1
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Michaud SE, Barber MM, Rivera Cruz KE, McCrory CCL. Electrochemical Oxidation of Primary Alcohols Using a Co 2NiO 4 Catalyst: Effects of Alcohol Identity and Electrochemical Bias on Product Distribution. ACS Catal 2022. [DOI: 10.1021/acscatal.2c02923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Samuel E. Michaud
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan48109-1055, United States
| | - Michaela M. Barber
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan48109-1055, United States
| | - Kevin E. Rivera Cruz
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan48109-1055, United States
| | - Charles C. L. McCrory
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan48109-1055, United States
- Macromolecular Science and Engineering Program, University of Michigan, Ann Arbor, Michigan48109-1055, United States
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2
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Zhang H, Xu X, Tan L, Liang Z, Cao R, Wan Q, Xu H, Wang J, Huang T, Wen G. The aggregation of Aspergillus spores and the impact on their inactivation by chlorine-based disinfectants. WATER RESEARCH 2021; 204:117629. [PMID: 34509870 DOI: 10.1016/j.watres.2021.117629] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 08/17/2021] [Accepted: 08/29/2021] [Indexed: 06/13/2023]
Abstract
The formation of fungal biofilm goes through some different states, including monodisperse state, aggregated state, germinated state, hyphal and biofilm. The aggregation of spores is a primary step of fungal biofilm development in aquatic systems. Previous studies on the inactivation of fungi were mostly performed in the monodisperse state of fungal spores and biofilm state, however, the inactivation of aggregated fungal spores is still unclear. In this study, the aggregated characteristics of fungal spores (Aspergillus fumigatus and Aspergillus flavus) at different pH values were firstly studied, and the inactivation efficiency of fungal spores at different aggregation degree by chlorine-based disinfectants was also clarified. The results showed that the aggregation degree of Aspergillus fumigatus was the highest at pH 9.0 while it was the lowest at pH 5.0. Aggregation between fungal spores was mainly mediated by occasional adhesin-adhesin interactions and electrostatic interactions. Compared with monodisperse spores, fungal spores were more resistant to chlorine-based disinfectants with the increase of spore aggregation degree. The inactivation rate constants of Aspergillus fumigatus at 30% and 63% aggregation degree were 1.5- and 4-folds lower than that of monodisperse spores, respectively. The lower proportion of membrane damage and higher intracellular reactive oxygen species level for aggregated spores than monodisperse spores was observed according to the flow cytometric results after chlorine-based disinfectants treatment. The reasons for the lower inactivation efficiency of aggregated spores are as following: the protection of outer layer spores and signals between aggregates lead to the increase of resistance for aggregated spores. This study is meaningful for the control of the fungal spores at different states in water.
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Affiliation(s)
- Huan Zhang
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Xiangqian Xu
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Lili Tan
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Zhiting Liang
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Ruihua Cao
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Qiqi Wan
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Huining Xu
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Jingyi Wang
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Tinglin Huang
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China
| | - Gang Wen
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, People's Republic of China.
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3
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Aniceto JP, Zêzere B, Silva CM. Machine learning models for the prediction of diffusivities in supercritical CO2 systems. J Mol Liq 2021. [DOI: 10.1016/j.molliq.2021.115281] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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4
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Predictive Models for the Binary Diffusion Coefficient at Infinite Dilution in Polar and Nonpolar Fluids. MATERIALS 2021; 14:ma14030542. [PMID: 33498723 PMCID: PMC7866074 DOI: 10.3390/ma14030542] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/07/2021] [Accepted: 01/19/2021] [Indexed: 12/03/2022]
Abstract
Experimental diffusivities are scarcely available, though their knowledge is essential to model rate-controlled processes. In this work various machine learning models to estimate diffusivities in polar and nonpolar solvents (except water and supercritical CO2) were developed. Such models were trained on a database of 90 polar systems (1431 points) and 154 nonpolar systems (1129 points) with data on 20 properties. Five machine learning algorithms were evaluated: multilinear regression, k-nearest neighbors, decision tree, and two ensemble methods (random forest and gradient boosted). For both polar and nonpolar data, the best results were found using the gradient boosted algorithm. The model for polar systems contains 6 variables/parameters (temperature, solvent viscosity, solute molar mass, solute critical pressure, solvent molar mass, and solvent Lennard-Jones energy constant) and showed an average deviation (AARD) of 5.07%. The nonpolar model requires five variables/parameters (the same of polar systems except the Lennard-Jones constant) and presents AARD = 5.86%. These results were compared with four classic models, including the 2-parameter correlation of Magalhães et al. (AARD = 5.19/6.19% for polar/nonpolar) and the predictive Wilke-Chang equation (AARD = 40.92/29.19%). Nonetheless Magalhães et al. requires two parameters per system that must be previously fitted to data. The developed models are coded and provided as command line program.
