Universal Nucleation Behavior of Sheared Systems

Goswami, Amrita; Dalal, Indranil Saha; Singh, Jayant K.

doi:10.1103/physrevlett.126.195702

Cited by 14 publications

(41 citation statements)

References 102 publications

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“…Figure 3 depicts the performance of the standard seeding approach, as implemented by Espinosa et al [78,79], for the atomistic models TIP4P/2005, TIP4P/Ice and the coarse-grained monatomic (mW) water model. The percent supercooling for every model is defined as ∆T % = Tm−T Tm × 100 where T m is the melting point [36]. Evidently, seeding method calculations using the atomistic water models have yielded remarkably good agreement with experimental data for water.…”

Section: Cnt and The Seeding Methodsmentioning

confidence: 98%

“…∆µ 0 is the chemical potential difference between the thermodynamically stable crystal phase and the metastable liquid phase when no shear is applied, σ 0 is the surface tension or the interfacial free energy of the nucleus at zero shear, v is the volume of one molecule in the crystal phase, G is the shear modulus of the nucleus. We define a characteristic time τ [36] as τ = η G , such that η is the fluid viscosity. β = 1 + 7 24 (τ γ) 2 is a corrective "shape factor" accounting for the shear-induced change in shape of the nucleus from a sphere to an ellipsoid.…”

Section: Rates As Functions Of the Shear Rate In The Cluster Radius S...mentioning

confidence: 99%

“…Goswami et al [36] proposed a formalism, similar in spirit to that of Mura et al [30]. Seeded simulations of the quiescent metastable liquid form the backbone of this formulation, wherein the shear rate appears as an explicit variable in the modified CNT expressions.…”

Section: Rates As Functions Of the Shear Rate In The Cluster Size Spacementioning

confidence: 99%

“…(23) suggest that, at a particular temperature, there exists a maximum in the nucleation rate at a specific shear rate, γopt . An estimate of the dimensionless optimal shear rate, τ γopt can be derived analytically, for 6c 2 Gk B T N * 0 v (D0η) 2 << 1 [36]:…”

Section: Rates As Functions Of the Shear Rate In The Cluster Size Spacementioning

confidence: 99%

“…Certain results indicate that shear impedes and inhibits nucleation [15,16], while others suggest that flow induces or enhances nucleation [17][18][19][20][21][22][23]. These seemingly conflicting results can be reconciled within a broader context, bolstered by experimental [24,25] and computational [26][27][28][29][30][31][32][33][34][35][36] studies which imply that the nucleation rate is non-monotonic with shear. A linear flow field tends to deform incipient clusters.…”

Section: Introductionmentioning

confidence: 99%

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Homogeneous Nucleation of Sheared Liquids: Advances and Insights from Simulations and Theory

Goswami,

Singh

2021

Preprint

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One of the most ubiquitous and technologically important phenomena in nature is the nucleation of homogeneous flowing systems. The microscopic effects of shear on a nucleating system are still imperfectly understood, although in recent years a consistent picture has emerged. The opposing effects of shear can be split into two major contributions for simple liquids: increase of the energetic cost of nucleation, and enhancement of the kinetics. In this review, we describe the latest computational and theoretical techniques which have been developed over the past two decades. We collate and unify the overarching influences of shear, temperature, and supersaturation on the process of homogeneous nucleation. Experimental techniques and capabilities are discussed, against the backdrop of results from simulations and theory. Although we primarily focus on simple liquids, we also touch upon the sheared nucleation of more complex systems, including glasses and polymer melts. We speculate on the promising directions and possible advances that could come to fruition in the future.

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Section: Cnt and The Seeding Methodsmentioning

confidence: 98%

Section: Rates As Functions Of the Shear Rate In The Cluster Radius S...mentioning

confidence: 99%

Section: Rates As Functions Of the Shear Rate In The Cluster Size Spacementioning

confidence: 99%

Section: Rates As Functions Of the Shear Rate In The Cluster Size Spacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Homogeneous Nucleation of Sheared Liquids: Advances and Insights from Simulations and Theory

Goswami,

Singh

2021

Preprint

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Recent progress in flow‐induced polymer crystallization

Nie

Fan

Cao

et al. 2022

Journal of Polymer Science

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During industrial processing, such as film blowing and injection molding, semicrystalline polymers have to be subjected to external flow. Flow changes the nucleation rate, crystal morphology and polymorphism of polymers. As flow can be tunable, polymeric products with different macroscopic performance and versatile applications can be obtained. Understanding polymer crystallization with the presence of flow, or namely flow-induced crystallization (FIC), is crucial to optimize polymer processing parameters and to understand phase transition under far-from equilibrium conditions, as FIC is essentially a typical nonequilibrium process. Current review aims to summarizes recent achievements of FIC during last five years from three aspects: theory, experiment and simulation. First, we present the FIC model and theory, including the classical conformational entropy reduction model, the newly developed POLYdisperse STRain Accelerated Nucleation Dynamics (PolySTRAND) Model and uFIC Model. Then we discuss the FIC experiments under both well-controlled flow and complex processing conditions. Finally, we show the recent advance of FIC in computer simulation. With the fast development in modeling efficiency, more detailed nucleation and structure transition processes during FIC can be obtained, which promote the study of molecular mechanisms of FIC.

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