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Supercooled water is expected to exhibit a liquid--liquid phase transition between low- and high-density liquid states, possibly terminating in a liquid--liquid critical point in the experimentally difficult no man's land. Because the…

Chemical Physics · Physics 2026-05-20 Michael Beerbaum , Julian Heske , Jure Gujt , Thomas D. Kühne

Metal superhydrides, known for their high hydrogen content and polyhedral hydrogen cages, are promising candidates for high-temperature superconductivity. Recent research has emphasized "chemical pre-compression," enabling hydrogen…

Superconductivity · Physics 2025-03-06 Yuanhui Sun , Maosheng Miao

A quantitative descriptor of local atomic environments is often required for the analysis of atomistic data. Descriptors of the local atomic environment ideally provide physically and chemically intuitive insight. This requires descriptors…

We introduce structural heterogeneity, a new topological characteristic for semi-ordered materials that captures their degree of organisation at a mesoscopic level and tracks their time-evolution, ultimately detecting the order-disorder…

The systematic identification of temperature scales in supercooled liquids that are key to understanding those liquids' underlying glass properties, and the latter's formation-history dependence, is a challenging task. Here we study the…

Soft Condensed Matter · Physics 2021-01-05 Karina González-López , Edan Lerner

The supra-molecular structure of a liquid is strongly connected to its dynamics which in turn controls macroscopic properties such as viscosity. Consequently, detailed knowledge about how this structure changes with temperature is essential…

Soft Condensed Matter · Physics 2025-08-05 Jan Philipp Gabriel , Robin Horstmann , Martin Tress

Water hydrogen bonding is extremely versatile; approximately 20 ice structures and several types of clathrate hydrate structures have been identified. These crystalline water structures form at temperatures below room temperature and/or at…

We employ the Distance Matrix method to investigate metabasin dynamics in supercooled water. We find that the motion of the system consists in the exploration of a finite region of configuration space (enclosing several distinct local…

Soft Condensed Matter · Physics 2007-05-23 Jorge Ariel Rodriguez Fris , Gustavo A. Appignanesi , Emilia La Nave , Francesco Sciortino

For a deeply supercooled liquid just above its glass transition temperature, we present a simple thermodynamic model, where the deeply supercooled liquid is assumed to be a mixture of solid-like and liquid-like micro regions. The mole…

Statistical Mechanics · Physics 2012-10-17 Hiroshi Matsuoka

In this paper, we introduce a novel framework for combining scientific knowledge within physics-based models and recurrent neural networks to advance scientific discovery in many dynamical systems. We will first describe the use of outputs…

Machine Learning · Computer Science 2018-10-09 Xiaowei Jia , Anuj Karpatne , Jared Willard , Michael Steinbach , Jordan Read , Paul C Hanson , Hilary A Dugan , Vipin Kumar

In this work, we study the nature of transitions between inherent structures of a two-dimensional model supercooled liquid. We demonstrate that these transitions occur predominately along a small number of directions on the energy…

Statistical Mechanics · Physics 2013-03-12 Glen M. Hocky , David R. Reichman

The predictions of a class of phenomenological trap models of supercooled liquids are tested via computer simulation of a model glass-forming liquid. It is found that a model with a Gaussian distribution of trap energies provides a good…

Soft Condensed Matter · Physics 2007-05-23 R. Aldrin Denny , David R. Reichman , Jean-Philippe Bouchaud

In this manuscript, we present a general computational method for characterizing the molecular structure of liquid water interfaces as sampled from atomistic simulations. With this method, the interfacial structure is quantified based on…

Soft Condensed Matter · Physics 2017-08-25 Sucheol Shin , Adam P. Willard

We present an operational method to determine the 'locally preferred structure'' of model liquids, a notion often put forward to explain supercooling of a liquid and glass formation. The method relies on finding the global minimum in the…

Disordered Systems and Neural Networks · Physics 2011-05-05 S. Mossa , G. Tarjus

The hydrogen-bonded structure of methanol-water mixtures is investigated over the entire alcohol concentration range (from $x_{\mathrm{Methanol}}=$ 0.1 to 1.0) at several temperatures, from 300 K down to the freezing point of the given…

Chemical Physics · Physics 2023-07-07 Ildikó Pethes , László Pusztai , László Temleitner

We determine the phase diagram of liquid supercooled water by extensive computer simulations using the TIP5P-E model [J. Chem. Phys. {\bf 120}, 6085 (2004)]. We find that the transformation of water into a low density liquid in the…

Statistical Mechanics · Physics 2007-05-23 Dietmar Paschek

The correlation between local structure and the propensity for structural rearrangements has been widely investigated in glass forming liquids and glasses. In this paper we use the excess two-body entropy $S_2$ and tetrahedrality $\n_{tet}$…

Statistical Mechanics · Physics 2022-03-14 Saheli Mitra , Susana Marin-Aguilar , Srikanth Sastry , Frank Smallenburg , Giuseppe Foffi

We have developed x-ray diffraction measurements with high energy-resolution and accuracy to study water structure at three different temperatures (7, 25 and 66 C) under normal pressure. Using a spherically curved Ge crystal an energy…

Soft Condensed Matter · Physics 2017-09-13 Congcong Huang , K. T. Wikfeldt , D. Nordlund , U. Bergmann , T. McQueen , J. Sellberg , L. G. M. Pettersson , A. Nilsson

The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how…

Chemical Physics · Physics 2014-11-14 Piero Gasparotto , Michele Ceriotti

In this paper we investigate the performance of different machine learning potentials (MLPs) in predicting key thermodynamic properties of water using RPBE+D3. Specifically, we scrutinize kernel-based regression and high-dimensional neural…