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Ionic liquids for the separation of fluorocarbon refrigerant mixtures
KR Baca, K Al-Barghouti, N Wang, MG Bennett… - Chemical …, 2024 - ACS Publications
This review discusses the research being performed on ionic liquids for the separation of
fluorocarbon refrigerant mixtures. Fluorocarbon refrigerants, invented in 1928 by Thomas …
fluorocarbon refrigerant mixtures. Fluorocarbon refrigerants, invented in 1928 by Thomas …
Molecular modeling applied to corrosion inhibition: a critical review
JM Castillo-Robles, E de Freitas Martins… - npj Materials …, 2024 - nature.com
In the last few years, organic corrosion inhibitors have been used as a green alternative to
toxic inorganic compounds to prevent corrosion in materials. Nonetheless, the fundamental …
toxic inorganic compounds to prevent corrosion in materials. Nonetheless, the fundamental …
The (Re)-Evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods
In their seminal work on quantitative structure− activity relationship (QSAR), Hansch and co-
workers predicted in 1962 that Hammett functions and partition coefficients would become …
workers predicted in 1962 that Hammett functions and partition coefficients would become …
Machine-learned molecular mechanics force fields from large-scale quantum chemical data
The development of reliable and extensible molecular mechanics (MM) force fields—fast,
empirical models characterizing the potential energy surface of molecular systems—is …
empirical models characterizing the potential energy surface of molecular systems—is …
Open-source machine learning in computational chemistry
A Hagg, KN Kirschner - Journal of chemical information and …, 2023 - ACS Publications
The field of computational chemistry has seen a significant increase in the integration of
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
The open force field initiative: Open software and open science for molecular modeling
L Wang, PK Behara, MW Thompson… - The Journal of …, 2024 - ACS Publications
Force fields are a key component of physics-based molecular modeling, describing the
energies and forces in a molecular system as a function of the positions of the atoms and …
energies and forces in a molecular system as a function of the positions of the atoms and …
Molecular modelling of the thermophysical properties of fluids: expectations, limitations, gaps and opportunities
MJ Tillotson, NI Diamantonis, C Buda… - Physical Chemistry …, 2023 - pubs.rsc.org
This manuscript provides an overview of the current state of the art in terms of the molecular
modelling of the thermophysical properties of fluids. It is intended to manage the …
modelling of the thermophysical properties of fluids. It is intended to manage the …
Structure and dynamics of hydrofluorocarbon/ionic liquid mixtures: an experimental and molecular dynamics study
The physical properties of four ionic liquids (ILs), including 1-n-butyl-3-methylimidazolium
tetrafluoroborate ([C4C1im][BF4]), 1-n-butyl-3-methylimidazolium hexafluorophosphate …
tetrafluoroborate ([C4C1im][BF4]), 1-n-butyl-3-methylimidazolium hexafluorophosphate …
Integrating machine learning in the coarse-grained molecular simulation of polymers
E Ricci, N Vergadou - The Journal of Physical Chemistry B, 2023 - ACS Publications
Machine learning (ML) is having an increasing impact on the physical sciences,
engineering, and technology and its integration into molecular simulation frameworks holds …
engineering, and technology and its integration into molecular simulation frameworks holds …
Refining potential energy surface through dynamical properties via differentiable molecular simulation
B Han, K Yu - Nature Communications, 2025 - nature.com
Recently, machine learning potential (MLP) largely enhances the reliability of molecular
dynamics, but its accuracy is limited by the underlying ab initio methods. A viable approach …
dynamics, but its accuracy is limited by the underlying ab initio methods. A viable approach …