Titanium-Pillared Clay: Preparation Optimization, Characterization, and Artificial Neural Network Modeling.

Titanium-pillared clay (Ti-PILC), as one of the most suitable types of porous adsorbents/(photo)catalysts, was prepared from a local type of Iranian clay and titanium isopropoxide. The production process was optimized by changing three operating parameters, including the clay suspension concentration (in the range of 0.5-10% w/v), the H+/Ti ratio (2-8 mol/mol), and the calcination temperature (300-700 °C). The largest specific surface area for the Ti-PILC was about 164 m2/g under the clay suspension of 0.5% w/v, H+/Ti = 6, with a surface area 273% larger than that of the raw clay. The surface areas obtained from more concentrated clay suspensions were, however, comparable (159 m2/g for 3% w/v clay and H+/Ti = 4). An increase in the calcination temperature has a negative effect on the porous texture of Ti-PILC, but based on modeling with artificial neural networks, its contribution was only 7%. Clay suspension and H+/Ti ratio play a role of 56 and 37% of the specific surface area. The presence of rutile phase, and in some cases anatase phase of TiO2 crystals was detected. FTIR and SEM investigations of Ti-PILCs produced under different operating parameters were analyzed.

Biological oxidation methods for the removal of organic and inorganic contaminants from wastewater: A comprehensive review.

Enzyme-based bioremediation is a simple, cost-effective, and environmentally friendly method for isolating and removing a wide range of environmental pollutants. This study is a comprehensive review of recent studies on the oxidation of pollutants by biological oxidation methods, performed individually or in combination with other methods. The main bio-oxidants capable of removing all types of pollutants, such as organic and inorganic molecules, from fungi, bacteria, algae, and plants, and different types of enzymes, as well as the removal mechanisms, were investigated. The use of mediators and modification methods to improve the performance of microorganisms and their resistance under harsh real wastewater conditions was discussed, and numerous case studies were presented and compared. The advantages and disadvantages of conventional and novel immobilization methods, and the development of enzyme engineering to adjust the content and properties of the desired enzymes, were also explained. The optimal operating parameters such as temperature and pH, which usually lead to the best performance, were presented. A detailed overview of the different combination processes was also given, including bio-oxidation in coincident or consecutive combination with adsorption, advanced oxidation processes, and membrane separation. One of the most important issues that this study has addressed is the removal of both organic and inorganic contaminants, taking into account the actual wastewaters and the economic aspect.

Air-to-Air Heat and Moisture Recovery in a Plate-Frame Exchanger Using Composite and Asymmetric Membranes.

The present work studied an air-to-air exchanger comprising a flat plate module with a diagonal channel and a counterflow configuration for the air streams. The objective of this study was to remove moisture and sensible heat from an exhaust air stream by indirect contact with another air stream. The temperature and flow rate of the exhaust air was in the range of 40-80 °C and 1-5 L·min-1, respectively, and the fresh ambient air to exhaust air flow ratio was 1-5. An asymmetric porous membrane (P-MEM), a thin film composite membrane (C-MEM), and a kraft paper were used as the core for the heat exchange module. The most influential parameter was the humid air temperature, with a direct positive effect (50-60%) due to the increase in the kinetic energy of the water molecules. The other effective parameter was the flow rate of the humid gas with a reverse effect on the enthalpy exchanger performance (25-37%). The ratio of "fresh" air to "exhaust" air had the lowest positive effect (8-10%) on the total effectiveness. The sensible effectiveness of different membranes under the studied conditions was relatively the same, showing their similar heat conductivity. However, the kraft paper showed the best performance compared to the synthetic membranes due to having a porous/hydrophile texture. P-MEM with an asymmetric porous texture showed the closest performance to kraft paper. Furthermore, it was found that under limited conditions, such as higher temperatures (70 and 80 °C) and flow rates (5 L·min-1) for the humid air, the performance of P-MEM was a little better than the kraft paper. However, C-MEM with the lowest total effectiveness and overall heat transfer coefficient (150-210 W·m-2·K-1) showed that the hydrophile PEBAX layer could not contribute to moisture recovery due to its high thickness.

Photocatalytic treatment of tetracycline antibiotic wastewater by silver/TiO2 nanosheets/reduced graphene oxide and artificial neural network modeling.

In this work, we focused on facile preparation of ternary nanocomposites containing TiO2 nanosheets, reduced graphene oxide, and different quantities of silver for photocatalytic treatment of tetracycline (TC) antibiotic wastewater. Plasmonic silver nanoparticles were deposited on TiO2 nanosheets/reduced graphene oxide nanocomposite via a photodeposition method (TGA(x) samples). The as-obtained samples were identified by variety of techniques such as XRD, UV-Vis DRS, FESEM/EDX, TEM, and Raman spectroscopy. The photocatalytic degradation experiments of TC (in concentration of 30 mg/L) were carried out by synthesized nanocomposites, and the degradation efficiency of TGA (0.076) (the optimal sample) was evaluated as 52.56% after 3 hr of irradiation under visible light. The obtained results showed that in TGA(x) samples, the reduced graphene oxide acts as a bridge for transferring photoinduced electrons from plasmonic silver nanoparticles to TiO2 nanosheetes. A three-layered artificial neural network model with four input variables (irradiation time, catalyst dosage, initial concentration of TC, and silver nitrate content) and one output variable (% degradation) was optimized with 11 hidden neurons. The relative importance of the independent variables was calculated using Garson formula and the initial concentration of TC was found as the most influencing parameter (relative importance of 31%) on the treatment efficiency. PRACTITIONER POINTS: TiO2 nanosheets synthesized on the reduced graphene oxide by hydrothermal method. Plasmonic silver nanoparticles deposited on TNs/rGO by photodeposition method The photocatalytic degradation of tetracycline (TC) was modeled by artificial neural network.