The effect of preparation time and aeration rate on the properties of bulk micro-nanobubble water using hydrodynamic cavitation.

Fundamental research on bulk micro-nanobubbles (BMNBs) has grown rapidly due to the demand for their industrial applications and potential role in interfacial sciences. This work focuses on examining properties of such bubbles, including the number, concentration, zeta potential, and surface tension in water. For this purpose, BMNBs were generated by the hydrodynamic cavitation (HC) mechanism. Distilled water and air in the experiments were the liquid and gas phases, respectively. The characterization of bulk microbubbles (BMBs) and bulk nanobubbles (BNBs) were performed through focused beam reflectance measurement (FBRM) and nanoparticle tracking analysis (NTA) techniques, respectively. Zeta potential and surface tension of aqueous solutions were measured at different time and aeration rates. The results showed that aeration rate and preparation time had an important role in the properties of BNBs (concentration, bubble size, and surface charge) and BMBs (number, and bubble size). The instability of BMBs led to the rapid changes in the dissolved oxygen (DO) content in the water. The number of BMBs decreased when preparation time and aeration rate increased, but their size remained constant. By enhancing the preparation time and aeration rate, the concentration of BNBs improved first and then reduced. Additionally, the surface tension of an aqueous solution containing BNBs was significantly lower than that of pure water.

Effect of ultrasound pre-treatment on carbonaceous copper-bearing shale flotation.

Although numerous studies have been implemented on identifying the impact of acoustic waves on mineral beneficiation, its fundamental aspects remain unclear in the literature. The present work, for the first time, systematically investigates the role of ultrasound pre-treatment (UPT) in the carbonaceous copper-bearing shale flotation. To this end, conditioning was carried out at different powers of applied ultrasound. Non-treated and UPT shale flotation tests were performed in the presence of frother (MIBC) and collector (KEX). To analyse particle surface charge variation and collector adsorption properties after application of UPT, zeta potential and ultraviolet-visible spectroscopy measurements were implemented, respectively. The generation of sub-micron bubbles due to the acoustic cavitation was characterised by laser-based particle size measurements. Shale hydrophobicity was determined using the sessile drop and captive bubble techniques. The micro-flotation results showed that the mass recovery increased by 40% at 20 W of applied ultrasonic power. The positive effect of UPT on the copper-bearing shale flotation was related to: i) generation of ultrafine bubbles due to the acoustic cavitation phenomenon and ii) the cleaning effect through transient bubble collapse. However, rigorous ultra-sonication diminished the recoverability of the sample owing to the less intensified number of ultrafine bubbles on the particle surfaces and formation of free H and OH radicals, which led to the oxidation of particle surfaces. These statements were correlated well with the observations of the zeta potential, particle size analysis and quantified ultrafine bubbles. Finally, we briefly highlighted fundamental knowledge gaps in flotation and ultrasound-related issues for future work.

Pickering emulsion prepared by nano-silica particles - A comparative study for exploring the effect of various mechanical methods.

Pickering emulsions are eco-friendly, stabilized by solid particles, and have an essential role in leading industries. Although Pickering emulations have found several applications, surprisingly few investigations have attempted to explore the effectiveness of various mechanical processes for its production. To fill these gaps, the present investigation comprehensively examined the application of various Pickering emulsion preparation processes such as rotor-stator homogenization emulsification (R-SH), ultrasonic emulsification, and their combined processes by using nano-silica particles. The influences of emulsification time and intensity on emulsion droplets' distribution were analyzed as indicative factors. The kerosene/water nano-silica Pickering emulsion was utilized for all assessments. The obtained results demonstrated that the main distribution peak of the emulsion prepared by R-SH occurred where the chord length was greater than 40 µm. Micro-scale nano-silica-aggregates generated large droplets, while the fine-emulsion fraction was significantly increased after ultrasonic treatment. The experimental results showed that the emulsion prepared only by ultrasound needed substantial power to form a Pickering emulsion since the oil phase was difficult to disperse in the water phase. Finally, it was concluded that preprocessing by R-SH could form a stable and uniform emulsion speedily, which is essential for ultrasound emulsion preparation.

Applying hybrid genetic and artificial bee colony algorithms to simulate a bio-treatment of synthetic dye-polluted wastewater using a rhamnolipid biosurfactant.

The present work aims at optimization and advanced simulation of removal efficiency of dye material from a synthetic wastewater using a locally generated rhamnolipid (RL) biosurfactant. For this purpose, bio-treatment of dye polluted synthetic wastewater was experimentally, kinetically, and statistically investigated by the ion flotation process in the presence of the RL. The removal rate of methylene blue (MB) as the dye material was assessed by the ultraviolet (UV)-visible absorbance measurements. The impact of operating variables including RL concentration (as a dye collector, 5-50 ppm), methyl isobutyl carbinol (MIBC) dosage (as a frother, 10-70 ppm), solution pH (2-12) and aeration rate (1-5 l/min) were assessed through one-way analysis of variance (ANOVA) and Anderson-Darling as the normality analysis strategy. The process was simulated using two artificial neural network (ANN) optimization algorithms, i.e., genetic algorithm (GA) and artificial bee colony (ABC) as a novel approach. The statistical results indicated that the dye removal process was significantly influenced by all operating variables (pvalue<0.05) while their relative intensity followed the order of aeration rate > solution pH > RL concentration > MIBC dosage. Anderson-Darling approach disclosed that the all factors were perfectly followed the normal trend with A2 less than unity and p-value of greater than 0.05 at 95% confidence level. Main effect plots revealed that except MIBC dosage with nonlinear trend, the rest of factors had an ascending influence on the removal efficiency. The process was optimized by interpreting the interaction effect among various variables to reach the maximum dye bioflotation. The maximum removal of 97 ± 0.13% was achieved at pH 12, airflow rate of 5 l/min, MIBC and rhamnolipid concentrations of 30 and 40 ppm, respectively with a flotation kinetic rate of 0.015 sec-1. Finally, the intelligent simulation results showed that the process could be modelled using an artificial bee colony algorithm of 4-7-1 structure with 99% and 98.8% accuracies in the training and testing steps, respectively. Further, we found that the artificial bee colony algorithm was superior to the genetic algorithm in terms of complexity analysis.

