Competing interactions near the liquid-liquid phase transition of core-softened water/methanol mixtures

Marques, Murilo Sodré; Hernandes, Vinícius Fonseca; Lomba, Enrique; Bordin, José Rafael

doi:10.1016/j.molliq.2020.114420

Cited by 10 publications

(16 citation statements)

References 82 publications

(103 reference statements)

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“…For the supercritical pressure P * = 0.15 we see a change in the diffusion inclination with temperature when it crosses the Widom Line, indicating the HDL-dominated to LDL-dominated regime. These results are in agreement with our recent work obtained by the heating of the system [55] and previous works employing this potential [57][58][59][60]. However, the solid phases weren't explored for this system.…”

Section: A Pure Cs Water Phase Diagramsupporting

confidence: 92%

“…However, the solid phases weren't explored for this system. In fact, the HCP phase was observed in our work [55] and in the study by Hus and Urbic using the methanol model [84,85]. Here, exploring a larger region in the phase diagram, we characterized three distinct solid phases.…”

Section: A Pure Cs Water Phase Diagrammentioning

confidence: 55%

“…To answer this question, we perform extensive simulations in order to analyze the phase diagram of water and water-alcohols mixtures, where both water and hydroxyls are modeled by core-softened potentials, which already have a long history of describing water anomalies both in bulk and confined environments [49][50][51][52][53][54]. In our very recent work [55] we have explored the supercooled regime of pure water, pure methanol and their mixtures using a core-softened (CS) potential model [2]. In this scheme, hydroxyl groups of different molecules interact by a continuous shouldered well (CSW) potential, while all other interactions are reproduced by LJ-like contributions, and our principal focus in that publication was on the relations between density anomaly, liquid-liquid phase transition and spontaneous crystallization by means of Molecular Dynamics simulations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Core-softened water–alcohol mixtures: the solute-size effects

Marques

Hernandes

Bordin

2021

Phys. Chem. Chem. Phys.

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Section: A Pure Cs Water Phase Diagramsupporting

confidence: 92%

Section: A Pure Cs Water Phase Diagrammentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Core-softened water–alcohol mixtures: the solute-size effects

Marques

Hernandes

Bordin

2021

Phys. Chem. Chem. Phys.

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“…82 It is used, also, to model hydroxyl groups interactions in methanol, [83][84][85] and waterhydroxyl groups interactions in water/methanol mixtures. 86 A potential similar to the CSW has been used to study the effect of macromolecular crowders in biological media with high concentration of proteins, polysaccharides or nucleic acids. 87,88 Yet, the CSW fluid has not a water-like entropy behavior, as all the other two-length scales isotropic potential, because it has no directional interactions.…”

Section: Introductionmentioning

confidence: 99%

Nanoconfined fluids: Uniqueness of water compared to other liquids

Leoni,

Calero,

Franzese

2021

Preprint

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Nanoconfinement can drastically change the behavior of liquids, puzzling us with counterintuitive properties. Moreover, it is relevant in applications, including decontamination and crystallization control. However, it still lacks a systematic analysis for fluids with different bulk properties. Here we fill this gap. We compare, by molecular dynamics simulations, three different liquids in a graphene slit pore: (A) A simple fluid, such as argon, described by a Lennard-Jones potential; (B) An anomalous fluid, such as a liquid metal, modeled with an isotropic core-softened potential; (C) Water, the prototypical anomalous liquid, with directional hydrogen bonds. We study how the slit-pore width affects the structure, thermodynamics, and dynamics of the fluids. We check that all the liquids, as expected, have a) free-energy minima-hence mechanical stability-for widths that are optimal to accommodate fluid layers, b) mechanicallyunstable free-energy maxima for intermediate widths, c) an effective wall-wall repulsion at sub-optimal widths, i.e., for under-sized slit-pores, d) a fluid-mediated attraction for

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“…Many experimental and theoretical works have studied these short-chain alcohol/water mixtures [60,61,62,63,64,65,66]. In our recent works, we have performed Molecular Dynamics (MD) simulations with a coresoftened (CS) approach to investigate the behavior of methanol-water [67] and water mixtures with methanol, ethanol and 1-propanol [68]. In this approach, the waterlike solvent is modeled as the CSW fluid proposed by Franzese [69].…”

Section: Introductionmentioning

confidence: 99%

Phase classification using neural networks: application to supercooled, polymorphic core-softened mixtures

Hernandes,

Marques,

Bordin

2021

Preprint

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Characterization of phases of soft matter systems is a challenge faced in many physicochemical problems. For polymorphic fluids it is an even greater challenge. Specifically, glass forming fluids, as water, can have, besides solid polymorphism, more than one liquid and glassy phases, and even a liquid-liquid critical point. In this sense, we apply a neural network (NN) algorithm to analyze the phase behavior of a core-softened mixture of core-softened CSW fluids that have liquid polymorphism and liquid-liquid critical points, similar to water. We also apply the NN to mixtures of CSW fluids and core-softened alcohols models. We combine and expand two methods based on bond-orientational order parameters to study mixtures, applied to mixtures of hardcore fluids by Boattini and co-authors [Molecular Physics 116, 3066-3075 (2018)] and to supercooled water by Martelli and co-authors [The Journal of Chemical Physics 153, 104503 (2020)], to include longer range coordination shells. With this, the trained neural network (NN) was able to properly predict the crystalline solid phases, the fluid phases and the amorphous phase for the pure CSW and CSW-alcohols mixtures with high efficiency. More than this, information about the phase populations, obtained from the NN approach, can help verify if the phase transition is continuous or discontinuous, and also to interpret how the metastable amorphous region spreads along the stable high density fluid phase. These findings help to understand the behavior of supercooled polymorphic fluids and extend the comprehension of how amphiphilic solutes affect the phases behavior.

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Competing interactions near the liquid-liquid phase transition of core-softened water/methanol mixtures

Cited by 10 publications

References 82 publications

Core-softened water–alcohol mixtures: the solute-size effects

Core-softened water–alcohol mixtures: the solute-size effects

Nanoconfined fluids: Uniqueness of water compared to other liquids

Phase classification using neural networks: application to supercooled, polymorphic core-softened mixtures

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