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Literature DB >> 18701960

Estimation of ternary liquid-liquid equilibria for arene/alkane/ionic liquid mixtures using neural networks.

José S Torrecilla¹, Maggel Deetlefs, Kenneth R Seddon, Francisco Rodríguez.

Abstract

Neural network models have been explored for the prediction of the liquid-liquid equilibrium data and aromatic/aliphatic selectivity values. Four ternary systems composed of toluene, heptane, and the ionic liquids 1-ethyl-3-methylimidazolium ethylsulfate, or 1,3-dimethylimidazolium methylsulfate were investigated at 313.2 and 348.2 K.

Entities: Chemical

Year: 2008 PMID： 18701960 DOI： 10.1039/b719533h

Source DB: PubMed Journal: Phys Chem Chem Phys ISSN： 1463-9076 Impact factor: 3.676

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Cited

3 in total

1. Optimization of Stripping Voltammetric Sensor by a Back Propagation Artificial Neural Network for the Accurate Determination of Pb(II) in the Presence of Cd(II).

Authors: Guo Zhao; Hui Wang; Gang Liu; Zhiqiang Wang
Journal: Sensors (Basel) Date: 2016-09-21 Impact factor: 3.576

2. Modeling and Compensation of Random Drift of MEMS Gyroscopes Based on Least Squares Support Vector Machine Optimized by Chaotic Particle Swarm Optimization.

Authors: Haifeng Xing; Bo Hou; Zhihui Lin; Meifeng Guo
Journal: Sensors (Basel) Date: 2017-10-13 Impact factor: 3.576

3. Direct Quantification of Cd²⁺ in the Presence of Cu²⁺ by a Combination of Anodic Stripping Voltammetry Using a Bi-Film-Modified Glassy Carbon Electrode and an Artificial Neural Network.

Authors: Guo Zhao; Hui Wang; Gang Liu
Journal: Sensors (Basel) Date: 2017-07-03 Impact factor: 3.576

3 in total

Estimation of ternary liquid-liquid equilibria for arene/alkane/ionic liquid mixtures using neural networks.

1. Optimization of Stripping Voltammetric Sensor by a Back Propagation Artificial Neural Network for the Accurate Determination of Pb(II) in the Presence of Cd(II).

2. Modeling and Compensation of Random Drift of MEMS Gyroscopes Based on Least Squares Support Vector Machine Optimized by Chaotic Particle Swarm Optimization.

3. Direct Quantification of Cd2+ in the Presence of Cu2+ by a Combination of Anodic Stripping Voltammetry Using a Bi-Film-Modified Glassy Carbon Electrode and an Artificial Neural Network.

3. Direct Quantification of Cd²⁺ in the Presence of Cu²⁺ by a Combination of Anodic Stripping Voltammetry Using a Bi-Film-Modified Glassy Carbon Electrode and an Artificial Neural Network.