ESPResSo++: A modern multiscale simulation package for soft matter systems

Abstract The redesigned Extensible Simulation Package for Research on Soft matter systems (ESPResSo++) is a free, open-source, parallelized, object-oriented simulation package designed to perform many-particle simulations, principally molecular dynamics and Monte Carlo, of condensed soft matter systems. In addition to the standard simulation methods found in well-established packages, ESPResSo++ provides the ability to perform Adaptive Resolution Scheme (AdResS) simulations which are multiscale simulations of molecular systems where the level of resolution of each molecule can change on-the-fly. With the main design objective being extensibility, the software features a highly modular C++ kernel that is coupled to a Python user interface. This makes it easy to add new algorithms, setup a simulation, perform online analysis, use complex workflows and steer a simulation. The extreme flexibility of the software allows for the study of a wide range of systems. The modular structure enables scientists to use ESPResSo++ as a research platform for their own methodological developments, which at the same time allows the software to grow and acquire the most modern methods. ESPResSo++ is targeted for a broad range of architectures and is licensed under the GNU General Public License.

[1]  Kurt Kremer,et al.  Molecular dynamics simulation study of nonconcatenated ring polymers in a melt. II. Dynamics. , 2011, The Journal of chemical physics.

[2]  L Delle Site,et al.  Adaptive resolution simulation of liquid para-hydrogen: testing the robustness of the quantum-classical adaptive coupling. , 2011, Physical chemistry chemical physics : PCCP.

[3]  Dirk Reith,et al.  Properties of Poly(isoprene): Model Building in the Melt and in Solution , 2003 .

[4]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[5]  Dirk Reith,et al.  Assessment of numerical optimization algorithms for the development of molecular models , 2010, Comput. Phys. Commun..

[6]  Jianpeng Ma,et al.  CHARMM: The biomolecular simulation program , 2009, J. Comput. Chem..

[7]  Matej Praprotnik,et al.  Coupling different levels of resolution in molecular simulations. , 2009, The Journal of chemical physics.

[8]  A. Arnold,et al.  Simulations of non-neutral slab systems with long-range electrostatic interactions in two-dimensional periodic boundary conditions. , 2009, The Journal of chemical physics.

[9]  K. Kremer,et al.  Adaptive resolution molecular-dynamics simulation: changing the degrees of freedom on the fly. , 2005, The Journal of chemical physics.

[10]  E. W. Meijer,et al.  About Supramolecular Assemblies of π‐Conjugated Systems , 2005 .

[11]  K. Kremer,et al.  Multiscale simulation in polymer science , 2002 .

[12]  P. P. Ewald Die Berechnung optischer und elektrostatischer Gitterpotentiale , 1921 .

[13]  Matt Probert,et al.  Langevin dynamics in constant pressure extended systems. , 2004, The Journal of chemical physics.

[14]  Karl N. Kirschner,et al.  A modern workflow for force-field development - Bridging quantum mechanics and atomistic computational models , 2011, Comput. Phys. Commun..

[15]  PMI-Parallel Method Invocation , 2009 .

[16]  Dirk Reith,et al.  Liquidliquid equilibria of dipropylene glycol dimethyl ether and water by molecular dynamics , 2011 .

[17]  H. C. Andersen Molecular dynamics simulations at constant pressure and/or temperature , 1980 .

[18]  K. Kremer,et al.  Advanced Computer Simulation Approaches for Soft Matter Sciences III , 2005 .

[19]  Florian Müller-Plathe,et al.  YASP: A molecular simulation package , 1993 .

[20]  David M. Beazley,et al.  Building Flexible Large-Scale Scientific Computing Applications with Scripting Languages , 1997, PPSC.

[21]  M. Parrinello,et al.  Polymorphic transitions in single crystals: A new molecular dynamics method , 1981 .

[22]  Ron O Dror,et al.  The midpoint method for parallelization of particle simulations. , 2006, The Journal of chemical physics.

[23]  Cecilia Clementi,et al.  Communication: On the locality of hydrogen bond networks at hydrophobic interfaces. , 2010, The Journal of chemical physics.

