| 1 |
Predicting home thermal dynamics using a reduced-order model and automated real-time parameter estimation
Wang JK, Tang CY, Brambley MR, Song L
Energy and Buildings, 198, 305, 2019 |
| 2 |
Estimation of thermodynamic properties of hydrogen isotopes and modeling of hydrogen isotope systems using Aspen Plus simulator
Noh J, Fulgueras AM, Sebastian LJ, Lee HG, Kim DS, Cho J
Journal of Industrial and Engineering Chemistry, 46, 1, 2017 |
| 3 |
A modified scaled variable reduced coordinate (SVRC)-quantitative structure property relationship (QSPR) model for predicting liquid viscosity of pure organic compounds
Lee SM, Park KH, Kwon YK, Park TY, Yang DR
Korean Journal of Chemical Engineering, 34(10), 2715, 2017 |
| 4 |
Separation of coal gasification tar residue by solvent extracting
Niu YX, Wang XL, Shen J, Sheng QT, Liu G, Li C, Wang YG
Separation and Purification Technology, 188, 98, 2017 |
| 5 |
An enhanced group-interaction contribution method for the prediction of glass transition temperature of ionic liquids
Mokadem K, Korichi M, Tumba K
Fluid Phase Equilibria, 425, 259, 2016 |
| 6 |
Challenges and opportunities in computer-aided molecular design
Ng LY, Chong FK, Chemmangattuvalappil NG
Computers & Chemical Engineering, 81, 115, 2015 |
| 7 |
A group contribution method to predict the thermal conductivity lambda(T,P) of ionic liquids
Lazzus JA
Fluid Phase Equilibria, 405, 141, 2015 |
| 8 |
Identification and analysis of synthesis routes in complex catalytic reaction networks for biomass upgrading
Rangarajan S, Bhan A, Daoutidis P
Applied Catalysis B: Environmental, 145, 149, 2014 |
| 9 |
An artificial neural network to calculate pure ionic liquid densities without the need for any experimental data
Fatehi MR, Raeissi S, Mowla D
Journal of Supercritical Fluids, 95, 60, 2014 |
| 10 |
A group contribution method to predict the melting point of ionic liquids
Lazzus JA
Fluid Phase Equilibria, 313, 1, 2012 |
