Faculty Mentor
Dr. Jungkyu (Justin) Park
Proposal Type
Oral Presentation
Start Date
2-11-2019 8:00 AM
End Date
2-11-2019 9:00 AM
Location
Nesbitt 2201
Abstract
In this research study, we employ machine learning algorithms to perform molecular dynamics simulations for graphene-like 3D carbon nanostructures. Custom MATLAB programs and Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) are used to conduct the simulations in this report. The results obtained in this research will accelerate the development of more advanced nanomaterials such as 3D carbon nanostructures by improving the accuracy of the simulations of their material properties.
Included in
Mechanical Engineering Commons, Polymer and Organic Materials Commons, Structural Materials Commons
Machine Learning For Designing Stretchable Carbon Nanostructures
Nesbitt 2201
In this research study, we employ machine learning algorithms to perform molecular dynamics simulations for graphene-like 3D carbon nanostructures. Custom MATLAB programs and Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) are used to conduct the simulations in this report. The results obtained in this research will accelerate the development of more advanced nanomaterials such as 3D carbon nanostructures by improving the accuracy of the simulations of their material properties.
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