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Abstract:
This study explores an efficient decontamination strategy using platinum-coated polystyrene rough-particles as a micron-sized catalyst system for decomposing methylene blue (MB), a common organic pollutant. The synthesized nanomaterials were comprehensively characterized using Nanoparticle Tracking Analysis (NTA), Dynamic Light Scattering (DLS), Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM), confirming their morphology, size distribution, and surface properties. The decontamination was performed at the air-water interface through an interface trapping method, with enhanced mixing achieved under a controlled flow environment. The experiments were conducted with a circulation speed of 50 RPM, corresponding to a Reynolds number (NR) of 1686 and a high particle packing fraction of 0.8. Under these operating conditions, complete degradation of MB was achieved within 30 min, significantly faster than the 75 min required for degradation in the bulk phase. The reaction kinetics were analyzed and found to follow the Langmuir–Hinshelwood model, with an estimated rate constant of 0.018 min−1, indicating efficient surface-mediated catalytic activity. Furthermore, an Artificial Neural Network (ANN) model was developed to validate and predict the degradation kinetics, showing a Root Mean Square Error (RMSE) of 5.5 and a high correlation coefficient (R2) of 0.9656, confirming the reliability of the predictive model. This interface-assisted, catalyst-based degradation approach demonstrates a promising, reusable, cost-effective, and environmentally friendly solution for advanced wastewater treatment applications.

Keywords:
Methylene blue, Pt nanoparticles, Air-water interface, Wastewater, ANN modeling, Removal efficiency

Abstract:
This communication presents a comprehensive investigation into the impact of mixing on the synthesis of water-in-water Pickering emulsions. The approach employs commercial-grade oppositely charged nanoparticles within two distinct fluid phases, facilitating self-assembly and the formation of aggregates with variable sizes and compositions. Enhanced interfacial area, achieved through aggregate adsorption at the interface, elevates the Gibbs detachment energy of particles between the two aqueous phases, leading to stable emulsion formation. We further explore the effect of various mixing devices, including high-pressure and sonic wave mixing. Our findings reveal that mixing within the aqueous phase critically influences emulsion size, with sonicator-assisted mixing producing smaller droplets than homogenizer mixing. Both devices yield poly-dispersed droplet size distributions. Interestingly, the droplet size correlates well with the Hinze scale (hd), and the Kolmogorov length scale (ld) exhibits good correspondence within a specific operating range. The proposed method introduces a streamlined, one-step synthesis process for easy preparation, demonstrating excellent stability for a minimum of 30 days. This study pioneers the investigation of mixing effects within an aqueous two-phase system utilizing a Pickering emulsion template.

Abstract:
Nanoplastics pose a significant global environmental concern, as they can accumulate emerging pollutants and enter the food chain, endangering human health and ecosystems. Wastewater treatment plants (WWTPs) have been identified as the primary source of micro and nanoplastic contamination, necessitating the development of effective removal methods. This study investigates the efficacy of electrolysis-assisted flotation (EF) process for removing nanoplastics from synthetic wastewater, using polystyrene-type nanoparticles synthesized from expanded polystyrene waste (EPS) as representative nanoplastic contaminants. Electrolysis experiments were conducted using parallel aluminium electrodes under low-voltage conditions. The study systematically explores the influence of various process parameters, including electrode spacing, salt concentration, nanoplastics concentration, and applied voltage, on the removal efficiency of nanoplastics. The removal efficiency was evaluated using a turbidity meter and dynamic light scattering technique. The derived count rate (DCR) obtained from dynamic light scattering supplements the nephelometric turbidity units (NTU) and provides a reliable estimate of the nanoplastics sample concentration. Under optimized conditions, with a specified electrolyte concentration and pH of 7.2 ± 0.3, the EF process achieved an impressive removal efficiency of nearly 95 % (94 % per DCR). A notable advantage of the proposed method is forming a foamy layer on top of the reactor when nanoplastics and coagulants are mixed, facilitating easy removal by simple scraping. This study provides valuable insights into developing an eco-friendly and sustainable approach for the large-scale removal of nanoplastics. The results contribute to advancing wastewater treatment strategies and addressing the pressing issue of nanoplastic pollution.

Keywords:
Nanoplastics, Polystyrene waste, Electrolysis, Wastewater, Flotation, Removal efficiency