4.8 Article

Tuning the Liquid-Liquid Transition by Modulating the Hydrogen-Bond Angular Flexibility in a Model for Water

期刊

PHYSICAL REVIEW LETTERS
卷 115, 期 1, 页码 -

出版社

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevLett.115.015701

关键词

-

向作者/读者索取更多资源

We propose a simple extension of the well known ST2 model for water [F.H. Stillinger and A. Rahman, J. Chem. Phys. 60, 1545 (1974)] that allows for a continuous modification of the hydrogen-bond angular flexibility. We show that the bond flexibility affects the relative thermodynamic stability of the liquid and of the hexagonal (or cubic) ice. On increasing the flexibility, the liquid-liquid critical point, which in the original ST2 model is located in the no-man's land (i.e., the region where ice is the thermodynamically stable phase) progressively moves to a temperature where the liquid is more stable than ice. Our study definitively proves that the liquid-liquid transition in the ST2 model is a genuine phenomenon, of high relevance in all tetrahedral network-forming liquids, including water.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Chemistry, Physical

Correlation between plastic rearrangements and local structure in a cyclically driven glass

Saheli Mitra, Susana Marin-Aguilar, Srikanth Sastry, Frank Smallenburg, Giuseppe Foffi

Summary: This study investigates the correlation between local structure and propensity for structural rearrangement in glass forming liquids and glasses. The results show that in a cyclic shear deformation, particles with higher S-2 and lower n(tet) are more likely to undergo rearrangement, regardless of the average energies of the configurations and strain amplitude. Distinctive local ordering is observed outside the shear band region, with the formation of icosahedral clusters.

JOURNAL OF CHEMICAL PHYSICS (2022)

Correction Chemistry, Physical

Efficient event-driven simulations of hard spheres (vol 45, 22, 2022)

Frank Smallenburg

EUROPEAN PHYSICAL JOURNAL E (2022)

Article Chemistry, Physical

Comparing machine learning techniques for predicting glassy dynamics

Rinske M. Alkemade, Emanuele Boattini, Laura Filion, Frank Smallenburg

Summary: In this study, three different machine learning algorithms were used to predict the dynamic properties of glassy materials. The results show that all three methods achieve similar accuracy when advanced structural descriptors are used. However, linear regression is significantly faster to train compared to the other methods.

JOURNAL OF CHEMICAL PHYSICS (2022)

Article Chemistry, Physical

Liquid-liquid criticality in the WAIL water model

Jack Weis, Francesco Sciortino, Athanassios Z. Panagiotopoulos, Pablo G. Debenedetti

Summary: Recent experiments and numerical simulations have provided support to the hypothesis that a second critical point exists in deeply supercooled water. In particular, a study has found that a liquid-liquid critical point can be located using a model parameterized solely based on ab initio calculations. This finding is important for understanding the phase behavior of supercooled water.

JOURNAL OF CHEMICAL PHYSICS (2022)

Article Physics, Multidisciplinary

Topological nature of the liquid-liquid phase transition in tetrahedral liquids

Andreas Neophytou, Dwaipayan Chakrabarti, Francesco Sciortino

Summary: This article demonstrates through experiments that the liquid-liquid phase transition in tetrahedral networks can be described as a transition between an unentangled, low-density liquid and an entangled, high-density liquid, with a clear topological distinction between the two phases.

NATURE PHYSICS (2022)

Article Physics, Multidisciplinary

Designing Enhanced Entropy Binding in Single-Chain Nanoparticles

Lorenzo Rovigatti, Francesco Sciortino

Summary: Single-chain nanoparticles are polymeric objects with special structures, and the phase transition can be controlled by designing the arrangement of reactive monomers. The study of this structure is of great significance for controlling polymer bonding.

PHYSICAL REVIEW LETTERS (2022)

Article Chemistry, Physical

Interpenetrating gels in binary suspensions of DNA nanostars

E. Lattuada, T. Pietrangeli, F. Sciortino

Summary: In this experiment, we investigated the equilibrium gel formation in a binary mixture of DNA nanostars. We found that two interpenetrating unconnected gels formed in the sample on cooling, with each gel forming at a temperature controlled by the selected binding DNA sequence. The dynamic light scattering correlation functions showed a non-common three-step relaxation process.

JOURNAL OF CHEMICAL PHYSICS (2022)

Article Chemistry, Physical

Correlated Fluctuations of Structural Indicators Close to the Liquid-Liquid Transition in Supercooled Water

Riccardo Foffi, Francesco Sciortino

Summary: Multiple numerical studies have confirmed the existence of a liquid-liquid critical point and proposed various structural indicators to describe the associated phase transition. Analyzing simulations of near-critical supercooled water, it is found that most indicators are strongly correlated to density, suggesting a tight coupling between apparently distinct structural degrees of freedom near the critical point.

