Synthesis of 2,4,6,8,10,12‐Hexanitro‐2,4,6,8,10,12‐hexaazaisowurtzitane Using Melaminium‐tris(hydrogensulfate) by a Simple One‐Pot Nitration Procedure

A highly efficient protocol for the synthesis of 2,4,6,8,10,12‐hexanitro‐2,4,6,8,10,12‐hexaazaisowurtzitane (CL‐20) in the presence of melaminium‐tris(hydrogen sulfate) as a solid acid is described.     

Modeling and Transport Analysis of Silver Extraction in Porous Membrane Extractors by Computational Methods

A comprehensive two-dimensional mathematical model was developed for the transport of $ {\text{Ag(CN)}}_{ 2}^{ - } $ ions through porous membrane extractors. Extraction of $ {\text{Ag(CN)}}_{ 2}^{ - } $ with n-heptane solution of N,N-bis(2-ethyl hexyl) guanidine as extractant (LIX79) was investigated theoretically. Simulations were done using computational fluid dynamics of momentum and mass transfer in all subdomains of a hollow-fiber membrane extractor by COMSOL Multiphysics software. The latter uses finite element method for numerical simulations. Parabolic velocity profile was used for the aqueous feed in the tube side and the solvent flow in the shell side that was characterized by Happel’s equation. The distribution of concentration was obtained for the solute in the membrane module. Simulation results indicated that increasing feed flow rate reduces the extraction efficiency of silver from aqueous phase to organic phase. Dimensionless concentration distribution (C/C₀) of silver ions in the tube side of membrane extractor in axial and radial direction shows that it moves to the membrane due to the concentration difference, and then it is swept by the moving extractants in the shell.     

PRSV equation of state parameter modeling through artificial neural network and adaptive network-based fuzzy inference system

Two different modeling methods have been proposed to relate the Peng-Robinson-Stryjek-Vera (PRSV) parameter, κ ₁, to some common thermodynamic constants, including critical temperature (T _c ), critical pressure (P _c ), acentric factor (ω) and molecular weight (Mw). The methods are artificial neural network (ANN) and adaptive networkbased fuzzy inference System (ANFIS). A set of 159 data points (116, 23 and 20) was used for construct training, validating and testing, respectively. The radius parameter of ANFIS was determined through genetic algorithm (GA) optimization technique. The ANN and especially ANFIS results are in a good agreement with most of the compound groups.