Advanced Simulation of Removing Chromium from a Synthetic Wastewater by Rhamnolipidic Bioflotation Using Hybrid Neural Networks with Metaheuristic Algorithms.

This work aims at presenting an advanced simulation approach for a novel rhamnolipidic-based bioflotation process to remove chromium from wastewater. For this purpose, the significance of key influential operating variables including initial solution pH (2, 4, 6, 8, 10 and 12), rhamnolipid to chromium ratio (RL:Cr = 0.010, 0.025, 0.050, 0.075 and 0.100), reductant (Fe) to chromium ratio (Fe:Cr of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0), and air flowrate (50, 100, 150, 200 and 250 mL/min) were investigated and evaluated using Analysis of Variance (ANOVA) method. The RL as both collector and frother was produced using a pure strain of Pseudomonas aeruginosa MA01 under specific conditions. The bioflotation tests were carried out within a bubbly regimed column cell with the dimensions of 60 × 5.70 × 0.1 cm. Four optimization techniques based on Artificial Neural Network (ANN) including Cuckoo, genetic, firefly and biogeography-based optimization algorithms were applied to 113 experiments to identify the optimum values of studied factors. The ANOVA results revealed that all four variables influence the bioflotation performance through a non-linear trend. Their influences, except for aeration rate, were found statistically significant (p-value < 0.05), and all parameters followed the normal distribution according to Anderson-Darlin (AD) criterion. Maximum chromium removal of about 98% was achieved at pH of 6, rhamnolipid to chromium ratio of 0.05, air flowrate of 150 mL/min, and Fe to Cr ratio of 1.0. Flotation kinetics study indicated that chromium bioflotation follows the first-order kinetic model with a rate of 0.023 sec-1. According to the statistical assessment of the model accuracy, the firefly algorithm (FFA) with a structure of 4-9-1 yielded the highest level of reliability with the mean squared, root mean squared, percentage errors and correlation coefficient values of test-data of 0.0038, 0.0617, 3.08% and 96.92%, respectively. These values were evidences of the consistency of the well-structured ANN method to simulate the process.

Paper based immunosensing of ovarian cancer tumor protein CA 125 using novel nano-ink: A new platform for efficient diagnosis of cancer and biomedical analysis using microfluidic paper-based analytical devices (µPAD).

Ovarian cancer is the first and most important cause of malignancy death in women. Mucin 16 or MUC16 protein also known as carcinoma antigen 125 (CA 125) is the most commonly used glycoprotein for early stage diagnosis of ovarian cancer. In this work, a novel paper-based bio-device through hand writing of Ag/RGO (silver nanoparticles/reduced graphene oxide) nano-ink on the flexible paper substrate using pen-on-paper technology was developed. The prepared interface was used to the recognition of CA 125 protein in human biofluid. For this purpose, Ag/rGO nano-ink was synthesized by deposition of Ag nanoparticles onto graphene oxide sheets and the reduction of graphene oxide to rGO simultaneously. Conductivity and resistance of conductive lines were studied after drawing on photographic paper. Subsequently, to prepare a new and unique immuno-device, paper electrode modified by cysteamine caped gold nanoparticles (CysA/Au NPs) using electrochemical techniques. CysA is bonded by sulfur atoms with Au (CysA/Au NPs), and from the amine group with hydroxyl and carboxyl groups of Ag/RGO nano-ink deposited on the surface of paper-based electrodes (CysA/Au NPs/Ag-rGO). Then, anti-CA 125 antibody was immobilized on the electrode surface through Au NPs and CA 125 positively charged amine groups interaction. Atomic force microscopy, Transmission electron microscopy, Field emission scanning electron microscopy, and dynamic light scattering, were performed to identify the engineered immunosensor. Using chronoamperometry technique and under the optimized conditions, the low limit of quantitation (LLOQ) for the proposed immunoassay was recorded as 0.78 U/ml, which this evaluation was performed at highly linear range of 0.78-400 U/ml. The high sensitivity of the electrochemical immunosensor device is indicative of the ability of this immuno-device to detect early stages ovarian cancer.

Immunosensing of breast cancer tumor protein CA 15-3 (carbohydrate antigen 15.3) using a novel nano-bioink: A new platform for screening of proteins in human biofluids by pen-on-paper technology.

Early stage diagnosis of breast cancer by monitoring the proteins in human biological fluids is the best method and the first section toward efficient therapy, delaying metastasis and hindrance mortality. In this study, graphite ink was synthesized and combined with CA 15-3 antibody in order to develop a novel immunosensor for detection of CA 15-3, breast cancer biomarker. Conductivity of bioink was examined by designing various conductive patterns on paper using a rollerball pen. Electrochemical behavior of engineered immunosensor was evaluated through employing sensitive diagnostic technique, DPV (differential pulse voltammetry). Under optimal conditions, the linear concentration range and low limit of quantification (LLOQ) of designed immunosensor was 15-250 U/mL and 15 U/mL, respectively. The process was successfully applied to assay of breast cancer biomarker (CA15-3) in unprocessed human plasma specimens.