A single-site anisotropic soft-core model for the study of phase behavior of soft rodlike particles

Li, Zhanwei; Liu, YuHua; Liu, Ying-Tao; Lu, Zhong‐Yuan

doi:10.1007/s11426-011-4333-8

Cited by 6 publications

(6 citation statements)

References 51 publications

(92 reference statements)

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“…The expressions of calculation (

{\overset{R}{true}}_{i}

{\overset{R}{true}}_{j}

{\overset{n}{true}}_{i}

{\overset{n}{true}}_{j}

) in Kernel 2 for translational force and torque are dependent on specific anisotropic potential (details can be found in Refs. ). The equations of both translational and rotational motion are integrated via a half‐step leapfrog algorithm.…”

Section: Characteristic Coarse‐grained Modelsmentioning

confidence: 97%

“…To simulate hierarchically self‐assembled superstructures of anisotropic particles, a novel anisotropic particle model was proposed by Li et al To be specific, the packing and the self‐assembly of disk‐like, rod‐like, Janus, and triblock Janus particles can be studied by using different anisotropic potentials . Due to the unique feature of being noncentrosymmetric, the self‐assembly patterns of anisotropic particles show great diversity .…”

Section: A Sketch Of Galamostmentioning

confidence: 99%

“…By adding two degrees of freedom of rotation, our one‐site anisotropic particle model can be used to describe disk‐like, rod‐like, diblock and triblock Janus particles. We have successfully examined the packing and the self‐assembly of anisotropic particles with this model …”

Section: Characteristic Coarse‐grained Modelsmentioning

confidence: 99%

“…

{boldr}_{i j} = {boldr}_{i} - {boldr}_{j}

is the interparticle vector. In rod‐like particle model, the anisotropic factor is

f = sin θ_{i} sin θ_{j}

where

θ_{i}

is the angle between

{boldn}_{i}

and the interparticle vector

{boldr}_{j i} = - {boldr}_{i j}

θ_{j}

is the angle between

{boldn}_{j}

and

{boldr}_{i j}

. For diblock and triblock Janus particles, we take an anisotropic potential with attractive tail,

U_{i j} = \frac{α_{i j}^{normalR}}{2} {(1 - r_{i j})}^{2} - f^{ν} \frac{α_{i j}^{normalA}}{2} (r_{i j} - r_{i j}^{2}),

where the magnitude of

α_{i j}^{normalR}

controls the strength of repulsion,

α_{i j}^{normalA}

controls the strength of attraction, and ν controls the angular width of attraction.…”

Section: Characteristic Coarse‐grained Modelsmentioning

confidence: 99%

“…The parallel CPU codes for one‐site anisotropic particle model had been well established before . By porting the algorithms from CPU code to GALAMOST, the performance of this anisotropic particle model has been promoted greatly.…”

Section: Performance and Validationmentioning

confidence: 99%

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GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

et al. 2013

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GALAMOST [graphics processing unit (GPU)-accelerated large-scale molecular simulation toolkit] is a molecular simulation package designed to utilize the computational power of GPUs. Besides the common features of molecular dynamics (MD) packages, it is developed specially for the studies of self-assembly, phase transition, and other properties of polymeric systems at mesoscopic scale by using some lately developed simulation techniques. To accelerate the simulations, GALAMOST contains a hybrid particle-field MD technique where particle–particle interactions are replaced by interactions of particles with density fields. Moreover, the numerical potential obtained by bottom-up coarse-graining methods can be implemented in simulations with GALAMOST. By combining these force fields and particle-density coupling method in GALAMOST, the simulations for polymers can be performed with very large system sizes over long simulation time. In addition, GALAMOST encompasses two specific models, that is, a soft anisotropic particle model and a chain-growth polymerization model, by which the hierarchical self-assembly of soft anisotropic particles and the problems related to polymerization can be studied, respectively. The optimized algorithms implemented on the GPU, package characteristics, and benchmarks of GALAMOST are reported in detail.

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“…The expressions of calculation (

{\overset{R}{true}}_{i}

{\overset{R}{true}}_{j}

{\overset{n}{true}}_{i}

{\overset{n}{true}}_{j}

Section: Characteristic Coarse‐grained Modelsmentioning

confidence: 97%

Section: A Sketch Of Galamostmentioning

confidence: 99%

Section: Characteristic Coarse‐grained Modelsmentioning

confidence: 99%

“…

{boldr}_{i j} = {boldr}_{i} - {boldr}_{j}

is the interparticle vector. In rod‐like particle model, the anisotropic factor is

f = sin θ_{i} sin θ_{j}

where

θ_{i}

is the angle between

{boldn}_{i}

and the interparticle vector

{boldr}_{j i} = - {boldr}_{i j}

θ_{j}

is the angle between

{boldn}_{j}

and

{boldr}_{i j}

. For diblock and triblock Janus particles, we take an anisotropic potential with attractive tail,

U_{i j} = \frac{α_{i j}^{normalR}}{2} {(1 - r_{i j})}^{2} - f^{ν} \frac{α_{i j}^{normalA}}{2} (r_{i j} - r_{i j}^{2}),

where the magnitude of

α_{i j}^{normalR}

controls the strength of repulsion,

α_{i j}^{normalA}

controls the strength of attraction, and ν controls the angular width of attraction.…”

Section: Characteristic Coarse‐grained Modelsmentioning

confidence: 99%

Section: Performance and Validationmentioning

confidence: 99%

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GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

et al. 2013

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A mini review of the recent progress in coarse-grained simulation of polymer systems

Gao,

Yu,

Zhang

et al. 2024

Chinese Journal of Structural Chemistry

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A versatile model for soft patchy particles with various patch arrangements

Zhu

et al. 2016

Soft Matter

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We propose a simple and general mesoscale soft patchy particle model, which can felicitously describe the deformable and surface-anisotropic characteristics of soft patchy particles. This model can be used in dynamics simulations to investigate the aggregation behavior and mechanism of various types of soft patchy particles with tunable number, size, direction, and geometrical arrangement of the patches. To improve the computational efficiency of this mesoscale model in dynamics simulations, we give the simulation algorithm that fits the compute unified device architecture (CUDA) framework of NVIDIA graphics processing units (GPUs). The validation of the model and the performance of the simulations using GPUs are demonstrated by simulating several benchmark systems of soft patchy particles with 1 to 4 patches in a regular geometrical arrangement. Because of its simplicity and computational efficiency, the soft patchy particle model will provide a powerful tool to investigate the aggregation behavior of soft patchy particles, such as patchy micelles, patchy microgels, and patchy dendrimers, over larger spatial and temporal scales.

show abstract

A single-site anisotropic soft-core model for the study of phase behavior of soft rodlike particles

Cited by 6 publications

References 51 publications

GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

A mini review of the recent progress in coarse-grained simulation of polymer systems

A versatile model for soft patchy particles with various patch arrangements

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