[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Ghaslani et al., 2017 - Google Patents

Descriptive and predictive models for Henry's law constant of CO2 in ionic liquids: a QSPR study

Ghaslani et al., 2017

View PDF
Document ID
5689083227384713757
Author
Ghaslani D
Gorji Z
Gorji A
Riahi S
Publication year
Publication venue
Chemical Engineering Research and Design

External Links

Snippet

Associate surplus substances presence in natural gases like carbon dioxide (CO 2) causes prominent problems in transporting and storage stages. Unique features of ionic liquids such as low vapor pressure, excellent thermal and chemical stability, high power of dissolution …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G06F17/5018—Computer-aided design using simulation using finite difference methods or finite element methods

Similar Documents

Publication Publication Date Title
Ghaslani et al. Descriptive and predictive models for Henry’s law constant of CO2 in ionic liquids: a QSPR study
Venkatraman et al. Predicting CO2 capture of ionic liquids using machine learning
Eslamimanesh et al. Artificial neural network modeling of solubility of supercritical carbon dioxide in 24 commonly used ionic liquids
Llovell et al. Free-volume theory coupled with soft-SAFT for viscosity calculations: comparison with molecular simulation and experimental data
Moultos et al. Atomistic molecular dynamics simulations of CO2 diffusivity in H2O for a wide range of temperatures and pressures
Ahmadi et al. Connectionist technique estimates H2S solubility in ionic liquids through a low parameter approach
Llovell et al. Modeling complex associating mixtures with [C n-mim][Tf2N] ionic liquids: predictions from the soft-SAFT equation
Amar et al. Modeling viscosity of CO2 at high temperature and pressure conditions
Nordness et al. Predicting thermophysical properties of dialkylimidazolium ionic liquids from sigma profiles
Ghiasi et al. Application of decision tree learning in modelling CO2 equilibrium absorption in ionic liquids
Ashrafmansouri et al. Modeling gas solubility in ionic liquids with the SAFT-γ group contribution method
Atashrouz et al. Estimation of the viscosity of ionic liquids containing binary mixtures based on the Eyring’s theory and a modified Gibbs energy model
Zhang et al. Molecular dynamics evaluation of removal of acid gases from SNG by ionic liquid
Polishuk Implementation of CP-PC-SAFT for predicting thermodynamic properties and gas solubility in 1-alkyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide ionic liquids without fitting binary parameters
Mokarizadeh et al. Comparison of LSSVM model results with artificial neural network model for determination of the solubility of SO2 in ionic liquids
Zhao et al. Predicting H 2 S solubility in ionic liquids by the quantitative structure–property relationship method using S σ-profile molecular descriptors
Haghbakhsh et al. A simple correlation to predict high pressure solubility of carbon dioxide in 27 commonly used ionic liquids
Zhao et al. Hydrogen sulfide solubility in ionic liquids (ILs): an extensive database and a new ELM model mainly established by imidazolium-based ILs
Bahmani et al. Prediction of solubility of sulfur dioxide in ionic liquids using artificial neural network
Barati-Harooni et al. An accurate CSA-LSSVM model for estimation of densities of ionic liquids
Mesbah et al. Predicting physical properties (viscosity, density, and refractive index) of ternary systems containing 1-octyl-3-methyl-imidazolium bis (trifluoromethylsulfonyl) imide, esters and alcohols at 298.15 K and atmospheric pressure, using rigorous classification techniques
Bakhbakhi Neural network modeling of ternary solubilities of 2-naphthol in supercritical CO2: A comparative study
Sanchez-Badillo et al. Solvation thermodynamic properties of hydrogen sulfide in [C4mim][PF6],[C4mim][BF4], and [C4mim][Cl] ionic liquids, determined by molecular simulations
Atashrouz et al. A robust modeling approach to predict the surface tension of ionic liquids
Dadkhah et al. Prediction of solubility of solid compounds in supercritical CO2 using a connectionist smart technique