Michael S. Murillo
BSEE, University of New Mexico
PhD, Physics, Rice University
Michael Murillo is a theoretical and computational physicist focusing on particle-based methods for simulating interacting systems of particles (molecular dynamics), fluids (smoothed-particle hydrodynamics) or people (agent-based modeling). His career began as a Director’s Postdoctoral Fellow in the Theoretical Division at Los Alamos National Laboratory (LANL), after which he was a staff scientist at LANL for many years. Prof. Murillo currently has a joint appointment here at MSU in the CMSE and CHEMS departments. He has more than 80 peer-reviewed publications, and he is a Fellow of the American Physical Society.
• Computational plasma physics
• Molecular dynamics simulations of non-ideal plasmas
• Agent-based modeling of infectious disease outbreaks
Scientific Leader: Dr. Michael Murillo
Our group is involved in the two seemingly disparate research directions of computational plasma physics and agent-based modeling. In both cases, we employ computational methods for interacting many-body systems to understand the collective dynamics of the systems we study.
The Murillo Group has recently released a new paper published by The Journal of Statistical Physics on August, 2017 about Conservative, Entropic Multispecies BGK Model.
CMSE researchers Gautham Dharuman & Michael Murillo have a new paper published by The Journal of Chemical Physics for their work involving Ewald method and medium-range interactions for charged-particle systems.
The Murillo Group has released a new paper published by Physical Review E on April 10th, 2017 about Hydrogen Plasmas within the Coupled-mode Regime.
M. S. Murillo & M. Marciante published a new paper on Thermodynamic and Kinetic Properties in Phys. Rev. Lett. 118, 025001 – 10 January 2017
The Murillo group is developing new computational methods for modeling non-ideal plasmas using both high-performance computing and machine learning techniques. Research will be carried out in the areas of magnetized ultracold plasmas, transport in non-ideal plasmas and implementation of new HPC methods in our MD code Sarkas. The successful applicant will work with Professor Murillo and other members of his group, and will have a strong background or interest in plasma physics, quantum mechanics, statistical mechanics, numerical methods, scientific computing, machine learning and multiscale modeling. https://murillogroupmsu.com/
A viscous quantum hydrodynamics model based on dynamic density functional theory
A Diaw, MS Murillo
Scientific Reports, in press, 2017
Interfacial mixing in high-energy-density matter with a multiphysics kinetic model
JR Haack, CD Hauck, MS Murillo
Physical Review E, in press, 2017
Controllable non-ideal plasmas from photoionized compressed gases
G Dharuman, LG Stanton, MS Murillo
Physical Review Letters, in press, 2017
FS-17: CMSE 201 Intro to Computational Modeling
FS-17: CMSE 499 Independent Study in CMSE
SS-18: CMSE 890 Section 002 Particle Methods of Simulations
FS-18: CMSE 890 Section 001 Kinetic Theory
Click "Teaching" link to see past courses.