Molecular simulation of crystal growth in <i>n</i>-eicosane

Waheed, Numan; Lavine, Marc S.; Rutledge, Gregory C.

doi:10.1063/1.1430744

Cited by 112 publications

(124 citation statements)

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“…34 This discrepancy cannot be due to the difference in temperature alone. We have traced this deviation in part to the overly large time step of 5 fs used in that work; such a large time step was reported by Waheed et al 37 to increase the chain relaxation time by only 10%, but its effect in suppressing nucleation is apparently more dramatic, compared to the more accurate rRESPA scheme used in this work. Our estimate for nucleation rate is also higher than the rate of 105 × 10 30 m −3 s −1 reported by Anwar et al at 250 K. 43 In this case, we suspect that the discrepancy is due to the application of the MFPT analysis method proposed by Wedekind et al 14 which employs the single-exponential approximation; as shown for our system in Table I, the singleexponential approximation results in an underestimation of the true nucleation rate.…”

Section: Case Study: N-eicosane Nucleationmentioning

confidence: 99%

“…34,35 The system consisted of 336 C20 molecules, with a united atom (UA) representation in which each UA represents a CH 3 or CH 2 group. The force field was initially proposed by Paul, Yoon, and Smith 36 with subsequent modifications by Waheed et al, 37,38 and includes bond stretching, bond angle bending, torsion, and non-bonded Lennard-Jones forces. We used a rRESPA integration scheme 39 with a time step of 2 fs for bonded interactions and 4 fs for intermolecular interactions.…”

Section: Case Study: N-eicosane Nucleationmentioning

confidence: 99%

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Analysis of nucleation using mean first-passage time data from molecular dynamics simulation

Nicholson

2016

The Journal of Chemical Physics

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We introduce a method for the analysis of nucleation using mean first-passage time (MFPT) statistics obtained by molecular dynamics simulation. The method is based on the Becker-Döring model for the dynamics of a nucleation-mediated phase change and rigorously accounts for the system size dependence of first-passage statistics. It is thus suitable for the analysis of systems in which the separation between time scales for nucleation and growth is small, due to either a small free energy barrier or a large system size. The method is made computationally practical by an approximation of the first-passage time distribution based on its cumulant expansion. Using this approximation, the MFPT of the model can be fit to data from molecular dynamics simulation in order to estimate valuable kinetic parameters, including the free energy barrier, critical nucleus size, and monomer attachment pre-factor, as well as the steady-state rates of nucleation and growth. The method is demonstrated using a case study on nucleation of n-eicosane crystals from the melt. For this system, we found that the observed distribution of first-passage times do not follow an exponential distribution at short times, rendering it incompatible with the assumptions made by some other methods. Using our method, the observed distribution of first-passage times was accurately described, and reasonable estimates for the kinetic parameters and steady-state rates of nucleation and growth were obtained. C 2016 AIP Publishing LLC. [http://dx

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Section: Case Study: N-eicosane Nucleationmentioning

confidence: 99%

Section: Case Study: N-eicosane Nucleationmentioning

confidence: 99%

Analysis of nucleation using mean first-passage time data from molecular dynamics simulation

Nicholson

2016

The Journal of Chemical Physics

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“…We have used a united atom model for polyethylene in which the chains consist of monomers that represent CH 2 and CH 3 groups [41,55]. The system parameters were the same as in ref.…”

Section: Model and Order Parametersmentioning

confidence: 99%

Crystallization of polyethylene: A molecular dynamics simulation study of the nucleation and growth mechanisms

Anwar

Schilling

2015

Polymer

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a b s t r a c tWe have performed molecular dynamics simulations to study the mechanism of crystallization from an undercooled polyethylene (C500) melt. We observe that crystal nucleation is initiated by the alignment of chain segments, which is followed by straightening of the chains and densification. Growth procedes via alignment of segments, which are in the vicinity of the growth front, with the chains in the crystalline lamella. Once chains are attached, the lamella thickens by sliding of the segments along the long axis of the chain from the amorphous regions into the crystalline regions. We do not observe the formation of any folded precursors.

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“…[35][36][37][38] However, we shall not primarily examine the thermodynamic background of these rates here. Rather, we use a procedure analogous to the one described above to model different particle shapes and different growth dimensionalities.…”

Section: ͑7͒mentioning

confidence: 99%

Crystal shapes and crystallization in continuum modeling

Hütter

Armstrong

2004

Physics of Fluids

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A crystallization model appropriate for application in continuum modeling of complex processes is presented. As an extension to the previously developed Schneider equations [W. Schneider, A. Köppel, and J. Berger, "Non-isothermal crystallization of polymers," Int. Polym. Proc. 2, 151 (1988)], the model presented here allows one to account for the growth of crystals of various shapes and to distinguish between one-, two-, and three-dimensional growth, e.g., between rod-like, plate-like, and sphere-like growth. It is explained how a priori knowledge of the shape and growth processes is to be built into the model in a compact form and how experimental data can be used in conjunction with the dynamic model to determine its growth parameters. The model is capable of treating transient processing conditions and permits their straightforward implementation. By using thermodynamic methods, the intimate relation between the crystal shape and the driving forces for phase change is highlighted. All these capabilities and the versatility of the method are made possible by the consistent use of four structural variables to describe the crystal shape and number density, irrespective of the growth dimensionality.

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Molecular simulation of crystal growth in n-eicosane

Abstract: Articles you may be interested inDynamic structure of methane/n-nonane clusters during nucleation and growth

Cited by 112 publications

References 38 publications

Analysis of nucleation using mean first-passage time data from molecular dynamics simulation

Analysis of nucleation using mean first-passage time data from molecular dynamics simulation

Crystallization of polyethylene: A molecular dynamics simulation study of the nucleation and growth mechanisms

Crystal shapes and crystallization in continuum modeling

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