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5
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QSPRs for Molecular Diffusion Coefficients in Polymeric Passive Samplers: A Comparison of Simple Molecular and Quantum‐mechanical Sigma‐moment Descriptors. Mol Inform 2019; 38:e1800110. [DOI: 10.1002/minf.201800110] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 04/08/2019] [Indexed: 11/07/2022]
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6
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An Alternative Method for Correlation and Evaluation of Mutual Diffusion Coefficients of Solutes in Organic Solvents at Infinite Dilution. J SOLUTION CHEM 2018. [DOI: 10.1007/s10953-018-0804-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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7
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Bagheri M, Borhani TNG, Gandomi AH, Manan ZA. A simple modelling approach for prediction of standard state real gas entropy of pure materials. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2014; 25:695-710. [PMID: 25158071 DOI: 10.1080/1062936x.2014.942356] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
The performance of an energy conversion system depends on exergy analysis and entropy generation minimisation. A new simple four-parameter equation is presented in this paper to predict the standard state absolute entropy of real gases (SSTD). The model development and validation were accomplished using the Linear Genetic Programming (LGP) method and a comprehensive dataset of 1727 widely used materials. The proposed model was compared with the results obtained using a three-layer feed forward neural network model (FFNN model). The root-mean-square error (RMSE) and the coefficient of determination (r(2)) of all data obtained for the LGP model were 52.24 J/(mol K) and 0.885, respectively. Several statistical assessments were used to evaluate the predictive power of the model. In addition, this study provides an appropriate understanding of the most important molecular variables for exergy analysis. Compared with the LGP based model, the application of FFNN improved the r(2) to 0.914. The developed model is useful in the design of materials to achieve a desired entropy value.
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Affiliation(s)
- M Bagheri
- a Young Researchers and Elites Club, Science and Research Branch , Islamic Azad University , Tehran , Iran
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8
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Gharagheizi F, Sattari M, Ilani-Kashkouli P, Mohammadi AH, Ramjugernath D, Richon D. Quantitative structure—property relationship for thermal decomposition temperature of ionic liquids. Chem Eng Sci 2012. [DOI: 10.1016/j.ces.2012.08.036] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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9
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Devillers J, Doucet JP, Doucet-Panaye A, Decourtye A, Aupinel P. Linear and non-linear QSAR modelling of juvenile hormone esterase inhibitors. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2012; 23:357-369. [PMID: 22443267 DOI: 10.1080/1062936x.2012.664562] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
A tight control of juvenile hormone (JH) titre is crucial during the life cycle of a holometabolous insect. JH metabolism is made through the action of enzymes, particularly the juvenile hormone esterase (JHE). Trifluoromethylketones (TFKs) are able to inhibit this enzyme to disrupt the endocrine function of the targeted insect. In this context, a set of 96 TFKs, tested on Trichoplusia ni for their JHE inhibition, was split into a training set (n = 77) and a test set (n = 19) to derive a QSAR model. TFKs were initially described by 42 CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) descriptors, but a feature selection process allowed us to consider only five descriptors encoding the structural characteristics of the TFKs and their reactivity. A classical and spline regression analysis, a three-layer perceptron, a radial basis function network and a support vector regression were experienced as statistical tools. The best results were obtained with the support vector regression (r(2) and r(test)(2) = 0.91). The model provides information on the structural features and properties responsible for the high JHE inhibition activity of TFKs.
