Jeffrey Potoff

projects
Development of a GPU Optimized Monte Carlo Simulation Engine (ongoing)

Faculty Profile

Department Chair
ai8111@wayne.edu

Phone

313-577-9357

Building

Engineering

Room

1105

Google Scholar URL

http://scholar.google.com/citations?user=Hpxo5G0AAAAJ&hl=en

Biography

Department of Chemical Engineering, Wayne State University

  • Chair, 2020-present
  • Associate Dean for Academic Affairs, 2016-2020
  • Professor, 2014-present
  • Associate Professor, 2007-2014
  • Assistant Professor, 2001-2007

Courses Taught

  • ChE 2800 - Material and Energy Balances
  • ChE 3220 - Measurements Laboratory
  • ChE 3300 - Thermodynamics
  • ChE 3400 - Kinetics and Reactor Design
  • ChE 3820 - Unit Operations Laboratory
  • Che 4600 - Process Dynamics and Control
  • ChE 7300 - Advanced Thermodynamics
  • BE 1300/1310 - Science of Engineering Materials

Research Interests

Our research group focuses on the application of atom-based computer simulation (Monte Carlo and Molecular dynamics) to the design of new materials.  To achieve this goal, we develop new algorithms and models (force fields), and implement them in our open-source software GOMC.  Additionally, we are contributing to the development of the Molecular Simulation Design Framework (MoSDeF) software, which enables the creation of efficient, and reproducible workflows.  Students working on these projects develop skills in programming in python and/or C++, algorithm development, including artificial intelligence, and management of an open-source software project, in addition to expertise in their chosen area of domain science.  These computational methods are applied to a number of domain science areas.

Research Projects

Research Opportunities for Undergraduate and High School Students:

Because our research is computational, it can be performed with a laptop computer and a reliable Internet connection from anywhere in the world. If you are an undergraduate student at Wayne State, or other institution, and would like to learn about how physics-based computer simulations can be used to design new materials, we would be eager to work with you. Additionally, we have mentored a number of high school students in research projects remotely, and this is a good way to gain research experience if you don't have a nearby university.  High school students working with our lab have gone on to pursue undergraduate STEM degrees at universities such as Michigan, Georgia Tech, Penn State and University of Chicago as well as Wayne State University.

Development of High Performance Monte Carlo and hybrid Monte Carlo/Molecular Dynamics software:

Physics-based computer simulations are an essential tool for understanding the relationship between atomic-level interactions and physically observable properties of materials. It is from knowledge of structure-property relationships that new materials may be designed, with properties specifically tailored to address the problem of interest. The effectiveness of computer simulation, however, depends primarily on two things: the accuracy of the models used to describe interactions between molecules, and the ability to sample the relevant molecular configurations and conformations for the system of interest.

In this project, we are focused on improving the efficiency of atom-based computer simulations through the development of improved sampling algorithms.  These algorithms are implemented in our high performance Monte Carlo software known as GOMC (https://gomc-wsu.org/).  Additionally, our lab develops the software py-MCMD (https://github.com/GOMC-WSU/py-MCMD/), which links GOMC to the molecular dynamics software NAMD (https://www.ks.uiuc.edu/Research/namd/), enabling users to perform hybrid MC/MD simulations.  Significant effort is spent optimizing the performance of our software on multi-core and GPU architectures. 

Understanding Wax Nucleation in Oil Pipelines:

The formation of blockages in oil pipelines and wells is a significant problem in the production of crude oil. Blockages may result from the formation of gas hydrates, self-assembly of asphaltenes, and/or the deposition of wax. Wax formation is especially problematic in oil in undersea pipelines, where the temperature of the surroundings may be as low was 4 C. To counteract the tendency of longer n-alkanes to deposit on pipeline walls, it is common to add chemical wax inhibitors and/or pour point depressants, such as ethylene vinyl acetate (EVA) copolymers. Despite extensive experimental efforts to develop more effective wax controls, e.g. nano-hybrids, to date, no universal wax inhibitor exists. Instead, optimal treatment strategies for wax inhibition remain largely trial and error.

In this project, we use molecular dynamics simulations to understand the molecular mechanisms through which wax inhibitors work. By understanding these mechanisms, it is possible to design new wax inhibitors with improved properties compared to existing formulations.

Prediction of Environmental Fate and Transport of Fluorinated Surfactants:

Perfluoroalkyl substances (PFAS) are a broad class of compounds where fluorine has been substituted for hydrogen on the alkyl chains. The most widely used and industrially relevant PFAS are surfactants, where fluorination of the alkyl tails renders them both hydrophobic and oleophobic, giving rise to unusual properties, such as exceptional chemical and thermal stability and very low interfacial tension at the air-water interface. Owing to their unique properties, PFAS are used in a broad array of consumer applications, including coatings for non-stick cookware, grease-resistant paper, and stain resistant fabrics. Industrial applications include fire-fighting foams and mist-suppressants in hard chrome plating. While having outstanding properties as surfactants, PFAS are both water soluble and very resistant to degredation in the environment. Therefore, they have significant potential for ground water contanmination and bioaccumulation. More than 4700 perfluorinated alkyl substances are known to exist, with new compounds being synthesized each year.

In my lab, we are using Monte Carlo and molecular dynamics simulations to predict the physical properties of PFAS compounds. This is a natural application for computer simulation, given that more than 8000 perfluorinated alkyl substances are known to exist, with new compounds being synthesized each year. In addition to physical properties, computer simulations provide atomic-level insight, informing the development of new surfactants with reduced environmental impact, and/or porous materials for the removal of PFAS from drinking water supplies.

