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2
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34548419337
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The lower explosion point-A Good Measure for Explosion Prevention: Experiment and Calculation for Pure Compounds and Some Mixtures
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Brandes, E.; Mitu, M.; Pawel, D. The lower explosion point-A Good Measure for Explosion Prevention: Experiment and Calculation for Pure Compounds and Some Mixtures. J. Loss Prevent. Proc. 2007, 20, 536.
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53849091731
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Quantitative Structure-Property Relationship for Prediction of Lower Flammability of Pure Compounds
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Gharagheizi, F. Quantitative Structure-Property Relationship for Prediction of Lower Flammability of Pure Compounds. Energy Fuels 2008, 22, 3037.
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Energy Fuels
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53849139612
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Prediction of Flash Point Temperature of Pure Components Using a Quantitative Structure-Property Relationship Model
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Gharagheizi, F.; Alamdari, R. F. Prediction of Flash Point Temperature of Pure Components Using a Quantitative Structure-Property Relationship Model. QSAR Comb. Sci. 2008, 27, 679.
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QSAR Comb. Sci
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Gharagheizi, F.1
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54049139304
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A New Neural Network-Group Contribution Method For Estimation of Flash Point
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Gharagheizi, F.; Alamdari, R. F.; Angaji, M. T. A New Neural Network-Group Contribution Method For Estimation of Flash Point. Energy Fuels 2008, 22, 1628.
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Energy Fuels
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Gharagheizi, F.1
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6
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53849129396
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QSPR Studies for Solubility Parameter by Means of Genetic Algorithm-Based Multivariate Linear Regression and Generalized Regression Neural Network
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Gharagheizi, F. QSPR Studies for Solubility Parameter by Means of Genetic Algorithm-Based Multivariate Linear Regression and Generalized Regression Neural Network. QSAR Comb. Sci. 2008, 27, 165.
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QSAR Comb. Sci
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Gharagheizi, F.1
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34248389661
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QSPR Analysis for Intrinsic Viscosity of Polymer Solutions by means of GA-MLR and RBFNN
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Gharagheizi, F. QSPR Analysis for Intrinsic Viscosity of Polymer Solutions by means of GA-MLR and RBFNN. Comput. Mater. Sci. 2007, 40, 159.
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Comput. Mater. Sci
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Gharagheizi, F.1
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8
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34547134704
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Prediction of Standard Chemical Exergy by a Three Descriptors QSPR Model
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Gharagheizi, F.; Mehrpooya, M. Prediction of Standard Chemical Exergy by a Three Descriptors QSPR Model. Energy Convers. Manage. 2007, 48, 2453.
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Energy Convers. Manage
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Gharagheizi, F.1
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9
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35348997170
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A New Neural Network Quantitative Structure-Property Relationship for Prediction of θ(Lower Critical Solution Temperature) of Polymer Solutions
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Gharagheizi, F. A New Neural Network Quantitative Structure-Property Relationship for Prediction of θ(Lower Critical Solution Temperature) of Polymer Solutions. e-Polym. 2007, 114.
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e-Polym
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Gharagheizi, F.1
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10
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40649113078
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A New Molecular-Based Model for Prediction of Enthalpy of Sublimation of Pure Components
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Gharagheizi, F. A New Molecular-Based Model for Prediction of Enthalpy of Sublimation of Pure Components. Thermochim. Acta 2008, 469, 8.
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Thermochim. Acta
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Gharagheizi, F.1
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11
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41049101648
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A Simple Equation for Prediction of Standard Net Heat of Combustion of Pure Chemicals
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Gharagheizi, F. A Simple Equation for Prediction of Standard Net Heat of Combustion of Pure Chemicals. Chemom. Intell. Lab. Syst. 2008, 91, 177.
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Chemom. Intell. Lab. Syst
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Gharagheizi, F.1
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12
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53849109008
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Prediction of Watson Characterization Factor of Hydrocarbon Compounds from Their Molecular Properties
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Gharagheizi, F.; Fazeli, A. Prediction of Watson Characterization Factor of Hydrocarbon Compounds from Their Molecular Properties. QSAR Comb. Sci. 2008, 27, 758.
