Atomistic Simulations to Compute Surface Properties of Poly(<i>N</i>-vinyl-2-pyrrolidone) (PVP) and Blends of PVP/Chitosan

Prathab, B.; Aminabhavi, Tejraj M.

doi:10.1021/la063228u

Cited by 32 publications

(20 citation statements)

References 48 publications

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“…Polymer assemblies containing three chains of PVP (20 monomer units) in its atatic stereochemical structure and three chains of chitosan (10 monomer units) were generated for the simulation of a 50/50 composition of the blend as previously conducted 14. For the simulation of PVP/chitosan 20/80, 33/67, 67/33, and 80/20 blends, three chains of each polymer were also used, but the numbers of monomer units were 20/40, 20/20, 40/10, and 80/10, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…Each generated polymer chain was minimized using the Discover module, and the blend systems were built inside a box with periodic boundary conditions constructed using the amorphous cell module of the Materials Studio. The density of the blend system was estimated from densities of the pure polymers, that is, 1.04 g/cm 3 for PVP and 0.67 g/cm 3 for chitosan 14. Thus, the simulation cell densities for PVP/chitosan 20/80, 33/67, 50/50, 67/33, and 80/20 were 0.744, 0.792, 0.855, 0.917, and 0.966 g/cm 3 , respectively.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Molecular modeling simulation and experimental measurements to characterize chitosan and poly(vinyl pyrrolidone) blend interactions

Suknuntha

Tantishaiyakul

Vao‐soongnern

et al. 2008

J Polym Sci B Polym Phys

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Blends of chitosan and poly(vinyl pyrrolidone) (PVP) have a high potential for use in various biomedical applications and in advanced drug‐delivery systems. Recently, the physical and chemical properties of these blends have been extensively characterized. However, the molecular interaction between these two polymers is not fully understood. In this study, the intermolecular interaction between chitosan and PVP was experimentally investigated using 13C cross‐polarization magic angle‐spinning nuclear magnetic resonance (13C CP/MAS NMR) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). According to these experimental results, the interaction between the polymers takes place through the carbonyl group of PVP and either the OHC6, OHC3, or NHC2 of chitosan. In an attempt to identify the interacting groups of these polymers, molecular modeling simulation was performed. Molecular simulation was able to clarify that the hydrogen atom of OHC6 of chitosan was the most favorable site to form hydrogen bonding with the oxygen atom of CO of PVP, followed by that of OHC3, whereas that of NHC2 was the weakest proton donor group. The nitrogen atom of PVP was not involved in the intermolecular interaction between these polymers. Furthermore, the interactions between these polymers are higher when PVP concentrations are lower, and interactions decrease with increasing amounts of PVP. © 2008 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 46: 1258–1264, 2008

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Molecular modeling simulation and experimental measurements to characterize chitosan and poly(vinyl pyrrolidone) blend interactions

Suknuntha

Tantishaiyakul

Vao‐soongnern

et al. 2008

J Polym Sci B Polym Phys

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“…To investigate the effect of initial drug concentration on the loading efficiency of the drug, understanding the interactions between the components of the studied system is essential. Previous simulation studies indicated that condensed-phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field effectively and accurately represents the molecular interactions [31][32][33]. Therefore, in this work the COMPASS force field was used to represent all the interactions between the polymer, as the carrier, and the drug in the studied drug delivery system.…”

Section: Simulation Methodsmentioning

confidence: 99%

Molecular dynamics simulation study of chitosan and gemcitabine as a drug delivery system

2015

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By using molecular dynamics (MD) simulation, biodegradable biopolymer chitosan as a carrier for the drug gemcitabine was investigated and the effect of three initial drug concentrations (10, 40, and 80%) on its loading efficiency was studied. Then water was added to the systems of drug and biopolymer and the effects of water on the interactions of drug and chitosan and on the drug loading efficiency were examined. From the results it was found that the maximum loading of the drug occurred at 40% of the drug concentration. The radial distribution function calculations indicated that in the absence of water molecules, the drug molecules were located at shorter distance from chitosan and the loading efficiency of the drug in these systems was higher.

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“…Therefore, atomistic simulations of blends are still relatively scarce. So far, most studies have focussed on miscibility aspects [174][175][176][177][178][179][180][181][182][183][184]. Already early on, atomistic and mesoscopic simulations were combined in multiscale studies: Atomistic simulations were used to determine the Flory-Huggins χ -parameter, coarse-grained methods were then applied to study large-scale aspects of phase separation [185][186][187][188][189][190][191] or mesophase formation [192].…”

Section: Atomistic Modelsmentioning

confidence: 99%

Theory and Simulation of Multiphase Polymer Systems

Schmid

2011

Handbook of Multiphase Polymer Systems

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The theory of multiphase polymer systems has a venerable tradition. The 'classical' theory of polymer demixing, the Flory-Huggins theory, was developed in the 1940s [1,2]. It is still the starting point for most current approaches -be they improved theories for polymer (im)miscibility that take into account the microscopic structure of blends more accurately, or sophisticated field theories that allow to study inhomogeneous multicomponent systems of polymers with arbitrary architectures in arbitrary geometries. In contrast, simulations of multiphase polymer systems are quite young. They are still limited by the fact that one must simulate a large number of large molecules in order to obtain meaningful results. Both powerful computers and smart modeling and simulation approaches are necessary to overcome this problem.In the limited space of this chapter, we can only give a taste of the state-of-the-art in both areas, theory and simulation. Since the theory has reached a fairly mature stage by now, many aspects of it are covered in textbooks on polymer physics [3][4][5][6][7][8][9]. The information on the state-of-the art of simulations is much more scattered. This is why we have put some effort into putting together a representative list of references in this area -which is of course still far from complete.The chapter is organized as follows. In Section II, we briefly introduce some basic concepts of polymer theory. The purpose of this part is to make the chapter accessible to readers who are not very familiar with polymer physics; it can safely be skipped by the others. Section III is devoted to the theory of multiphase polymer systems. We recapitulate the Flory-Huggins theory and introduce in particular the concept of the Flory interaction parameter (the χ parameter), which is a central ingredient in most theoretical descriptions of multicomponent polymer systems. Then we focus on one of the most successful mean-field theories for inhomogeneous (co)polymer blends, the self-consistent field theory. We sketch the main idea, discuss various Handbook of Multiphase Polymer Systems, First Edition. Edited by Abderrahim Boudenne, Laurent Ibos, Yves Candau, and Sabu Thomas.

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Atomistic Simulations to Compute Surface Properties of Poly(N-vinyl-2-pyrrolidone) (PVP) and Blends of PVP/Chitosan

Cited by 32 publications

References 48 publications

Molecular modeling simulation and experimental measurements to characterize chitosan and poly(vinyl pyrrolidone) blend interactions

Molecular modeling simulation and experimental measurements to characterize chitosan and poly(vinyl pyrrolidone) blend interactions

Molecular dynamics simulation study of chitosan and gemcitabine as a drug delivery system

Theory and Simulation of Multiphase Polymer Systems

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