JOURNAL OF PHYSICAL CHEMISTRY B (2023)

Article Chemistry, Physical

Two-step nucleation in a binary mixture of patchy particles

Camilla Beneduce, Diogo E. P. Pinto, Petr Sulc, Francesco Sciortino, John Russo

Summary: This study investigates the nucleation process of a binary mixture of patchy particles designed to nucleate into a diamond lattice. By combining Gibbs-ensemble simulations and direct nucleation simulations, the role of the liquid-gas metastable phase diagram on the nucleation process is revealed. The strongest enhancement of crystallization is found to occur at an azeotropic point with the same stoichiometric composition of the crystal.

JOURNAL OF CHEMICAL PHYSICS (2023)

Editorial Material Chemistry, Physical

2021 JCP Emerging Investigator Special Collection

Michele Ceriotti, Lasse Jensen, David E. Manolopoulos, Todd Martinez, David R. Reichman, Francesco Sciortino, C. David Sherrill, Qiang Shi, Carlos Vega, Lai-Sheng Wang, Emily A. Weiss, Xiaoyang Zhu, Jenny Stein, Tianquan Lian

JOURNAL OF CHEMICAL PHYSICS (2023)

Article Chemistry, Physical

Improving the prediction of glassy dynamics by pinpointing the local cage

Rinske M. Alkemade, Frank Smallenburg, Laura Filion

Summary: This study explores whether a simple linear regression algorithm combined with intelligently chosen structural order parameters can achieve the accuracy of the current advanced machine learning approaches for predicting dynamic propensity. The research finds that the structure of the cage state is highly predictive of the long-time dynamics of the system compared to the initial and inherent states. By combining the cage state information with the initial state, dynamic propensities can be predicted with unprecedented accuracy over a broad range of time scales, including the caging regime.

JOURNAL OF CHEMICAL PHYSICS (2023)

Article Chemistry, Physical

A neural network potential with self-trained atomic fingerprints: A test with the mW water potential

Francesco Guidarelli Mattioli, Francesco Sciortino, John Russo

Summary: We propose a new neural network potential that incorporates atomic fingerprints based on both two- and three-body contributions. These fingerprints probe distances and local orientational order. The training process of the proposed potential is simplified by using a small set of tunable parameters for the fingerprints. This approach improves the overall accuracy of the network representation and successfully reproduces the behavior of the mW model of water.

JOURNAL OF CHEMICAL PHYSICS (2023)

Article Chemistry, Physical

Are Neural Network Potentials Trained on Liquid States Transferable to Crystal Nucleation? A Test on Ice Nucleation in the mW Water Model

Francesco Guidarelli Mattioli, Francesco Sciortino, John Russo

Summary: Neural network potentials (NNPs) are increasingly used to study long time scale processes, such as crystal nucleation. It is unclear whether NN potentials trained on equilibrium liquid states can accurately describe nucleation processes. In this study, a NNP trained on a classical three-body potential for water accurately reproduces nucleation rates and free energy barriers, supporting the use of NNPs for studying nucleation events.

JOURNAL OF PHYSICAL CHEMISTRY B (2023)

Article Multidisciplinary Sciences

Design strategies for the self-assembly of polyhedral shells

Diogo E. P. Pinto, Petr Sulc, Francesco Sciortino, John Russo

Summary: The control over self-assembly of complex structures, particularly at the colloidal scale, has been a significant challenge in material science. The formation of amorphous aggregates often disrupts the desired assembly pathway. In this study, we investigate the self-assembly problem of three Archimedean shells using patchy particles as model building blocks. By recasting the assembly problem as a Boolean satisfiability problem, we find effective designs and selectively suppress unwanted structures.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2023)

Article Chemistry, Physical

Self-assembly of dodecagonal and octagonal quasicrystals in hard spheres on a plane

Etienne Fayen, Marianne Imperor-Clerc, Laura Filion, Giuseppe Foffi, Frank Smallenburg

Summary: Hard spheres are a fundamental model system in soft matter physics and have been crucial in understanding classical condensed matter. Simulations show that a simple model system of two sizes of hard spheres can self-assemble into two distinct random-tiling quasicrystal phases. The formation of these quasicrystals demonstrates that entropy and geometrically compatible, densely packed tiles are sufficient for the self-assembly of colloidal quasicrystals.

SOFT MATTER (2023)

暂无数据