Monte Carlo simulations of fluid vesicles with in-plane orientational ordering

Ramakrishnan, N.; Kumar, P. B. Sunil; Ipsen, John Hjort

doi:10.1103/physreve.81.041922

Cited by 90 publications

(161 citation statements)

References 43 publications

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“…The principal directions and the local surface normal form a local orthonormal frame of reference (Darboux frame). The details of the calculation of the discrete shape operator are given in [35]. The discretised form of the Helfrich's free energy eq.…”

Section: Triangulated Surface Modelmentioning

confidence: 99%

Numerical insights into the phase diagram of p-atic membranes with spherical topology

et al. 2017

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Abstract.The properties of self-avoiding p-atic membranes restricted to spherical topology have been studied by Monte Carlo simulations of a triangulated random surface model. Spherically shaped p-atic membranes undergo a Kosterlitz-Thouless transition as expected with topology induced mutually repelling disclinations of the p-atic ordered phase. For flexible membranes the phase behaviour bears some resemblance to the spherically shaped case with a p-atic disordered crumpled phase and p-atic ordered, conformationally ordered (crinkled) phase separated by a KT-like transition with proliferation of disclinations. We confirm the proposed buckling of disclinations in the p-atic ordered phase, while the expected associated disordering (crumpling) transition at low bending rigidities is absent in the phase diagram.

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Section: Triangulated Surface Modelmentioning

confidence: 99%

Numerical insights into the phase diagram of p-atic membranes with spherical topology

et al. 2017

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“…[22] It has been shown that the entropy dominated branched shapes, the equilibrium shapes of flexible surfaces(κ = 0), are cut off by order induced membrane stiffening. These observations add support to the hypothesis of membrane shape stabilization by protein-lipid interactions.…”

Section: Frustrated In-plane Order and Membrane Morphologymentioning

confidence: 99%

“…We will outline, in this article, the basic steps to compute these surface geometrical quantifiers. [22] Computing surface quantifiers…”

Section: In-plane Orientational Ordermentioning

confidence: 99%

“…The additional Monte Carlo move involving the in-plane order is given in Figure 2. [22] The total energy of the field decorated surface, of spherical topology(genus, g = 0), is H tot = H sur +H N M +H p−atic . In the ground state of H tot , the p-atic field is frustrated by the topology of the embedding surface and has in it χp defects, each of topological charge 1/p.…”

Section: Frustrated In-plane Order and Membrane Morphologymentioning

confidence: 99%

“…S v (v) is constructed in the global cartesian frame and a Householder transformation, [22,25] rotates the operator in Equation (3) to its tangent frame and the resulting matrix is a 2 × 2 minor. This transformation gives a computationally efficient route to calculate the eigenspectrum of Equation (3) …”

Section: In-plane Orientational Ordermentioning

confidence: 99%

See 2 more Smart Citations

Modeling Anisotropic Elasticity of Fluid Membranes

Ramakrishnan¹,

Kumar²,

Ipsen³

2011

Macro Theory & Simulations

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The biological membrane, which compartmentalizes the cell and its organelles, exhibit wide variety of macroscopic shapes of varying morphology and topology.s A systematic understanding of the relation of membrane shapes to composition, external field, environmental conditions etc. have important biological relevance. Here we review the triangulated surface model, used in the macroscopic simulation of membranes and the associated Monte Carlo (DTMC) methods. New techniques to calculate surface quantifiers, that will facilitate the study of additional in-plane orientational degrees of freedom, has been introduced. The mere presence of a polar and nematic fields in the ordered phase drives the ground state conformations of the membrane to a cylinder and tetrahedron respectively.

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Vesicles and Vesicle Fusion: Coarse-Grained Simulations

Shillcock

2012

Methods in Molecular Biology

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Biological cells are highly dynamic, and continually move material around their own volume and between their interior and exterior. Much of this transport encapsulates the material inside phospholipid vesicles that shuttle to and from, fusing with, and budding from, other membranes. A feature of vesicles that is crucial for this transport is their ability to fuse to target membranes and release their contents to the distal side. In industry, some personal care products contain vesicles to help transport reagents across the skin, and research on drug formulation shows that packaging active compounds inside vesicles delays their clearance from the blood stream. In this chapter, we survey the biological role and physicochemical properties of phospholipids, and describe progress in coarse-grained simulations of vesicles and vesicle fusion. Because coarse-grained simulations retain only those molecular details that are thought to influence the large-scale processes of interest, they act as a model embodying our current understanding. Comparing the predictions of these models with experiments reveals the importance of the retained microscopic details and also the deficiencies that can suggest missing details, thereby furthering our understanding of the complex dynamic world of vesicles.

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Monte Carlo simulations of fluid vesicles with in-plane orientational ordering

Cited by 90 publications

References 43 publications

Numerical insights into the phase diagram of p-atic membranes with spherical topology

Numerical insights into the phase diagram of p-atic membranes with spherical topology

Modeling Anisotropic Elasticity of Fluid Membranes

Vesicles and Vesicle Fusion: Coarse-Grained Simulations

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