Physics-informed machine learning of the correlation functions in bulk fluids

W Chen, P Gao, P Stinis - Physics of Fluids, 2024 - pubs.aip.org
The Ornstein–Zernike (OZ) equation is the fundamental equation for pair correlation function
computations in the modern integral equation theory for liquids. In this work, machine …

Oil occurrence states in shale mixed inorganic matter nanopores

S Liang, JM Wang, YK Liu, B Liu, S Sun… - Frontiers in Earth …, 2022 - frontiersin.org
In present paper, the mineral and fluid compositions of shale oil from the Songliao Basin are
analyzed systematically using core samples, X-ray diffractometer (XRD), and gas …

Physics informed neural networks applied to liquid state theory

FS Carvalho, JP Braga - Journal of Molecular Liquids, 2022 - Elsevier
The calculation of correlation functions for liquids is a problem that can be solved using
different methods such as molecular dynamics, integral equation theories or from …

Thermodynamic consistency by a modified Perkus–Yevick theory using the Mittag-Leffler function

FS Carvalho, JP Braga - Physica A: Statistical Mechanics and its …, 2021 - Elsevier
Closure relations that satisfies thermodynamical consistencies are very important, for it
implies physical consistent Ornstein–Zernike equation solutions. The method proposed by …

Partial radial distribution functions for a two-component glassy solid, GeSe, from scattering experimental data using an artificial intelligence framework

FS Carvalho, JP Braga - Journal of Molecular Modeling, 2022 - Springer
The Hopfield neural network has been applied successfully to solve ill-posed inverse
problems in simple monoatomic liquids structure using scattering experimental data to …

Radial distribution function for liquid gallium from experimental structure factor: a Hopfield neural network approach

FS Carvalho, JP Braga - Journal of Molecular Modeling, 2020 - Springer
Hopfield neural network was used to retrieve liquid gallium radial distribution function from
an experimental structure factor, obtained at 959 K. The inversion framework was carried out …

Indirect solution of Ornstein-Zernike equation using the Hopfield neural network method

FS Carvalho, JP Braga - Brazilian Journal of Physics, 2020 - Springer
Microscopic information, such as the pair distribution and direct correlation functions, can be
obtained from experimental data. From these correlation functions, thermodynamical …

Radial Distribution Function for a Hard Sphere Liquid: A Modified Percus-Yevick and Hypernetted-Chain Closure Relations

FS Carvalho, JP Braga - Journal of the Brazilian Chemical Society, 2021 - SciELO Brasil
Establishment of the radial distribution function by solving the Ornstein-Zernike equation is
still an important problem, even more than a hundred years after the original paper …

Adsorbate-adsorbent potential energy function from second virial coefficient data: a non-linear Hopfield Neural Network approach

FS Carvalho, JP Braga, MO Alves - Journal of Molecular Modeling, 2022 - Springer
Abstract The Hopfield Neural Network has been successfully applied to solve ill-posed
inverse problems in different fields of chemistry and physics. In this work, the non-linear …