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10
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Gharagheizi F, Ilani-Kashkouli P, Mirkhani SA, Mohammadi AH. Computation of Upper Flash Point of Chemical Compounds Using a Chemical Structure-Based Model. Ind Eng Chem Res 2012. [DOI: 10.1021/ie202868v] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Farhad Gharagheizi
- Department
of Chemical Engineering, Science and Research Branch, Islamic Azad University,
Tehran, Iran
| | | | - Seyyed Alireza Mirkhani
- Department
of Chemical Engineering, Science and Research Branch, Islamic Azad University,
Tehran, Iran
| | - Amir H. Mohammadi
- MINES ParisTech, CEP/TEP—Centre Énergétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
- Thermodynamics Research Unit,
School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South
Africa
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11
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Mirkhani SA, Gharagheizi F, Sattari M. A QSPR model for prediction of diffusion coefficient of non-electrolyte organic compounds in air at ambient condition. CHEMOSPHERE 2012; 86:959-966. [PMID: 22189378 DOI: 10.1016/j.chemosphere.2011.11.021] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2011] [Revised: 11/09/2011] [Accepted: 11/13/2011] [Indexed: 05/31/2023]
Abstract
Evaluation of diffusion coefficients of pure compounds in air is of great interest for many diverse industrial and air quality control applications. In this communication, a QSPR method is applied to predict the molecular diffusivity of chemical compounds in air at 298.15K and atmospheric pressure. Four thousand five hundred and seventy nine organic compounds from broad spectrum of chemical families have been investigated to propose a comprehensive and predictive model. The final model is derived by Genetic Function Approximation (GFA) and contains five descriptors. Using this dedicated model, we obtain satisfactory results quantified by the following statistical results: Squared Correlation Coefficient=0.9723, Standard Deviation Error=0.003 and Average Absolute Relative Deviation=0.3% for the predicted properties from existing experimental values.
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12
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Gharagheizi F. Determination of Diffusion Coefficient of Organic Compounds in Water Using a Simple Molecular-Based Method. Ind Eng Chem Res 2012. [DOI: 10.1021/ie201944h] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Farhad Gharagheizi
- Department of Chemical
Engineering, Buinzahra
Branch, Islamic Azad University, Buinzahra,
Iran
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13
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Handling a very large data set for determination of surface tension of chemical compounds using Quantitative Structure–Property Relationship strategy. Chem Eng Sci 2011. [DOI: 10.1016/j.ces.2011.06.052] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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14
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Mattle MJ, Crouzy B, Brennecke M, Wigginton KR, Perona P, Kohn T. Impact of virus aggregation on inactivation by peracetic acid and implications for other disinfectants. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2011; 45:7710-7717. [PMID: 21819042 DOI: 10.1021/es201633s] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Viruses in wastewater and natural environments are often present as aggregates. The disinfectant dose required for their inactivation, however, is typically determined with dispersed viruses. This study investigates how aggregation affects virus inactivation by chemical disinfectants. Bacteriophage MS2 was aggregated by lowering the solution pH, and aggregates were inactivated by peracetic acid (PAA). Aggregates were redispersed before enumeration to obtain the residual number of individual infectious viruses. In contrast to enumerating whole aggregates, this approach allowed an assessment of disinfection efficiency which remains applicable even if the aggregates disperse in post-treatment environments. Inactivation kinetics were determined as a function of aggregate size (dispersed, 0.55 and 0.90 μm radius) and PAA concentration (5-103 mg/L). Aggregation reduced the apparent inactivation rate constants 2-6 fold. The larger the aggregate and the higher the PAA concentration, the more pronounced the inhibitory effect of aggregation on disinfection. A reaction-diffusion based model was developed to interpret the experimental results, and to predict inactivation rates for additional aggregate sizes and disinfectants. The model showed that the inhibitory effect of aggregation arises from consumption of the disinfectant within the aggregate, but that diffusion of the disinfectant into the aggregates is not a rate-limiting factor. Aggregation therefore has a large inhibitory effect if highly reactive disinfectants are used, whereas inactivation by mild disinfectants is less affected. Our results suggest that mild disinfectants should be used for the treatment of water containing viral aggregates.
