Cluster Identification and Percolation Analysis Using a Recursive Algorithm

Edvinsson, Tomas; Råsmark, Per Johan; Elvingson, Christer

doi:10.1080/08927029908022121

Cited by 14 publications

(10 citation statements)

References 17 publications

(9 reference statements)

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“…Percolation analysis involves two steps: First, some connectivity metric must be defined between adjacent percolating units; for water, we make the natural choice that two water molecules are connected if and only if there is a hydrogen bond between them. Next, some algorithm (usually recursive [122]) must be applied to check whether there exists a continuous network of connected (hydrogen bonded) water molecules that entirely spans the system length and is connected with itself through the periodic boundaries of the simulation box. If such a network exists, then it is said to percolate.…”

Section: Resultsmentioning

confidence: 99%

“…Electrostatic interactions were computed with the particle mesh Ewald (PME) approach [119] and van der Waals interactions were truncated at 1.4 nm accompanied with standard long-range correction. The MDTraj software was utilized for simulation analysis [120], NetworkX software was used for clustering analysis [121] and a recursive algorithm was employed for percolation analysis [122]; specific details of the analysis methods are discussed in the Supporting Information.…”

Section: Introductionmentioning

confidence: 99%

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Tuning Water Networks via Ionic Liquid/Water Mixtures

Verma

Stoppelman

McDaniel

2020

IJMS

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Water in nanoconfinement is ubiquitous in biological systems and membrane materials, with altered properties that significantly influence the surrounding system. In this work, we show how ionic liquid (IL)/water mixtures can be tuned to create water environments that resemble nanoconfined systems. We utilize molecular dynamics simulations employing ab initio force fields to extensively characterize the water structure within five different IL/water mixtures: [BMIM + ][BF 4 − ], [BMIM + ][PF 6 − ], [BMIM + ][OTf − ], [BMIM + ][NO 3 − ] and [BMIM + ][TFSI − ] ILs at varying water fraction. We characterize water clustering, hydrogen bonding, water orientation, pairwise correlation functions and percolation networks as a function of water content and IL type. The nature of the water nanostructure is significantly tuned by changing the hydrophobicity of the IL and sensitively depends on water content. In hydrophobic ILs such as [BMIM + ][PF 6 − ], significant water clustering leads to dynamic formation of water pockets that can appear similar to those formed within reverse micelles. Furthermore, rotational relaxation times of water molecules in supersaturated hydrophobic IL/water mixtures indicate the close-connection with nanoconfined systems, as they are quantitatively similar to water relaxation in previously characterized lyotropic liquid crystals. We expect that this physical insight will lead to better design principles for incorporation of ILs into membrane materials to tune water nanostructure.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tuning Water Networks via Ionic Liquid/Water Mixtures

Verma

Stoppelman

McDaniel

2020

IJMS

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“…To be able to distinguish the different stages of the gel collapse, one may also try to identify clusters formed during a collapse transition. It should be noted that there is no exact definition of a cluster, and different cluster recognition algorithms may be used for this purpose. − Here, we will define a cluster as the smallest set of units such that each unit is within a threshold distance, D , from at least one other nonbonded member of the set. As the choice of threshold distance is ambiguous, different values of D were investigated, based on the LJ potential energy curve, to test the sensitivity of the results.…”

Section: Model and Methodsmentioning

confidence: 99%

Collapse Dynamics of Core–Shell Nanogels

Kamerlin

Elvingson

2016

Macromolecules

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Stimuli-responsive core−shell nanogels display collapse properties which are determined by both the core and the shell. We examine the equilibrium properties and the detailed structural changes during a collapse transition of polymer core− shell nanoparticles using Brownian dynamics simulations. Gel particles with randomly distributed cross-linking nodes are created. The influence of the cross-linking degree, core/shell mass ratio, and the strength of the interparticle attractive interaction on the collapse behavior is investigated. Both collapsed core and collapsed shell structures are considered and compared with collapsed homopolymer networks. The transition time was found to be reduced with increasing cross-linking degree and inversely related to the depth of the Lennard-Jones potential. Similar to the kinetics of single chain collapse, there is an initial formation of clusters, in this case near cross-linking nodes, and a subsequent coarsening to form a compact globule. Where the nanogels were collapsed into a compact core, the deformation was found to be essentially symmetric, with a significantly slower relaxation time for the shell units compared to the core collapse transition time. Reducing the core size, the shell units were less affected by the presence of a collapsing core. For the system with a collapsing shell, our simulations reveal in some cases an inversion, with the shell compressing and eventually squeezing out the core units. This effect was more pronounced with decreasing cross-linking degree and core/shell mass ratio.

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“…A cluster analysis was performed on the simulation snapshots of the liquids to determine how the glycine molecules tend to associate with each other in the aqueous solutions. The Edvinsson algorithm 31 was used to calculate cluster statistics.…”

Section: Methodsmentioning

confidence: 99%

Molecular dynamics simulations of aqueous glycine solutions

2017

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Simulations of glycine aqueous solutions have been carried out to study the effect of increasing solute concentration on the aggregation of glycine zwitterions. AMBER force field coupled with three atomic charge sets was employed for the simulations of the aqueous solutions. The number of glycine monomers in solutions rapidly decreases with increase in concentration. The properties of the glycine clusters in the solutions were studied. It was shown that the clusters are strongly hydrated entities with a liquid-like character. The residence lifetimes of water and glycine from the first solvation shell of glycine molecules were calculated. The lifetime values show that the clusters are highly dynamic solutes that change configuration within hundreds of picoseconds. We observed long-living pairs of glycine molecules, which move together in the solutions for ca. 1 ns. The effect of the electric-field-induced orientation of the highly polar glycine molecules in the clusters was studied. A preferential parallel arrangement of the molecules was observed as the distinctive feature of the γ-polymorph, which was crystallized from the solutions in a static electric field.

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Cluster Identification and Percolation Analysis Using a Recursive Algorithm

Cited by 14 publications

References 17 publications

Tuning Water Networks via Ionic Liquid/Water Mixtures

Tuning Water Networks via Ionic Liquid/Water Mixtures

Collapse Dynamics of Core–Shell Nanogels

Molecular dynamics simulations of aqueous glycine solutions

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