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Frontiers of Chemical Science and Engineering

ISSN 2095-0179

ISSN 2095-0187(Online)

CN 11-5981/TQ

Postal Subscription Code 80-969

2018 Impact Factor: 2.809

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Front Chem Sci Eng    2013, Vol. 7 Issue (1) : 49-54    https://doi.org/10.1007/s11705-013-1307-8
RESEARCH ARTICLE
Molecular level simulations on multi-component systems —a morphology prediction method
C. SCHMIDT(), J. ULRICH
Center for Engineering Science, Thermal Process Engineering, Martin Luther University Halle-Wittenberg, D-06099 Halle (Saale), Germany
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Abstract

The crystal morphology grown from a solution composed of an organic solvent, solute and additive can be predicted reliably by a computational method. Modeling the supersaturated solution as liquid phase is achieved by employing commercial software. The molecular composition of this solution is a required input parameter. The face specific diffusion coefficient of the solid (crystal surface) and liquid (solution) system is determined using the molecular dynamics procedure. The obtained diffusion coefficient is related to the specific face growth rate via the attachment energy of the pure morphology. The significant improvements are achieved in the morphology prediction because the investigation on the face growth rates in a complex growth environment (as multi-component solutions with additives) can be carried out based on the diffusion coefficients.
Keywords crystallization      morphology      molecular dynamics      solution     
Corresponding Author(s): SCHMIDT C.,Email:christiane.schmidt@iw.uni-halle.de   
Issue Date: 05 March 2013
 Cite this article:   
C. SCHMIDT,J. ULRICH. Molecular level simulations on multi-component systems —a morphology prediction method[J]. Front Chem Sci Eng, 2013, 7(1): 49-54.
 URL:  
https://academic.hep.com.cn/fcse/EN/10.1007/s11705-013-1307-8
https://academic.hep.com.cn/fcse/EN/Y2013/V7/I1/49
Fig.1  Succinic acid molecule (left) and unit cell (right)
Fig.1  Succinic acid molecule (left) and unit cell (right)
Fig.2  Computed morphologies of vapor grown succinic acid crystals: BFDH (left) and AE morphology (right)
Fig.2  Computed morphologies of vapor grown succinic acid crystals: BFDH (left) and AE morphology (right)
Fig.3  Computed morphologies of succinic acid crystals modeled using the build-in (left) [] and the surface docking (right) methods
Fig.3  Computed morphologies of succinic acid crystals modeled using the build-in (left) [] and the surface docking (right) methods
Fig.4  Computed morphologies of succinic acid crystals modeled using the layer docking method via attachment energy (left) and the diffusion coefficient (right)
Fig.4  Computed morphologies of succinic acid crystals modeled using the layer docking method via attachment energy (left) and the diffusion coefficient (right)
FaceSurface conformation
(020)(011)(100)
Tab.1  Molecular structure of selected surfaces of a succinic acid crystal
Fig.6  Binding energy differences, attachment energy of the pure morphology and modified attachment energy of the succinic acid crystal
Fig.6  Binding energy differences, attachment energy of the pure morphology and modified attachment energy of the succinic acid crystal
Fig.7  Potential energy of the amorphous cell at various simulations stages in the optimization procedure (NVE: N-constant number of particles, V-constant volume, E-constant energy; NPT: N-constant number of particles, P-constant pressure, T-constant temperature)
Fig.7  Potential energy of the amorphous cell at various simulations stages in the optimization procedure (NVE: N-constant number of particles, V-constant volume, E-constant energy; NPT: N-constant number of particles, P-constant pressure, T-constant temperature)
Fig.8  Diffusion coefficients computed for the faces (100) (left) and (011) (right) of a succinic acid crystal
Fig.8  Diffusion coefficients computed for the faces (100) (left) and (011) (right) of a succinic acid crystal
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