Professor Ilja Siepmann

Project Title: 
Simulating Complex Chemical Systems and Processes

The Siepmann group develops a variety of computational chemistry tools including: Monte Carlo algorithms for efficient sampling of macromolecular conformations and spatial distributions in multi-component multi-phase systems; accurate and transferable force fields with multiple levels of resolution; first principles simulation approaches; high-throughput simulation and machine learning approaches for the discovery of functional materials; and large-scale molecular simulations to investigate thermodynamic and transport properties relevant to turbulent multi-phase flows of aqueous systems. The group investigates phase, sorption, and chemical equilibria, self-aggregation behavior and partitioning in polar and non-polar bulk fluids and in heterogeneous and interfacial systems.

In particle, the Siepmann group's efforts are directed to:

  • High-throughput screening of nanoporous materials for energy applications (gas storage, chemical separations, water harvesting, and adsorption cooling)
  • Understanding chromatographic retention processes including various forms of liquid chromatography, supercritical fluid chromatography, and size exclusion chromatography
  • Understanding the solvation mechanisms in liquid-liquid and supercritical extraction systems and in surfactant solutions
  • Bubble nucleation and multi-phase flow
  • Predicting reactive phase equilibria using first principles simulations

The Siepmann group develops its own software for Monte Carlo simulations (MCCCS-MN) and utilizes various open-source software for molecular dynamics simulations (GROMACS, LAMMPS, HOOMD, and CP2K). On MSI's infrastructure, some of the group's applications use a parallelization hierarchy where large-scale distribution (e.g., 12 independent trajectories at 16 different state points/compositions) of small, but long runs (1 to 12 cores for 24 hours) are employed, whereas first principles simulations can efficiently utilize 256 to 8,192 cores. Some of the MC/MD software benefits from GPU acceleration. Beyond MSI, the group's software is also deployed on the high-performance computers at the Argonne Leadership Computing Facility and a Lawrence Livermore National Laboratory.

Research from this group was featured on the MSI website in:

Project Investigators

Naomi Trampe
Kha Trinh
Stephanie Zakhia
Caini Zheng
 
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