Related papers: Water Isotope Separation using Deep Learning and a…
Recent studies have shown the latency and energy consumption of deep neural networks can be significantly improved by splitting the network between the mobile device and cloud. This paper introduces a new deep learning architecture, called…
Ultraviolet irradiation of ice is of great interest for understanding the chemistry in both atmospheric and astrophysical environments. In interstellar space, photodissociation of H2O molecules can be a driving force behind the chemistry on…
High gradient magnetic separation (HGMS) is an efficient way to remove magnetic and paramagnetic particles, such as heavy metals, from waste water. As the suspension flows through a magnetized filter mesh, high magnetic gradients around the…
The radiolysis of water is an important study in microdosimetry, one of the resulting and important molecules in this study is the $OH^-$. Theoretical quantum mechanics calculations are used to obtain the differential cross section for the…
Deep Inelastic Neutron Scattering provides a means of directly and accurately measuring the momentum distribution of protons in water, which is determined primarily by the protons ground state wavefunction. We find that in water confined on…
Urban water is important for the urban ecosystem. Accurate and efficient detection of urban water with remote sensing data is of great significance for urban management and planning. In this paper, we proposed a new method to combine Google…
Double-core-hole (DCH) states in isolated water and heavy water molecules, resulting from the sequential absorption of two x-ray photons, have been investigated. A comparison of the subsequent Auger emission spectra from the two isotopes…
Liquids under confinement differ in behavior from their bulk counterparts and can acquire properties that are specific to the confined phase and linked to the nature and structure of the host matrix. While confined liquid water is not a new…
We demonstrate how deep convolutional neural networks can be trained to predict 2+1 D hydrodynamic simulation results for flow coefficients, mean-transverse-momentum and charged particle multiplicity from the initial energy density profile.…
The study explores machine learning methods for revealing chemical sensitivity in Helium spin-echo spectroscopy, in order to obtain ultra-sensitive surface analytic technique. We model bi-species co-adsorbed systems and demonstrate that by…
Purpose: To use a deep neural network (DNN) for solving the optimization problem of water/fat separation and to compare supervised and unsupervised training. Methods: The current T2*-IDEAL algorithm for solving fat/water separation is…
Molecular segregation in methanol-water mixtures is studied across a wide concentration range as a function of temperature and pressure. Cluster distributions obtained from both neutron diffraction and molecular dynamics simulations point…
Phase segregation, the process by which the components of a binary mixture spontaneously separate, is a key process in the evolution and design of many chemical, mechanical, and biological systems. In this work, we present a data-driven…
We present a recently developed one-dimensional dipole lattice model that accurately captures the key properties of water in narrow nanopores. For this model, we derive three equivalent representations of the Hamiltonian that together yield…
Most of the performances of electrochemical devices are governed by molecular processes taking place at the solution-electrode interfaces and molecular simulation are the main way to study these processes. Aqueous electrochemical systems…
Wave breaking is an important process for energy dissipation in the open ocean and coastal seas. It drives beach morphodynamics, controls air-sea interactions, determines when ship and offshore structure operations can occur safely, and…
The low efficiency of commercially-used reverse osmosis (RO) membranes has been the main obstacle in seawater desalination application. Here, we report the auspicious performance, through molecular dynamics simulations, of a seawater…
We show that a two-dimensional hydrodynamics model provides a physical explanation for the splitting of higher-charge optical vortices under elliptical deformations. The model is applicable to laser light and quantum fluids alike. The study…
We consider a lattice model of active matter with exclusion and derive its hydrodynamic description exactly. The hydrodynamic limit leads to an integro-differential equation for the density of particles with a given orientation. Volume…
Research suggests that acoustic technology may be able to detect ultra-high-energy neutrinos if a large amount of non-linear fluid is analyzed. When a neutrino interacts in water, it creates a quasi-instantaneous cascade of particles,…