Neural networks to fit potential energy curves from asphaltene-asphaltene interaction data

[1]  J. Pfeiffer,et al.  Asphaltic Bitumen as Colloid System. , 1940 .

[2]  J. M. Swanson A Contribution to the Physical Chemistry of the Asphalts. , 1942 .

[3]  T. Yen,et al.  Investigation of the Structure of Petroleum Asphaltenes by X-Ray Diffraction , 1961 .

[4]  Peter E. Hart,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[5]  J. Speight,et al.  Some observations on the molecular nature of petroleum asphaltenes , 1979 .

[6]  J. Speight The Chemistry and Technology of Petroleum , 1980 .

[7]  G. Mansoori,et al.  Optimized parameters and exponents of Mie (n,m) intermolecular potential energy function based on the shape of molecules , 1980 .

[8]  J. Ravey,et al.  Asphaltene macrostructure by small angle neutron scattering , 1988 .

[9]  Lorien Y. Pratt,et al.  Transferring previously learned back-propagation neural networks to new learning tasks , 1993 .

[10]  Martin T. Hagan,et al.  Neural network design , 1995 .

[11]  A. Firoozabadi,et al.  Thermodynamic micellizatin model of asphaltene precipitation from petroleum fluids , 1996 .

[12]  A. Leach Molecular Modelling: Principles and Applications , 1996 .

[13]  J. Murgich,et al.  Molecular Recognition and Molecular Mechanics of Micelles of Some Model Asphaltenes and Resins , 1996 .

[14]  G. Mansoori,et al.  PREDICTION OF THE PHASE BEHAVIOR OF ASPHALTENE MICELLE / AROMATIC HYDROCARBON SYSTEMS , 1998 .

[15]  M. Scarsella,et al.  Colloidal Structural Evolution from Stable to Flocculated State of Asphaltene Solutions and Heavy Crudes , 1998 .

[16]  O. Mullins,et al.  Asphaltene Molecular Size and Structure , 1999 .

[17]  Guoqiang Peter Zhang,et al.  Neural networks for classification: a survey , 2000, IEEE Trans. Syst. Man Cybern. Part C.

[18]  INTERACTION ENERGY IN MAYA-OIL ASPHALTENES: A MOLECULAR MECHANICS STUDY , 2001 .

[19]  P. Sánchez,et al.  A theory of phase separation in asphaltene-micellar solutions , 2001 .

[20]  L. Barré,et al.  Aggregated structure of flocculated asphaltenes , 2001 .

[21]  M. José-Yacamán,et al.  Fullerenic structures derived from oil asphaltenes , 2002 .

[22]  Shinya Sato,et al.  Molecular Dynamics Simulation of the Heat-Induced Relaxation of Asphaltene Aggregates , 2003 .

[23]  Kristen Bell DeTienne,et al.  Neural Networks as Statistical Tools for Business Researchers , 2003 .

[24]  J. Pacheco-Sánchez,et al.  Asphaltene Aggregation under Vacuum at Different Temperatures by Molecular Dynamics , 2003 .

[25]  V. Castaño,et al.  Naturally produced carbon nanotubes , 2003 .

[26]  平田 文男 Molecular theory of solvation , 2003 .

[27]  A. Gil-Villegas,et al.  Molecular View of the Asphaltene Aggregation Behavior in Asphaltene−Resin Mixtures , 2003 .

[28]  J. Pacheco-Sánchez,et al.  Morphology of Aggregated Asphaltene Structural Models , 2004 .

[29]  Shinya Sato,et al.  Characterization of Asphaltene Aggregates Using X-ray Diffraction and Small-Angle X-ray Scattering , 2004 .

[30]  P. Seidl,et al.  Conformational search and dimerization study of average structures of asphaltenes , 2005 .

[31]  Y. Ruiz-Morales,et al.  Calculation of the Interaction Potential Curve between Asphaltene−Asphaltene, Asphaltene−Resin, and Resin−Resin Systems Using Density Functional Theory , 2006 .

[32]  A. Gross,et al.  Descriptions of surface chemical reactions using a neural network representation of the potential-energy surface , 2006 .

[33]  P. Badot,et al.  Application of chitosan, a natural aminopolysaccharide, for dye removal from aqueous solutions by adsorption processes using batch studies: A review of recent literature , 2008 .

[34]  Multiscale modelling of asphaltene disaggregation , 2008 .

[35]  Eleni I. Vlahogianni,et al.  Statistical methods versus neural networks in transportation research: Differences, similarities and some insights , 2011 .

[36]  L. Barré,et al.  Structure and dynamic properties of colloidal asphaltene aggregates. , 2012, Langmuir : the ACS journal of surfaces and colloids.

[37]  Klaus-Robert Müller,et al.  Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.

[38]  E. Boek,et al.  Experimental Investigation of Asphaltene Deposition in Capillary Flow , 2012 .

[39]  W. Welch,et al.  Effect of asphaltene structure on association and aggregation using molecular dynamics. , 2013, The journal of physical chemistry. B.

[40]  H. S. Fogler,et al.  Multiscale scattering investigations of asphaltene cluster breakup, nanoaggregate dissociation, and molecular ordering. , 2013, Langmuir : the ACS journal of surfaces and colloids.

[41]  G. Mansoori,et al.  Tricritical phenomena in asphaltene/aromatic hydrocarbon systems , 2013 .

[42]  A. Galindo,et al.  Aspects of Asphaltene Aggregation Obtained from Coarse-Grained Molecular Modeling , 2015 .

[43]  J. Conway,et al.  A rare isocyanide derived from an unprecedented neutral yttrium(ii) bis(amide) complex , 2023, Chemical science.

[44]  G. Mansoori,et al.  Molecular dynamics studies of interaction between asphaltenes and solvents , 2017, 1805.10555.

[45]  Timothy Marler,et al.  Neural network for regression problems with reduced training sets , 2017, Neural Networks.

[46]  B. Hoyos,et al.  A stochastic method for asphaltene structure formulation from experimental data: avoidance of implausible structures. , 2017, Physical chemistry chemical physics : PCCP.

[47]  G. Mansoori,et al.  A new insight into asphaltenes aggregation onset at molecular level in crude oil (an MD simulation study) , 2018 .

[48]  G. Mansoori,et al.  Molecular insights on the interfacial and transport properties of supercritical CO2/brine/crude oil ternary system , 2018, Journal of Molecular Liquids.

[49]  W. Welch,et al.  Molecular polydispersity improves prediction of asphaltene aggregation , 2018 .