On the phase diagram of Mackay icosahedra

Mravlak, Marko; Schilling, Tanja

doi:10.1063/1.5031418

Cited by 2 publications

(3 citation statements)

References 40 publications

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“…Simulations with parameters in either end of the parameter range are inefficient because particles get easily stuck in their neighbor shell (Figure ). Shape plays an important role for the optimal choice of μ. Icosahedra prefer more translations (μ ≳ 0), which is explained by the presence of a rotator phase prior to crystallization . Tetrahedra prefer more rotations (μ ≲ 1) due to their strong preference for face-to-face contact .…”

Section: Implementation and Parameterizationmentioning

confidence: 99%

“…Shape plays an important role for the optimal choice of μ. Icosahedra prefer more translations (μ ≳ 0), which is explained by the presence of a rotator phase prior to crystallization. 38 Tetrahedra prefer more rotations (μ ≲ 1) due to their strong preference for face-to-face contact. 39 In general, we expect nearly spherical polyhedra to rotate easily and highly anisotropic polyhedra to preferentially align face to face.…”

Section: Implementation and Parameterizationmentioning

confidence: 99%

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Newtonian Event-Chain Monte Carlo and Collision Prediction with Polyhedral Particles

Klement

Lee

Anderson

et al. 2021

J. Chem. Theory Comput.

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Polyhedral nanocrystals are building blocks for nanostructured materials that find applications in catalysis and plasmonics. Synthesis efforts and self-assembly experiments have been assisted by computer simulations that predict phase equilibria. Most current simulations employ Monte Carlo methods, which generate stochastic dynamics. Collective and correlated configuration updates are alternatives that promise higher computational efficiency and generate trajectories with realistic dynamics. One such alternative involves event-chain updates and has recently been proposed for spherical particles. In this contribution, we develop and apply event-chain Monte Carlo for hard convex polyhedra. Our simulation makes use of an improved computational geometry algorithm XenoSweep, which predicts sweep collision in a particularly simple way. We implement Newtonian event chains in the open-source general-purpose particle simulation toolkit HOOMD-blue for serial and parallel simulation. The speedup over state-of-the-art Monte Carlo is between a factor of 10 for nearly spherical polyhedra and a factor of 2 for highly aspherical polyhedra. Finally, we validate the Newtonian event-chain algorithm by applying it to a current research problem, the multistep nucleation of two classes of hard polyhedra.

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Section: Implementation and Parameterizationmentioning

confidence: 99%

Section: Implementation and Parameterizationmentioning

confidence: 99%

Newtonian Event-Chain Monte Carlo and Collision Prediction with Polyhedral Particles

Klement

Lee

Anderson

et al. 2021

J. Chem. Theory Comput.

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show abstract

“…Shape plays an important role for the optimal choice of µ. Icosahedra prefer more translations (µ > ∼ 0), which is explained by the presence of a rotator phase prior to crystallization. 35 Tetrahedra prefer more rotations (µ < ∼ 1) due to their strong preference for face-to-face contact. 36 In general, we expect nearly spher- ical polyhedra to rotate easily and highly anisotropic polyhedra to preferentially align face-to-face.…”

Section: Move Ratio Parametermentioning

confidence: 99%

Newtonian Event-Chain Monte Carlo and Collision Prediction with Polyhedral Particles

Klement,

Lee,

Anderson

et al. 2021

Preprint

View full text Add to dashboard Cite

Polyhedral nanocrystals are building blocks for nanostructured materials that find applications in catalysis and plasmonics. Synthesis efforts and self-assembly experiments have been assisted by computer simulations that predict phase equilibra. Most current simulations employ Monte Carlo methods, which generate stochastic dynamics. Collective and correlated configuration updates are alternatives that promise higher computational efficiency and generate trajectories with realistic dynamics. One such alternative involves event-chain updates and has recently been proposed for spherical particles. In this contribution, we develop and apply eventchain Monte Carlo for hard convex polyhedra. Our simulation makes use of an improved computational geometry algorithm XenoSweep, which predicts sweep collision in a particularly simple way. We implement Newtonian event chains in the open source general-purpose particle simulation toolkit HOOMD-blue for serial and parallel simulation. The speed-up over state-of-the-art Monte Carlo is between a factor of 10 for nearly spherical polyhedra and a factor of 2 for highly aspherical polyhedra. Finally, we validate the Newtonian event-chain algorithm by applying it to a current research problem, the multi-step nucleation of two classes of hard polyhedra.

show abstract

On the phase diagram of Mackay icosahedra

Cited by 2 publications

References 40 publications

Newtonian Event-Chain Monte Carlo and Collision Prediction with Polyhedral Particles

Newtonian Event-Chain Monte Carlo and Collision Prediction with Polyhedral Particles

Newtonian Event-Chain Monte Carlo and Collision Prediction with Polyhedral Particles

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