Skip to main content
OSTI.GOVU.S. Department of Energy Office of Scientific and Technical Information
U.S. Department of Energy
Office of Scientific and Technical Information
 

Trends in Ionic Liquid Diffusion in Graphite Slit Pores from Molecular Dynamics Simulation and Machine Learning

Conference ·
DOI:https://doi.org/10.2172/2540280· OSTI ID:2540280
 [1];  [2];  [1];  [1];  [1];  [1];  [1];  [3]
  1. Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
  2. Chemical Sciences and Engineering Division, Argonne National Laboratory
  3. ACC Consulting New Mexico
+ Show Author Affiliations
Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
Laboratory Directed Research and Development
DOE Contract Number:
NA0003525
OSTI ID:
2540280
Report Number(s):
SAND2024-03465C
Country of Publication:
United States
Language:
English

Similar Records

Machine Learning Based Upscaling of Finite-Box Size Molecular Dynamics Diffusion Simulations.
Conference · Sat Aug 01 00:00:00 EDT 2020 · OSTI ID:1814581
Machine Learning Applications for Molecular Dynamics Simulations.
Conference · Sun Jul 01 00:00:00 EDT 2018 · OSTI ID:1575041
Machine Learning Prediction of Lennard-Jones Fluid Self-Diffusion in Pores.
Conference · Thu Jul 01 00:00:00 EDT 2021 · OSTI ID:1884090

Related Subjects