Related papers: Phase classification using neural networks: applic…
This study investigates the application of an artificial neural network framework for analysing water pollution caused by solids. Water pollution by suspended solids poses significant environmental and health risks. Traditional methods for…
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…
We introduce a machine-learning approach to predict the complex non-Markovian dynamics of supercooled liquids from static averaged quantities. Compared to techniques based on particle propensity, our method is built upon a theoretical…
We demonstrate several techniques to encourage practical uses of neural networks for fluid flow estimation. In the present paper, three perspectives which are remaining challenges for applications of machine learning to fluid dynamics are…
We study the phase diagram of a system of spherical particles interacting in three dimensions through a potential consisting of a strict hard core plus a linear repulsive shoulder at larger distances. The phase diagram (obtained…
Water's unique anomalies are vital in various applications and biological processes, yet the molecular mechanisms behind these anomalies remain debated, particularly in the metastable liquid phase under supercooling and stretching…
The multi-scale nature of gaseous flows poses tremendous difficulties for theoretical and numerical analysis. The Boltzmann equation, while possessing a wider applicability than hydrodynamic equations, requires significantly more…
Complex-valued neural networks (CVNNs) are particularly suitable for handling phase-sensitive signals, including electrocardiography (ECG), radar/sonar, and wireless in-phase/quadrature (I/Q) streams. Nevertheless, their…
Climate change results in altered air and water temperatures. Increases affect physicochemical properties, such as oxygen concentration, and can shift species distribution and survival, with consequences for ecosystem functioning and…
Functionalization of nanoparticles or colloids is increasingly being used to develop customizable "atoms". Functionalization by attaching single strands of DNA allows for direct control of the binding between nanoparticles, since…
Recent experimental and computational studies have demonstrated that nanoconfinement profoundly alters the phase behavior of water, facilitating complex phase transitions at pressures and temperatures far lower than typically observed in…
We use simulation-based supervised machine learning and classical density functional theory to investigate bulk and interfacial phenomena associated with phase coexistence in binary mixtures. For a prototypical symmetrical Lennard-Jones…
Simulating liquid water to an accuracy that matches its wealth of available experimental data requires both precise electronic structure methods and reliable sampling of nuclear (quantum) motion. This is challenging because applying the…
The combination of large spontaneous polarization and fluidity makes the newly discovered ferroelectric nematic liquid crystalline phase (NF) responsive to electric fields in ways that have no counterpart in other materials. We probe this…
Liquid mixtures with a nematogen can undergo both fluid phase separation and a transition from an isotropic to a nematic state. These phase transitions can couple and lead to phase behavior distinct from simple liquid mixtures or pure…
Binary mixtures of water with lower alcohols display non-linear phase behaviour upon mixing which are attributed to potential cluster formation at molecular level. Unravelling such elusive structures requires the investigation of…
Amorphous glassy materials of diverse nature -- concentrated emulsions, granular materials, pastes, molecular glasses -- display complex flow properties, intermediate between solid and liquid, which are at the root of their use in many…
We study the finite temperature (FT) phase transitions of two-dimensional (2D) $q$-states Potts models on the square lattice, using the first principles Monte Carlo (MC) simulations as well as the techniques of neural networks (NN). We…
The distinctive characteristics of water, evident in its thermodynamic anomalies, have implications across disciplines from biology to geophysics. Considered a valid hypothesis to rationalize its unique properties, a liquid-liquid phase…
The dynamics of water molecules plays a vital role in understanding water. We combined computer simulation and deep learning to study the dynamics of H-bonds between water molecules. Based on ab initio molecular dynamics simulations and a…