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The striking anomalies in physical properties of supercooled water that were discovered in the 1960-70s, remain incompletely understood and so provide both a source of controversy amongst theoreticians, and a stimulus to experimentalists…

Chemical Physics · Physics 2016-05-31 Sander Woutersen , Michiel Hilbers , Zuofeng Zhao , C. Austen Angell

We present a multi-lattice kinetic Monte Carlo (kMC) approach that efficiently describes the atomistic dynamics of morphological transitions between commensurate structures at crystal surfaces. As an example we study the reduction of a…

Mesoscale and Nanoscale Physics · Physics 2015-01-09 Max J. Hoffmann , Matthias Scheffler , Karsten Reuter

Water scarcity is a dilemma facing much of the global population. Cation intercalation desalination (CID) cells, which use intercalation host compounds (IHCs) in combination with ion-exchange membranes (IEMs), could aid in addressing this…

Chemical Physics · Physics 2016-12-28 Kyle C. Smith

Water and silicon are chemically dissimilar substances with common physical properties. Their liquids display a temperature of maximum density, increased diffusivity on compression, they form tetrahedral crystals and tetrahedral amorphous…

Soft Condensed Matter · Physics 2008-09-18 Valeria Molinero , Emily B. Moore

A first principles machine learning model has been developed aimed at studying the formation of calcium carbonate from aqueous solution using molecular dynamics simulations. The model, dubbed SCAN-ML, reproduces accurately the potential…

Chemical Physics · Physics 2025-03-19 Pablo M. Piaggi , Julian D. Gale , Paolo Raiteri

A mathematical model describing a steady pH-gradient in the solution of ampholytes in water has been studied with the use of analytical, asymptotic, and numerical methods. We show that at the large values of an electric current a…

Chemical Physics · Physics 2009-02-24 L. V. Sakharova , V. A. Vladimirov , M. Yu. Zhukov

Machine Learning (ML) is a powerful tool for material science applications. Artificial Neural Network (ANN) is a machine learning technique that can provide high prediction accuracy. This study aimed to develop an ANN model to predict the…

Machine Learning · Computer Science 2023-08-14 Masoume Kazemi , Davood Moradkhani , Alireza A. Alipour

The thermal conductivity of organic liquids is a vital parameter influencing various industrial and environmental applications, including energy conversion, electronics cooling, and chemical processing. However, atomistic simulation of…

The mathematical model describing the non-stationary natural pH-gradient arising under the action of an electric field in an aqueous solution of ampholytes (amino acids) is constructed. The model is a part of a more general model of the…

Chemical Physics · Physics 2013-11-26 E. V. Shiryaeva , N. M. Zhukova , M. Yu. Zhukov

It is established that liquid metals exhibit surface layering at the liquid-vapor interface, while dielectric simple systems, like those interacting through Lennard-Jones potentials, show a monotonic decay from the liquid density to that of…

Disordered Systems and Neural Networks · Physics 2009-11-11 Luis E. Gonzalez , David J. Gonzalez

Molecular dynamics in pure water and aqueous salt solutions remain incompletely understood, partly due to the apparent contradictions between results from different spectroscopic techniques. In this work, we demonstrate, by detailed…

Soft Condensed Matter · Physics 2025-12-22 Rolf Zeißler , Florian Pabst , Thomas Blochowicz

Alkaline vents (AV) are hypothesized to have been a setting for the emergence of life, by creating strong gradients across inorganic membranes within chimney structures. In the past, 3-dimensional chimney structures were formed under…

This letter presents a novel approach for identifying uncorrelated atomic configurations from extensive data sets with a non-standard neural network workflow known as random network distillation (RND) for training machine-learned…

Computational Physics · Physics 2023-09-08 Jan Finkbeiner , Samuel Tovey , Christian Holm

Simplified, classical models of water are an integral part of atomistic molecular simulations, especially in biology and chemistry where hydration effects are critical. Yet, despite several decades of effort, these models are still far from…

Chemical Physics · Physics 2015-01-13 Saeed Izadi , Ramu Anandakrishnan , Alexey V. Onufriev

Droplet nucleation and evaporation are ubiquitous in nature and many technological applications, such as phase-change cooling and boiling heat transfer. So far, the description of these phenomena at the molecular scale has posed challenges…

Fluid Dynamics · Physics 2023-11-28 Panagiotis E. Theodorakis , Y. Wang , A. Chen , B. Liu

Although electrolyte density measurements have been reported for over a century, employing them to obtain accurate partial molar volume (PMV) profiles as a function of salt concentration has remained elusive. Obtaining such curves requires…

Carbon dioxide (CO$_2$) sequestration in saline aquifers has been introduced as one of the most practical, long-term, and safe solutions to tackle a growing threat originating from the emission of CO$_2$. Successfully executing and planning…

Mesoscale and Nanoscale Physics · Physics 2021-09-07 Sina Omrani , Mehdi Ghasemi , Saeed Mahmoodpour , Ali Shafiei , Behzad Rostami

Additive manufacturing (AM) processes produce parts with improved physical, chemical, and mechanical properties compared to conventional manufacturing processes. In AM processes, intricate part geometries are produced from multicomponent…

Materials Science · Physics 2018-01-04 Supriyo Ghosh

The nucleation of crystals from the liquid melt is often characterized by a competition between different crystalline structures or polymorphs, and can result in nuclei with heterogeneous compositions. These mixed-phase nuclei can display…

Soft Condensed Matter · Physics 2021-08-26 Fabio Leoni , John Russo

In this work we give the analysis of the low frequency dielectric response of selected kaolinitic clays at different water content ranging from dry, over plastic to liquid limit. For all samples investigated, depending on the moisture…

Soft Condensed Matter · Physics 2016-08-31 Dean Korosak , Janja Kramer , Renata Jecl , Bruno Cvikl , Miran Veselic