A review on machine learning algorithms for the ionic liquid chemical space
There are thousands of papers published every year investigating the properties and
possible applications of ionic liquids. Industrial use of these exceptional fluids requires …
possible applications of ionic liquids. Industrial use of these exceptional fluids requires …
Machine learning assisted molecular modeling from biochemistry to petroleum engineering: A review
G Ma, J Shi, H Xiong, C Xiong, R Zhao… - Geoenergy Science and …, 2024 - Elsevier
Unconventional reservoirs have emerged as pivotal contributors, responsible for over 50%
of total US oil production. Yet, comprehending the intricate mechanisms of fluid transport in …
of total US oil production. Yet, comprehending the intricate mechanisms of fluid transport in …
Reduced-order model for multiphysics simulations of CNT/Polymer Composites via principal component regression and artificial neural networks
In this work, the stochastic microstructure of simulated CNT-polymer composite statistical
volume elements (SVEs) is quantified using two-point correlation functions. The two-point …
volume elements (SVEs) is quantified using two-point correlation functions. The two-point …
Learning everywhere: Pervasive machine learning for effective high-performance computation
The convergence of HPC and data intensive methodologies provide a promising approach
to major performance improvements. This paper provides a general description of the …
to major performance improvements. This paper provides a general description of the …
Machine learning surrogates for molecular dynamics simulations of soft materials
Molecular dynamics (MD) simulations accelerated by high-performance computing (HPC)
methods are powerful tools to investigate and extract the microscopic mechanisms …
methods are powerful tools to investigate and extract the microscopic mechanisms …
Mapa: Multi-accelerator pattern allocation policy for multi-tenant gpu servers
K Ranganath, JD Suetterlein, JB Manzano… - Proceedings of the …, 2021 - dl.acm.org
Multi-accelerator servers are increasingly being deployed in shared multi-tenant
environments (such as in cloud data centers) in order to meet the demands of large-scale …
environments (such as in cloud data centers) in order to meet the demands of large-scale …
Probing the rheological properties of liquids under conditions of elastohydrodynamic lubrication using simulations and machine learning
JCS Kadupitiya, V Jadhao - Tribology Letters, 2021 - Springer
In elastohydrodynamic lubrication (EHL), the lubricant experiences pressures in excess of
500 MPa and strain rates larger than 10 5 s-1. The high pressures lead to a dramatic rise in …
500 MPa and strain rates larger than 10 5 s-1. The high pressures lead to a dramatic rise in …
Machine learning for parameter auto-tuning in molecular dynamics simulations: Efficient dynamics of ions near polarizable nanoparticles
JCS Kadupitiya, GC Fox… - The International Journal …, 2020 - journals.sagepub.com
Simulating the dynamics of ions near polarizable nanoparticles (NPs) using coarse-grained
models is extremely challenging due to the need to solve the Poisson equation at every …
models is extremely challenging due to the need to solve the Poisson equation at every …
Solving Newton's equations of motion with large timesteps using recurrent neural networks based operators
Classical molecular dynamics simulations are based on solving Newton's equations of
motion. Using a small timestep, numerical integrators such as Verlet generate trajectories of …
motion. Using a small timestep, numerical integrators such as Verlet generate trajectories of …
Molecular dynamics simulations on cloud computing and machine learning platforms
Scientific computing applications have benefited greatly from high performance computing
infrastructure such as supercomputers. However, we are seeing a paradigm shift in the …
infrastructure such as supercomputers. However, we are seeing a paradigm shift in the …