Publications

Selected recent publications:

  1. Alexey Illarionov, Serzhan Sakipov, Leonid Pereyaslavets, Igor V Kurnikov, Ganesh Kamath, Oleg Butin, Ekaterina Voronina, Ilya Ivahnenko, Igor Leontyev, Grzegorz Nawrocki, Mikhail Darkhovskiy, Michael Olevanov, Yevhen K Cherniavskyi, Christopher Lock, Sean Greenslade, Subramanian KRS Sankaranarayanan, Maria G Kurnikova, Jeffrey Potoff, Roger D Kornberg, Michael Levitt, Boris Fain, "Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions," JACS, 145, 23620-23629 (2023).
  2. Brad Crawford, Umesh Timalsina, Co D. Quach, Nicholas C. Craven, Justin B. Gilmer, Clare McCabe, Peter T. Cummings, Jeffrey J. Potoff*, "MoSDeF-GOMC: Python Software for the Creation of Scientific Workflows for the Monte Carlo Simulation Engine GOMC, "63, 1218-1228 (2023).
  3. Mohammad Soroush Barhaghi, Brad Crawford, Gregory Schwing, David Hardy, John E. Stone, Loren Schwiebert, Jeffrey Potoff*, and Emad Tajkhorshid, “py-MCMD: Python Software for Performing Hybrid Monte Carlo – Molecular Dynamics Simulations with GOMC and NAMD,” J. Chem. Theory Comput., 19, 4983-4994 (2022). [Cover][Research Highlight Video]
  4. Leonid Pereyaslavets, Ganesh Kamath, Oleg Butin, Alexey Illarionov, Michael Olevanov, Igor Kurnikov, Serzhan Sakipov, Igor Leontyev, Ekaterina Voronina, Tyler Gannon, Grzegorz Nawrocki, Mikhail Darkhovskiy, Ilya Ivahnenko, Alexander Kostikov, Jessica Scaranto, Maria G. Kurnikova3, Suvo Banik, Henry Chan, Michael G. Sternberg, Subramanian Sankaranarayanan, Brad Crawford, Jeffrey Potoff, Michael Levitt, Roger D. Kornberg, Boris Fain,” Accurate determination of solvation free energies of neutral organic compounds from first principles,” Nature Communications, 13, 414 (2022).
  5. Peter T. Cummings, Clare McCabe, Christopher R. Iacovella, Akos Ledeczi, Eric Jankowski, Arthi Jayaraman, Jeremy C. Palmer, Edward J. Maginn, Sharon C. Glotzer, Joshua A. Anderson, J. Ilja Siepmann, Jeffrey Potoff, Ray A. Matsumoto, Justin B. Gilmer, Ryan S. DeFever, Ramanish Singh, Brad Crawford, “Open‐source molecular modeling software in chemical engineering focusing on the Molecular Simulation Design Framework,” AICHE J, 67, e17206 (2021)
  6. Younes Nejahi, Mohammad Soroush Barhaghi, Gregory Schwing, Loren Schwiebert, Jeffrey Potoff*, Update 2.70 to “GOMC: GPU Optimized Monte Carlo for the simulation of phase equilibria and physical properties of complex fluids,” SoftwareX 13, 100627, (2020).
  7. Mohammad Soroush Barhaghi, Jeffrey J. Potoff*, “Effect of fluorination on the partitioning of alcohols,” Mol. Phys. 117 (23-24), 3827-3839 (2019).
  8. Younes Nejahi, Mohammad Soroush Barhaghi, Jason Mick, Brock Jackman, Kamel Rushaidat, Yuanzhe Li, Loren Schwiebert, Jeffrey Potoff*, “GOMC: GPU Optimized Monte Carlo for the simulation of phase equilibria and physical properties of complex fluids,” SoftwareX 9, 20-27 (2019). https://doi.org/10.1016/j.softx2018.11.005.
  9. Mohammad Soroush Barhaghi, Korosh Torabi, Younes Nejahi, Loren Schwiebert, and Jeffrey J. Potoff, “Molecular Exchange Monte Carlo. A generalized method for identity exchanges in grand canonical Monte Carlo simulations,” J. Chem. Phys. 149, 072318 (2018).
  10. Jason R. Mick, Mohammad Soroush Barhaghi, Brock Jackman, Loren Schwiebert, and Jeffrey J. Potoff*, “Optimized Mie Potentials for Phase Equilibria: Application to Branched Alkanes,” J. Chem. Eng. Data. 62, 1806-1818 (2017).
  11. Mohammad Soroush Barhaghi, Jason R. Mick and Jeffrey J. Potoff*, “Optimized Mie Potentials for Phase Equilibria: Application to Alkynes,” Molec. Phys. (2017), 1-11, [invited paper] DOI: 10.1080/00268976.2017.1297862.

Awards and Honors

  • President's Award for Excellence in Teaching: 2014
  • Detroit AICHE section, Chemical Engineer of the Year: 2008
  • College of Engineering Excellence in Teaching Award: 2003-2004
  • Engineering Student Faculty Board, Outstanding Faculty Service: 2002, 2003, 2004
  • Minnesota Supercomputing Institute Research Scholar: 2000

Websites

 http://gomc.eng.wayne.edu/
https://github.com/GOMC-WSU
LinkedIn Profile 

Education

Post-Doctoral, Chemistry, University of Minnesota (advisor: J. Ilja Siepmann), 2000
Ph.D., Chemical Engineering, Cornell University (advisor: Athanassios Z. Panagiotopoulos), 1999
B.Sc, Chemical Engineering, Michigan State University, 1994

Research Description

Our research group focuses on the application of computer simulation at various length scales (sub-atomic, atomic, and mesoscale) to the following areas:

Force field development for complex fluids.
Vapor-liquid, solid-liquid equilibria and critical phenomena.
Prediction of environmental impact of energetic materials and chemical warfare agents.
Mechanisms of membrane fusion.
Novel materials development.

Affiliated Departments