Intelligent modeling of hydrogen sulfide solubility in various types of single and multicomponent solvents

Abstract

This study aims to study the solubility of acid gas, i.e., hydrogen sulfide (H2S) in different solvents. Three intelligent approaches, including Multilayer Perceptron (MLP), Gaussian Process Regression (GPR) and Radial Basis Function (RBF) were used to construct reliable models based on an extensive databank comprising 5148 measured samples from 54 published sources. The analyzed data cover 95 single and multicomponent solvents such as amines, ionic liquids, electrolytes, organics, etc., in broad pressure and temperature ranges. The proposed models require just three simple input variables, i.e., pressure, temperature and the equivalent molecular weight of solvent to determine the solubility. A competitive examination of the novel models implied that the GPR-based one gives the most appropriate estimations with excellent AARE, R2 and RRMSE values of 4.73%, 99.75% and 4.83%, respectively for the tested data. The mentioned intelligent model also performed well in describing the physical behaviors of H2S solubility at various operating conditions. Furthermore, analyzing the William's plot for the GPR-based model affirmed the high reliability of the analyzed databank, as the outlying data points comprise just 2.04% of entire data. In contrast to the literature models, the newly presented approaches proved to be applicable for different types of single and multicomponent H2S absorbers with AAREs less than 7%. Eventually, a sensitivity analysis based on the GPR model reflected the fact that the solvent equivalent molecular weight is the most influential factor in controlling H2S solubility.

Two-phase Flow Condensation Inside Smooth Channels of Various Sizes: Universal Smart Models to Estimate the Frictional Pressure Drop

“…After receiving the information from the input layer, the hidden layer exert the nonlinear functions and sends the results to the final layer, which is responsible to combine the weights and the activation functions, linearly 57,58 ,…”

A new neodymium complex on renewable magnetic biochar nanoparticles as an environmentally friendly, recyclable and efficient nanocatalyst in the homoselective synthesis of tetrazoles

“…[15][16][17][18] Therefore, nanocatalysts as a bridge between homogeneous and heterogeneous catalysts have recently received attention because they have high catalytic activity and are easily recycled and reused, so they do not have the disadvantages of conventional catalysts, while having their own advantages. [19][20][21][22] In this context, different nanoparticles such as mesoporous silica materials, [23][24][25] graphene oxide, 26 polymers, 27,28 hercynite, 29 MOF nanoparticles, [30][31][32] boehmite, [33][34][35][36] magnetic nanoparticles, 37,38 carbon nanostructures, 39,40 biochar, [41][42][43][44][45] etc. have been reported as catalysts or catalyst supports.…”