Optimizing methanol synthesis from CO2 using graphene-based heterogeneous photocatalyst under RSM and ANN-driven parametric optimization for achieving better suitability.

Assessment of the performance of linear and nonlinear regression-based methods for estimating in situ catalytic CO2 transformations employing TiO2/Cu coupled with hydrogen exfoliation graphene (HEG) has been investigated. The yield of methanol was thoroughly optimized and predicted using response surface methodology (RSM) and artificial neural network (ANN) model after rigorous experimentation and comparison. Amongst the different types of HEG loading from 10 to 40 wt%, the 30 wt% in the HEG-TiO2/Cu assisted photosynthetic catalyst was found to be successful in providing the highest conversion efficiency of methanol from CO2. The most influencing parameters, HEG dosing and inflow rate of CO2, were found to affect the conversion rate in the acidic reaction regime (at pH of 3). According to RSM and ANN, the optimum methanol yields were 36.3 mg g-1 of catalyst and 37.3 mg g-1 of catalyst, respectively. Through the comparison of performances using the least squared error analysis, the nonlinear regression-based ANN showed a better determination coefficient (overall R2 > 0.985) than the linear regression-based RSM model (overall R2 ∼ 0.97). Even though both models performed well, ANN, consisting of 9 neurons in the input and 1 hidden layer, could predict optimum results closer to RSM in terms of agreement with the experimental outcome.

Two-Phase Crude Oil-Water Flow Through Different Pipes: An Experimental Investigation Coupled with Computational Fluid Dynamics Approach.

The present study deals with two-phase non-Newtonian pseudoplastic crude oil and water flow inside horizontal pipes simulated by ANSYS. The study helps predict velocity and velocity profiles, as well as pressure drop during two-phase crude-oil-water flow, without complex calculations. Computational fluid dynamics (CFD) analysis will be very important in reducing the experimental cost and the effort of data acquisition. Three independent horizontal stainless steel pipes (SS-304) with inner diameters of 1 in., 1.5 in., and 2 in. were used to circulate crude oil with 5, 10, and 15% v/v water for simulation purposes. The entire length of the pipes, along with their surfaces, were insulated to reduce heat loss. A grid size of 221,365 was selected as the optimal grid. Two-phase flow phenomena, pressure drop calculations, shear stress on the walls, along with the rate of shear strain, and phase analysis were studied. Moreover, velocity changes from the wall to the center, causing a velocity gradient and shear strain rate, but at the center, no velocity variation (velocity gradient) was observed between the layers of the fluid. The precision of the simulation was investigated using three error parameters, such as mean square error, Nash-Sutcliffe efficiency, and RMSE-standard deviation of observation ratio. From the simulation, it was found that CFD analysis holds good agreement with experimental results. The uncertainty analysis demonstrated that our CFD model is helpful in predicting the rheological parameters very accurately. The study aids in identifying and predicting fluid flow phenomena inside horizontal straight pipes in a very effective way.

CuO/TiO2/ZnO NPs Anchored Hydrogen Exfoliated Graphene: To Comprehend the Role of Graphene in Catalytic Reduction of p-Nitrophenol.

The present study deals with sonochemically in situ synthesis of a novel functional catalyst using hydrogen exfoliated graphene (HEG) supported titanium dioxide (TiO2) and copper sulfate (CuSO4) doped with zinc oxide (ZnO) (abbreviated as Ti/Cu/Zn-HEG). The synthesis of the Ti/Cu/Zn-HEG nanocomposite (NCs) catalyst was confirmed through its characterizations by XRD, SEM-EDX, TEM, XPS, FTIR, and BET methods. It was assessed for catalytic conversion of a model aromatic compound para-nitrophenol (p-NP) in an aqueous solution. The p-NP is a nitroaromatic compound that has a toxic and mutagenic effect. Its removal from the water system is necessary to protect the environment and living being. The newly synthesized Ti/Cu/Zn-HEG NCs were applied for their higher stability and catalytic activity as a potential candidate for reducing p-NP in practice. The operating parameters, such as p-NP concentration, catalyst dosage, and operating time were optimized for 150 ppm, 400 ppm, and 10 min through response surface methodology (RSM) in Design-Expert software to obtain the maximum reduction p-NP up to 98.4% at its normal pH of 7.1 against the controls (using HEG, Ti/Cu-HEG, and Zn-HEG). Analysis of variance of the response suggested the regression equation to be significant for the process with a major impact on catalyst concentration and operating time. The model prediction data (from RSM) and experimental data were corroborated well as reflected through model's low relative error (RE < 0.10), high regression coefficient (R2 > 0.97), and Willmott d-index (dwill-index > 0.95) values.