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Affiliation(s)
- Michael J Mattle
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL)
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15
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Gharagheizi F, Eslamimanesh A, Farjood F, Mohammadi AH, Richon D. Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure–Property Relationship Strategy. Ind Eng Chem Res 2011. [DOI: 10.1021/ie200962w] [Citation(s) in RCA: 88] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Affiliation(s)
| | - Ali Eslamimanesh
- MINES ParisTech, CEP/TEP - Centre Energétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
| | - Farhad Farjood
- School of Chemical Engineering, University of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Amir H. Mohammadi
- MINES ParisTech, CEP/TEP - Centre Energétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
- Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
| | - Dominique Richon
- MINES ParisTech, CEP/TEP - Centre Energétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
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16
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Gharagheizi F, Eslamimanesh A, Mohammadi AH, Richon D. Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds. Ind Eng Chem Res 2011. [DOI: 10.1021/ie201002e] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
| | - Ali Eslamimanesh
- MINES ParisTech, CEP/TEP−Centre Énergetique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
| | - Amir H. Mohammadi
- MINES ParisTech, CEP/TEP−Centre Énergetique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
- Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
| | - Dominique Richon
- MINES ParisTech, CEP/TEP−Centre Énergetique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
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17
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Artificial Neural Network modeling of solubility of supercritical carbon dioxide in 24 commonly used ionic liquids. Chem Eng Sci 2011. [DOI: 10.1016/j.ces.2011.03.016] [Citation(s) in RCA: 112] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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18
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Gharagheizi F, Eslamimanesh A, Mohammadi AH, Richon D. QSPR approach for determination of parachor of non-electrolyte organic compounds. Chem Eng Sci 2011. [DOI: 10.1016/j.ces.2011.03.039] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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19
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Gharagheizi F, Babaie O, Mazdeyasna S. Prediction of Vaporization Enthalpy of Pure Compounds using a Group Contribution-Based Method. Ind Eng Chem Res 2011. [DOI: 10.1021/ie2001764] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Omid Babaie
- Saman Energy Giti Co., Postal Code 3331619636, Tehran, Iran
| | - Sahar Mazdeyasna
- Department of Chemical Engineering, Iran University of Science and Technology, Tehran, Iran
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20
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Gharagheizi F, Eslamimanesh A, Mohammadi AH, Richon D. Determination of Parachor of Various Compounds Using an Artificial Neural Network−Group Contribution Method. Ind Eng Chem Res 2011. [DOI: 10.1021/ie102464t] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Ali Eslamimanesh
- MINES ParisTech, CEP/TEP—Centre Énergétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
| | - Amir H. Mohammadi
- MINES ParisTech, CEP/TEP—Centre Énergétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
- Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
| | - Dominique Richon
- MINES ParisTech, CEP/TEP—Centre Énergétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France
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21
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Gharagheizi F, Abbasi R. A New Neural Network Group Contribution Method for Estimation of Upper Flash Point of Pure Chemicals. Ind Eng Chem Res 2010. [DOI: 10.1021/ie1011273] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Reza Abbasi
- Saman Energy Giti Co., Postal Code 3331619636, Tehran, Iran
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22
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Gharagheizi F, Eslamimanesh A, Mohammadi AH, Richon D. Artificial Neural Network Modeling of Solubilities of 21 Commonly Used Industrial Solid Compounds in Supercritical Carbon Dioxide. Ind Eng Chem Res 2010. [DOI: 10.1021/ie101545g] [Citation(s) in RCA: 77] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Farhad Gharagheizi
- Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563, Tehran, Iran, MINES ParisTech, CEP/TEP - Centre Énergétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France, and Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
| | - Ali Eslamimanesh
- Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563, Tehran, Iran, MINES ParisTech, CEP/TEP - Centre Énergétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France, and Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
| | - Amir H. Mohammadi
- Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563, Tehran, Iran, MINES ParisTech, CEP/TEP - Centre Énergétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France, and Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
| | - Dominique Richon
- Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563, Tehran, Iran, MINES ParisTech, CEP/TEP - Centre Énergétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France, and Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
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23
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Gharagheizi F, Sattari M. Prediction of Triple-Point Temperature of Pure Components Using their Chemical Structures. Ind Eng Chem Res 2009. [DOI: 10.1021/ie901029m] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Farhad Gharagheizi
- Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563, Tehran, Iran, and Division of Polymer Science and Technology, Research Institute of Petroleum Industry (RIPI), P.O. Box 14665-1998, Tehran, Iran
| | - Mehdi Sattari
- Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563, Tehran, Iran, and Division of Polymer Science and Technology, Research Institute of Petroleum Industry (RIPI), P.O. Box 14665-1998, Tehran, Iran
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24
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Gharagheizi F, Sattari M. Prediction of the θ(UCST) of Polymer Solutions: A Quantitative Structure−Property Relationship Study. Ind Eng Chem Res 2009. [DOI: 10.1021/ie9000426] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Farhad Gharagheizi
- Department of Chemical Engineering, Faculty of Engineering,
University of Tehran, P.O. Box 11365-4563, Tehran, Iran, and Division
of Polymer Science and Technology, Research Institute of Petroleum
Industry (RIPI), P.O. Box 14665-1998, Tehran, Iran
| | - Mehdi Sattari
- Department of Chemical Engineering, Faculty of Engineering,
University of Tehran, P.O. Box 11365-4563, Tehran, Iran, and Division
of Polymer Science and Technology, Research Institute of Petroleum
Industry (RIPI), P.O. Box 14665-1998, Tehran, Iran
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