In this work, we used waste Styrofoam as a precursor to synthesize a hypercrosslinked polymeric (HCP) adsorbent for CO2 adsorption utilizing the Friedel–Craft procedure. The hypercrosslinked adsorbent was designed using formaldehyde dimethyl acetal (FDA) as the crosslinker. The precursor to crosslinker to catalyst ratio was 1:3:3, and the HCP synthesis was carried out for 12 h at 312.6 K. Fourier‐transform infrared spectroscopy, field emission scanning electron microscopy, and thermogravimetric analysis were used to analyze the waste Styrofoam hypercrosslinked (WSHC) adsorbent. The adsorbent attained an 802.84 m2/g Brunauer–Emmett–Teller (BET) surface area and an average pore diameter of 2.869 m3/g. The CO2 adsorption process was studied under different operating conditions, temperature between 298 and 328 K and pressure between 2 and 10 bar. WSHC adsorbent has the maximum CO2 uptake with a value of 11.053 mmol/g at 298 K and 10 bar. The behavior of the adsorption process was investigated using isotherm, kinetic, and thermodynamic models. Experimental findings indicated that the Sips isotherm and the second‐order kinetic models provided the best fit. The isotherm data indicated that adsorption occurs in multi‐layers and is heterogeneous. According to the thermodynamic characteristics, the process is exothermic and spontaneous. Finally, the kinetic findings established that the process happened physically. Additionally, a regeneration study after seven cycles revealed a 96.1% success rate. The current research may attempt to use waste Styrofoam as a gas separation adsorbent in the industry.

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This article presents a thermal sintering method to fabricate porous bone tissue engineering scaffolds based on polycaprolactone (PCL), polylactic acid (PLA), and their composites. The mechanical properties, porous structure, biodegradability, and biocompatibility of sintered scaffolds were evaluated. The scaffolds showed a porosity in the range of 86-91% with a pore size of 75 m to 400 m. PCL/PLA composite scaffolds showed a' Young's modulus of around 49 MPa, which was between the modulus values of PCL ( 24MPa) and PLA (63 MPa) scaffolds. Fibroblast cells (SNL) exhibited spreading, and adhesion on the scaffolds, and Scaffolds demonstrated a significant difference in the osteogenic differentiation of human Mesenchymal Stem Cells (hMSCs) after 7 and 14 days of culture in comparison to the control (tissue culture polystyrene). Our results demonstrated that the thermal sintered PCL/PLA composite scaffold could be a promising candidate for bone tissue regeneration.

In the present study, fabrications of two eco-friendly superhydrophobic/superoleophilic recyclable foamy-based adsorbents for oil/water mixture separation were developed. Hierarchically biomass (celery)-derived porous carbon (PC) and multi-walled carbon nanotube (MWCNT) were firstly synthesized and loaded on pristine melamine foam (MF) by the simple dip-coating approach by combining silicone adhesive to create superhydrophobic/superoleophilic, recyclable, and reusable three-dimensional porous structure. The prepared samples have a large specific surface area of 240 m2/g (MWCNT), 1126 m2/g (PC), and good micro-mesoporous frameworks. The water contact angle (WCA) values of the as-prepared foams, PC/MF and MWCNT/MF, not only were 159.34° ± 1.9° and 156.42° ± 1.6°, respectively but also had oil contact angle (OCA) of equal to 0° for a wide range of oils and organic solvents. Therefore, PC/MF and MWCNT/MF exhibited superhydrophobicity and superoleophilicity properties, which can be considered effective adsorbents in oil/water mixture separations. In this context, superhydrophobic/superoleophilic prepared foams for kind of different oils and organic solvents were shown to have superior separation performance ranges of 54–143 g/g and 46–137 g/g for PC/MF and MWCNT/MF, respectively, suggesting a new effective porous material for separating oil spills. Also, outstanding recyclability and reusability of these structures in the ten adsorption-squeezing cycles indicated that the WCA and sorption capacity has not appreciably changed after soaking into acidic (pH = 2) and alkaline (pH = 12) as well as saline (3.5% NaCl) solutions. More importantly, the reusability and chemical durability of the superhydrophobic samples made them good opportunities for use in different harsh conditions for oil-spill cleanup.

The direct reduction process has been developed and investigated in recent years due to less pollution than other methods. In this work, the first direct reduction iron oxide (DRI) modeling has been developed using artificial neural networks (ANN) algorithms such as the multilayer perceptron (MLP) and radial basis function (RBF) models. A DRI operation takes place inside the shaft furnace. A shaft furnace reactor is a gas-solid reactor that transforms iron oxide particles into sponge iron. Because of its low environmental pollution, the MIDREX process, one of the DRI procedures, has received much attention in recent years. The main purpose of the shaft furnace is to achieve the desired percentage of solid conversion output from the furnace. The network parameters were optimized, and an algorithm was developed to achieve an optimum NN model. The results showed that the MLP network has a minimum squared error (MSE) of 8.95 × 10−6, which is the lowest error compared to the RBF network model. The purpose of the study was to identify the shaft furnace solid conversion using machine learning methods without solving nonlinear equations. Another advantage of this research is that the running speed is 3.5 times the speed of mathematical modeling.