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Systematic Coarse Graining: “Four Lessons and A Caveat” from Nonequilibrium Statistical Mechanics

Published online by Cambridge University Press:  31 January 2011

Hans Christian Öttinger
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Abstract

With the guidance offered by nonequilibrium statistical thermodynamics, simulation techniques are elevated from brute-force computer experiments to systematic tools for extracting complete, redundancy-free, and consistent coarse-grained information for dynamic systems. We sketch the role and potential of Monte Carlo, molecular dynamics, and Brownian dynamics simulations in the thermodynamic approach to coarse graining. A melt of entangled linear polyethylene molecules serves us as an illustrative example.

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Research Article
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MRS Bulletin , Volume 32 , Issue 11: Multiscale Modeling in Advanced Materials Research , November 2007 , pp. 936 - 940
Copyright
Copyright © Materials Research Society 2007

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References

1.Grmela, M., Öttinger, H.C., Phys. Rev. E 56, 6620 (1997).CrossRefGoogle Scholar
2.Öttinger, H.C., Grmela, M., Phys. Rev. E 56, 6633 (1997).CrossRefGoogle Scholar
3.Öttinger, H.C., Beyond Equilibrium Thermodynamics (Wiley, Hoboken, N.J., 2005).CrossRefGoogle Scholar
4.de Groot, S.R., Mazur, P., Non-Equilibrium Thermodynamics (Dover, New York, 1984, ed. 2).Google Scholar
5.Kubo, R., Toda, M., Hashitsume, N., Nonequilibrium Statistical Mechanics, Vol. II of Statistical Physics (Springer, Berlin, 1991, ed. 2).Google Scholar
6.Grabert, H., Projection Operator Techniques in Nonequilibrium Statistical Mechanics (Springer, Berlin, 1982).CrossRefGoogle Scholar
7.Öttinger, H.C., Phys. Rev. E 57, 1416 (1998).CrossRefGoogle Scholar
8.Gorban, A.N., Kazantzis, N., Kevrekidis, I.G., Öttinger, H.C., Theodoropoulos, C., Eds., Model Reduction and Coarse-Graining Approaches for Multiscale Phenomena (Springer, Berlin, 2006).CrossRefGoogle Scholar
9.Milano, G., Müller-Plathe, F., J. Phys. Chem. B 109, 18609 (2005).CrossRefGoogle Scholar
10.Sun, Q., Faller, R., Macromolecules 39, 812 (2006).CrossRefGoogle Scholar
11.Harmandaris, V.A., Adhikari, N.P., van der Vegt, N.F.A., Kremer, K., Macromolecules 39, 6708 (2006).CrossRefGoogle Scholar
12.Padding, J.T., Briels, W.J., J. Chem. Phys. 117, 925 (2002).CrossRefGoogle Scholar
13.Öttinger, H.C., J. Chem. Phys. 86, 3731 (1987).CrossRefGoogle Scholar
14.Öttinger, H.C., J. Chem. Phys. 90, 463 (1989).CrossRefGoogle Scholar
15.Kröger, M., Models for Polymeric and Anisotropic Liquids, No. 675 in Lecture Notes in Physics (Springer, Berlin, 2005).Google Scholar
16.Mavrantzas, V.G., Öttinger, H.C., Macromolecules 35, 960 (2002).CrossRefGoogle Scholar
17.Marinari, E., Parisi, G., Europhys. Lett. 19, 451 (1992).CrossRefGoogle Scholar
18.Tesi, M.C., Janse van Rensburg, E.J., Orlandini, E., Whittington, S.G., J. Stat. Phys. 82, 155 (1996).CrossRefGoogle Scholar
19.Faller, R., Yan, Q., de Pablo, J.J., J. Chem. Phys. 116, 5419 (2002).CrossRefGoogle Scholar
20.Wang, F., Landau, D.P., Phys. Rev. Lett. 86, 2050 (2001).CrossRefGoogle Scholar
21.Wang, F., Landau, D.P., Phys. Rev. E 64, 056101 (2001).CrossRefGoogle Scholar
22.Faller, R., de Pablo, J.J., J. Chem. Phys. 119, 4405 (2003).CrossRefGoogle Scholar
23.Landau, D.P., Binder, K., A Guide to Monte Carlo Simulations in Statistical Physics (Cambridge University Press, Cambridge, U.K., 2000).Google Scholar
24.Binder, K., Heermann, D.W., Monte Carlo Simulation in Statistical Physics, Springer Series in Solid-State Sciences 80 (2) (Springer, Berlin, 1992).Google Scholar
25.Mouritsen, O.G., Computer Studies of Phase Transitions and Critical Phenomena, Springer Series in Computational Physics (Springer, Berlin, 1984).CrossRefGoogle Scholar
26.Allen, M.P., Tildesley, D.J., Computer Simulation of Liquids (Clarendon, Oxford, 1987).Google Scholar
27.Öttinger, H.C., Stochastic Processes in Polymeric Fluids: Tools and Examples for Developing Simulation Algorithms (Springer, Berlin, 1996).CrossRefGoogle Scholar
28.Nosé, S., Mol. Phys. 52, 255 (1984).CrossRefGoogle Scholar
29.Hoover, W.G., Phys. Rev. A 31, 1695 (1995).CrossRefGoogle Scholar
30.Bond, S.D., Leimkuhler, B.J., Laird, B.B., J. Comput. Phys. 151, 114 (1999).CrossRefGoogle Scholar
31.Leimkuhler, B., Comput. Phys. Commun. 148, 206 (2002).CrossRefGoogle Scholar
32.Andersen, H.C., J. Chem. Phys. 72, 2384 (1980).CrossRefGoogle Scholar
33.Doi, M., Edwards, S.F., The Theory of Polymer Dynamics, International Series of Monographs on Physics 73 (Clarendon, Oxford, 1986).Google Scholar
34.Kröger, M., Ramírez, J., Öttinger, H.C., Polymer 43, 477 (2002).CrossRefGoogle Scholar
35.Ianniruberto, G., Marrucci, G., J. Non-Newtonian Fluid Mech. 79, 225 (1998).CrossRefGoogle Scholar
36.Marrucci, G., Ianniruberto, G., J. Non-Newtonian Fluid Mech. 82, 275 (1999).CrossRefGoogle Scholar
37.Öttinger, H.C., J. Non-Newtonian Fluid Mech. 89, 165 (2000).CrossRefGoogle Scholar
38.Harmandaris, V.A., Mavrantzas, V.G., Theodorou, D.N., Macromolecules 31, 7934 (1998).CrossRefGoogle Scholar
39.Harmandaris, V.A., Mavrantzas, V.G., Theodorou, D.N., Macromolecules 33, 8062 (2000).CrossRefGoogle Scholar
40.Harmandaris, V.A., Mavrantzas, V.G., Theodorou, D.N., Kröger, M., Ramírez, J., Öttinger, H.C., Vlassopoulos, D., Macromolecules 36, 1376 (2003).CrossRefGoogle Scholar
41.Öttinger, H.C., Phys. Rev. E 50, 4891 (1994).CrossRefGoogle Scholar