AI-PCSAFT approach: New high predictive method for estimating PC-SAFT pure component properties and phase equilibria parameters was written by Abdallah el hadj, A.;Laidi, M.;Hanini, S.. And the article was included in Fluid Phase Equilibria in 2022.Formula: C19H15Cl This article mentions the following:
In this work, a new approach based on the association of Artificial intelligence method (AI) and PC-SAFT equation of state is applied to conceive a model for estimating the solubility of solid drugs in supercritical carbon dioxide. Neuro-equation of state approach (NES) is the new technique that takes benefit from the advantages of both ANN and PC-SAFT equation of state. The new method decomposes into three main stages, first the optimization of direct ANN for predicting solids-scCO2 phase equilibrium (where 15 binary systems are used), then the ANN inverse is performed to be an alternative to group contribution methods (GCMs) for estimating the pure components and phys. properties (reduce the uncertainty committed in estimating these properties) and enhance the PCSAFT equation of state to estimate phase equilibrium parameters and finally, ANN-PCSAFT approach is used to estimate the solubility of 213 solid solutes in supercritical carbon dioxide. The performance strategy has been carried out using a linear regression anal. of the predicted vs. exptl. outputs, as an indication of the predictive ability of the developed method. The new approach is successfully applied to the phase equilibrium modeling for 213 binary systems with high accuracy (the comparison in terms of average absolute relative deviation (AARD %) showed a variation from 2 to 6%) and allowed to enhance the phase equilibrium modeling by reducing the number of optimized parameters and surpass the main drawbacks faced in this area mainly the non-availability of phys. properties and EOS pure component properties and the limitation of the equation of state. In the experiment, the researchers used many compounds, for example, (Chloromethanetriyl)tribenzene (cas: 76-83-5Formula: C19H15Cl).
(Chloromethanetriyl)tribenzene (cas: 76-83-5) belongs to organic chlorides. Chlorination modifies the physical properties of hydrocarbons in several ways. These compounds are typically denser than water due to the higher atomic weight of chlorine versus hydrogen. Aliphatic organochlorides are often alkylating agents as chlorine can act as a leaving group, which can result in cellular damage.Formula: C19H15Cl
Referemce:
Chloride – Wikipedia,
Chlorides – an overview | ScienceDirect Topics