg g(-1), respectively.

Metabolism plays the key roles in Th cells differentiation.

The increasing rate of autoimmunity in recent decades cannot be related to only genetic instabilities and disorders. Diet can directly influence our health. Studies have shown that there is a relationship between nutritional elements and alteration in the immune system. Among immune cells, the function of T lymphocyte is important in directing immune response. T CD4+ cells lead other immune cells to respond to pathogens by secreting cytokines. HIV+ patients, who have largely lost their T CD4+ cells, are susceptible to opportunistic infections, which do not normally affect healthy people. It seems that the metabolism of T cells is critical for their differentiation and their consequent functions. After activation, T cells need to undergo clonal expansion, which is a high energy- consuming process. Studies have shown that specific metabolites deprivation or their excess supply affects T CD4+cells subsets differentiation. Abnormal induction of subsets of T CD4+ cells causes some autoimmunity reactions and hyper-sensitivity as well, which may result from imbalance of diet uptake. In this mini-review, we describe the findings about fatty acids, glucose, amino acids, and vitamins, which are effective in determining the fates of T CD4+ cells. These findings may help us uncover the role of diet in autoimmune diseases.

Application of least squares support vector regression and linear multiple regression for modeling removal of methyl orange onto tin oxide nanoparticles loaded on activated carbon and activated carbon prepared from Pistacia atlantica wood.

Two novel and eco friendly adsorbents namely tin oxide nanoparticles loaded on activated carbon (SnO2-NP-AC) and activated carbon prepared from wood tree Pistacia atlantica (AC-PAW) were used for the rapid removal and fast adsorption of methyl orange (MO) from the aqueous phase. The dependency of MO removal with various adsorption influential parameters was well modeled and optimized using multiple linear regressions (MLR) and least squares support vector regression (LSSVR). The optimal parameters for the LSSVR model were found based on γ value of 0.76 and σ(2) of 0.15. For testing the data set, the mean square error (MSE) values of 0.0010 and the coefficient of determination (R(2)) values of 0.976 were obtained for LSSVR model, and the MSE value of 0.0037 and the R(2) value of 0.897 were obtained for the MLR model. The adsorption equilibrium and kinetic data was found to be well fitted and in good agreement with Langmuir isotherm model and second-order equation and intra-particle diffusion models respectively. The small amount of the proposed SnO2-NP-AC and AC-PAW (0.015 g and 0.08 g) is applicable for successful rapid removal of methyl orange (>95%). The maximum adsorption capacity for SnO2-NP-AC and AC-PAW was 250 mg g(-1) and 125 mg g(-1) respectively.