Table of Contents

Crunch DPD

One of the main research areas of the CRUNCH group is to develop and employ stochastic multiscale computational techniques to diverse problems in complex fluids and soft matter. Currently, we are working on this research area developing different simulation techniques including Dissipative Particle Dynamics (DPD), Smooth DPD (SDPD), and Smoothed Particle Hydrodynamics (SPH) as well as concurrent coupling between these methods. The DPD Club meets weekly in the Division of Applied Mathematics at Brown University in order to provide opportunities for enhanced exchanges and collaborative research among researchers interested in DPD, either inside or outside of the group. Our main sponsors are the Department of Energy (DOE) via the Collaboratory on Mathematics for Mesoscopic Modeling of Materials (CM4) and the National Institute of Health.

Research Themes and Topics

In recent months, we discussed topics related to:



Weekly Seminar

Main article: List of Previous DPD Club Meeting Topics

The group holds weekly seminars. A few samples of topics discussed during the previous meetings are:


If you have done exciting work on DPD or other particle-based methods and you would like to share it with us, just contact Dr Xuejin Li, Xuejin. If you are interested in visiting us, we will cover related travelling and accommodation expenses.


A couple of software projects have been actively developed within the group and available under the GPL license to the general public.





Group Publications

Main article: List of Crunch Group Publications on DPD

  1. L. Lu, H. Li, X. Bian, X. Li, and G. E. Karniadakis. Mesoscopic adaptive resolution scheme toward understanding of interactions between sickle cell fibers. Biophys. J., 2017, 113, 48-59. (Cover Article)
  2. H.-Y. Chang, X. Li, and G. E. Karniadakis. Modeling of biomechanics and biorheology of red blood cells in type-2 diabetes mellitus. Biophys. J., 2017, 113, 481-490. (BJ Highlighted Article)
  3. Y.-H. Tang, L. Lu, H. Li, C. Evangelinos, L. Grinberg, V. Sachdeva, and G. E. Karniadakis. OpenRBC: A fast simulator of red blood cells at protein resolution. Biophys. J., 2017, 112, 2030-2037.
  4. A. L. Blumers, Y.-H. Tang, Z. Li, X. Li and G. E. Karniadakis. GPU-accelerated red blood cells simulations with transport dissipative particle dynamics. Comput. Phys. Commun., 2017, 217, 171-179.
  5. X. Li, E. Du, M. Dao, S. Suresh, and G. E. Karniadakis. Patient-specific modeling of individual sickle cell behavior under transient hypoxia. PLOS Comput. Biol., 2017, 13, e1005426.
  6. X Bian, C Kim, GE Karniadakis. 111 years of Brownian motion. Soft Matter, 2016, 12, 6331-6346.
  7. H.-Y. Chang, X. Li, H. Li, and G. E. Karniadakis. MD/DPD multiscale framework for predicting morphology and stresses of red blood cells in health and disease. PLOS Comput. Biol. 2016, 12, e1005173.
  8. Y.-H. Tang, S. Kudo, X. Bian, Z. Li and G. E. Karniadakis. Multiscale Universal Interface: A Concurrent Framework for Coupling Heterogeneous Solvers. J. Comput. Phys., 2015, 297, 13-31.
  9. Z. Li, Y.-H. Tang, X. J. Li and G. E. Karniadakis. Mesoscale modeling of phase transition of thermoresponsive polymers. Chem. Commun., 2015, 51, 11038-11040.
  10. K. Lykov, X. J. Li, I. V. Pivkin and G. E. Karniadakis. Inflow/Outflow boundary conditions for particle-based blood flow simulations: Application to arterial bifurcations and trees. PLOS Comput. Biol., 2015, 11, e1004410.
  11. Y.-H. Tang and G. E. Karniadakis. Accelerating Dissipative Particle Dynamics Simulations on GPUs: Algorithms, Numerics and Applications. Comput. Phys. Commun., 2014, 185, 2809-2822.
  12. Z. Li, Y.-H. Tang, H. Lei, B. Caswell and G.E. Karniadakis. Energy-conserving dissipative particle dynamics with temperature-dependent properties. J. Comput. Phys., 2014, 265, 113-127.
  13. X. J. Li, Y.-H. Tang, H. J. Liang and G. E. Karniadakis. Large-scale dissipative particle dynamics simulations of self-assembly amphiphilic systems. Chem. Commun., 2014, 50, 8306-8308.
  14. H. Lei and G. E. Karniadakis. Probing vaso-occlusion phenomena in sickle cell anemia via mesoscopic simulations. Proc. Natl. Acad. Sci. USA, 2013, 110, 11326-11330.
  15. Z. L. Peng, X. J. Li, I. V. Pivkin, M. Dao, G. E. Karniadakis and S. Suresh. Lipid-bilayer and cytoskeletal interactions in a red blood cell. Proc. Natl. Acad. Sci. USA, 2013, 110, 13356-13361.
  16. D. A. Fedosov, W. Pan, B. Caswell, G. Gompper and G. E. Karniadakis. Predicting human blood viscosity in silico. Proc. Natl. Acad. Sci. USA, 2011, 108, 11772-11777.
  17. D. A. Fedosov, B. Caswell, S. Suresh and G. E. Karniadakis. Quantifying the biophysical characteristics of Plasmodium-falciparum-parasitized red blood cells in microcirculation. Proc. Natl. Acad. Sci. USA, 2011, 108, 35-39.
  18. I. V. Pivkin and G. E. Karniadakis. Accurate coarse-grained modeling of red blood cells. Phys. Rev. Lett., 2008, 101, 118105.
  19. I. V. Pivkin and G. E. Karniadakis. Controlling density fluctuations in wall bounded DPD systems. Phys. Rev. Lett., 2006, 96, 206001.
  20. V. Symeonidis, G. E. Karniadakis and B. Caswell. Dissipative particle dynamics simulations of polymer chains: Scaling laws and shearing response compared to DNA experiments. Phys. Rev. Lett., 2005, 95, 076001.

Ph.D. Thesis of Graduated Students

DPD Lecture Note

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