d-SEAMS: Deferred Structural Elucidation Analysis for Molecular Simulations

Goswami, Rohit; Goswami, Amrita; Singh, Jayant K.

doi:10.1021/acs.jcim.0c00031

Cited by 9 publications

(4 citation statements)

References 74 publications

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“…We have used OVITO for generating the visuals in this work. Primitive rings were obtained and further analyzed according to our topological network criterion for quasi-two-dimensional systems, using a FOSS molecular dynamics analysis engine, d-SEAMS …”

Section: Computational Detailsmentioning

confidence: 99%

Exploring the Anomalous Phase Behavior of High-Pressure Ices in Diamond Confinement

Goswami

Singh

2020

J. Phys. Chem. C

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Inspired by the discovery of high-pressure ice inclusions in diamond, we investigate the rich structural diversity of high-pressure phases of quasi-two-dimensional water constrained by diamond matrices, using molecular dynamics simulations. Monolayer ices formed are structurally similar to monolayer ices constrained by graphene. We report new bilayer and trilayer ice phases, specifically, the AB II, ABC I, ABC II, and AAB/ABB ordered phases. The relative stability of the interlayer hydrogen bonds between adjacent layers reveals differences in structural properties. We observe grain-boundary migration between pockets of AAB and ABB ices, during the pressurization process. The compressionlimit phase diagram in the slit width−lateral pressure plane has been constructed and analyzed. Our results indicate that the phase behavior of confined ice is qualitatively independent of the diamond−water force-field parameters and is significantly influenced by the lattice structure and geometry of the confining surfaces.

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Section: Computational Detailsmentioning

confidence: 99%

Exploring the Anomalous Phase Behavior of High-Pressure Ices in Diamond Confinement

Goswami

Singh

2020

J. Phys. Chem. C

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“…The ice-like molecules were differentiated from the liquid phase by using the structural identification method of Maras et al [62], in OVITO [63]. The evolution of the largest ice cluster in each trajectory was monitored using d-SEAMS [64].…”

Section: Seeding Methods Calculationsmentioning

confidence: 99%

Seeding Method for Ice Nucleation under Shear

Goswami¹,

Dalal²,

Singh³

2020

Preprint

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Hydrodynamic flow can have complex and far-reaching consequences on the rate of homogenous nucleation. We present a general formalism for calculating the nucleation rates of simply sheared systems. We have derived an extension to the conventional Classical Nucleation Theory, explicitly embodying the shear rate. Seeded Molecular Dynamics simulations form the backbone of our approach. The framework can be used for moderate supercoolings, at which temperatures brute-force methods are practically infeasible. The competing energetic and kinetic effects of shear arise naturally from the equations. We show how the theory can be used to identify shear regimes of ice nucleation behaviour for the mW water model, unifying disparate trends reported in the literature. At each temperature, we define a crossover shear rate in the limit of 1000 − 10, 000 s −1 , beyond which the nucleation rate increases steadily upto a maximum, at the optimal shear rate. For 235, 240, 255 and 260 K, the optimal shear rates are in the range of ≈ 10 6 − 10 7 s −1 . For very high shear rates beyond 10 8 s −1 , nucleation is strongly inhibited. Our results indicate that the shear-dependent nucleation rate curves have a non-monotonic dependence on temperature.

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“…The computation of the critical nucleus size using the seeding approach is further described in Section S1 of the ESI. † The water molecules are identified as ice or liquid based on the CHILL+ 50,51 criteria as implemented in the d-SEAMS 52 package. The evolution of the largest cluster is monitored using the cluster analysis tool in the OVITO 53 package.…”

Section: Seeding Simulationsmentioning

confidence: 99%