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QSAR Comb. Sci
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Gharagheizi, F.1
Fazeli, A.2
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13
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38149048424
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A Molecular-Based Model for Prediction of Solubility of C60 Fullerene in Various Solvents
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Gharagheizi, F.; Alamdari, R. F. A Molecular-Based Model for Prediction of Solubility of C60 Fullerene in Various Solvents. Fullerenes, Nanotubes, Carbon Nanostruct. 2008, 16, 40.
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Fullerenes, Nanotubes, Carbon Nanostruct
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Gharagheizi, F.1
Alamdari, R.F.2
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14
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60549103767
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Prediction of Some Important Physical Properties of Sulfur Compounds Using QSPR models
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Gharagheizi, F.; Mehrpooya, M. Prediction of Some Important Physical Properties of Sulfur Compounds Using QSPR models. Mol. Divers. 2008, 12, 143.
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Mol. Divers
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, pp. 143
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Gharagheizi, F.1
Mehrpooya, M.2
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15
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61549105859
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Estimation of Aniline Point Temperature of Pure Hydrocarbons: A Quantitative Structure-Property Relationship Approach
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Gharagheizi, F.; Tirandazi, B.; Barzin, R. Estimation of Aniline Point Temperature of Pure Hydrocarbons: A Quantitative Structure-Property Relationship Approach. Ind. Eng. Chem. Res. 2009, 48, 1678.
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Ind. Eng. Chem. Res
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Gharagheizi, F.1
Tirandazi, B.2
Barzin, R.3
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16
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34249900700
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Prediction of Standard Enthalpy of Formation by a QSPR Model
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Vatani, A.; Mehrpooya, M.; Gharagheizi, F. Prediction of Standard Enthalpy of Formation by a QSPR Model. Int. J. Mol. Sci. 2007, 8, 407.
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Int. J. Mol. Sci
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Vatani, A.1
Mehrpooya, M.2
Gharagheizi, F.3
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17
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46149093912
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Prediction of Molecular Diffusivity of Pure Components into Air: A QSPR Approach
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Sattari, M.; Gharagheizi, F. Prediction of Molecular Diffusivity of Pure Components into Air: A QSPR Approach. Chemosphere 2008, 72, 1298.
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Chemosphere
, vol.72
, pp. 1298
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Sattari, M.1
Gharagheizi, F.2
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18
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67649933550
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Model for Estimation of Lower Flammability Limit Temperature of Pure Compounds Based on molecular Structure
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available online March 27
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Gharagheizi, F. A QSPR Model for Estimation of Lower Flammability Limit Temperature of Pure Compounds Based on molecular Structure. J. Hazard. Mater., available online March 27, http://dx.doi.org/10.1016/j.jhazmat.2009. 03.083.
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J. Hazard. Mater
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Gharagheizi, F.A.Q.1
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19
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53849136438
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Design Institute for Physical Properties (DIPPR, American Institute of Chemical Engineers AIChE
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Project 801, Evaluated Process Design Data, Public Release Documentation; Design Institute for Physical Properties (DIPPR), American Institute of Chemical Engineers (AIChE), 2006.
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Evaluated Process Design Data, Public Release Documentation
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20
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0043235835
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Prediction of Physicochemical Properties Based on Neural Network Modelling
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Taskinen, J.; Yliruusi, J. Prediction of Physicochemical Properties Based on Neural Network Modelling. Adv. Drug Delivery Rev. 2003, 55, 1163.
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0142245649
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Artificial Neural Network Investigation of Structural Group Contribution Method for Predicting Pure Components Auto Ignition Temperature
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Albahri, T.; George, R. S. Artificial Neural Network Investigation of Structural Group Contribution Method for Predicting Pure Components Auto Ignition Temperature. Ind. Eng. Chem. Res. 2003, 42, 5708.
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Structural Group Contribution Method for Predicting the Octane Number of Pure Hydrocarbon Liquids
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Albahri, T. Structural Group Contribution Method for Predicting the Octane Number of Pure Hydrocarbon Liquids. Ind. Eng. Chem. Res. 2003, 42, 657.
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