[24]  David Thomas,et al.  The Art in Computer Programming , 2001 .

[25]  Björn Persson,et al.  Faunus: An object oriented framework for molecular simulation , 2008, Source Code for Biology and Medicine.

[26]  Hans Hasse,et al.  Set of molecular models based on quantum mechanical ab initio calculations and thermodynamic data. , 2008, The journal of physical chemistry. B.

[27]  Matej Praprotnik,et al.  FAST TRACK COMMUNICATION: Fractional dimensions of phase space variables: a tool for varying the degrees of freedom of a system in a multiscale treatment , 2007 .

[28]  G. Blin,et al.  Multiple Functionalities of Polyelectrolyte Multilayer Films: New Biomedical Applications , 2010, Advanced materials.

[29]  Matej Praprotnik,et al.  Adaptive resolution scheme for efficient hybrid atomistic-mesoscale molecular dynamics simulations of dense liquids. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  Alexander Lukyanov,et al.  Versatile Object-Oriented Toolkit for Coarse-Graining Applications. , 2009, Journal of chemical theory and computation.

[31]  R W Hockney,et al.  Computer Simulation Using Particles , 1966 .

[32]  Matej Praprotnik,et al.  A macromolecule in a solvent: adaptive resolution molecular dynamics simulation. , 2007, The Journal of chemical physics.

[33]  Hans Petter Langtangen,et al.  A Primer on Scientific Programming with Python , 2009 .

[34]  Kurt Kremer,et al.  Structure Formation of Toluene around C60: Implementation of the Adaptive Resolution Scheme (AdResS) into GROMACS. , 2012, Journal of chemical theory and computation.

[35]  Gaël Varoquaux,et al.  Proceedings of the 20th Python in Science Conference 2021 (SciPy 2021), Virtual Conference, July 12 - July 18, 2021 , 2008, SciPy.

[36]  T. Schneider,et al.  Molecular-dynamics study of a three-dimensional one-component model for distortive phase transitions , 1978 .

[37]  Ilian T. Todorov,et al.  A short description of DL_POLY , 2006 .

[38]  Christoph Junghans,et al.  A reference implementation of the adaptive resolution scheme in ESPResSo , 2010, Comput. Phys. Commun..

[39]  G. Grest,et al.  Dynamics of entangled linear polymer melts: A molecular‐dynamics simulation , 1990 .

[40]  Konrad Hinsen The molecular modeling toolkit: A new approach to molecular simulations , 2000 .

[41]  Kurt Kremer,et al.  Multiscale simulation of soft matter systems. , 2010, Faraday discussions.

[42]  C. M. Bates,et al.  Multiblock Polymers: Panacea or Pandora’s Box? , 2012, Science.

[43]  S. Meloni,et al.  Efficient particle labeling in atomistic simulations. , 2007, The Journal of chemical physics.

[44]  Jadwiga Kuta,et al.  ForceFit: A code to fit classical force fields to quantum mechanical potential energy surfaces , 2010, J. Comput. Chem..

[45]  G. Voth Coarse-Graining of Condensed Phase and Biomolecular Systems , 2008 .

[46]  T Darden,et al.  New tricks for modelers from the crystallography toolkit: the particle mesh Ewald algorithm and its use in nucleic acid simulations. , 1999, Structure.

[47]  Martijn Lenes,et al.  Small Bandgap Polymers for Organic Solar Cells (Polymer Material Development in the Last 5 Years) , 2008 .

[48]  Alexander D. MacKerell,et al.  Automated conformational energy fitting for force-field development , 2008, Journal of molecular modeling.

[49]  Kurt Kremer,et al.  Molecular dynamics simulation study of nonconcatenated ring polymers in a melt. I. Statics. , 2011, The Journal of chemical physics.

[50]  L Delle Site,et al.  Quantum locality and equilibrium properties in low-temperature parahydrogen: a multiscale simulation study. , 2012, The Journal of chemical physics.

[51]  Matej Praprotnik,et al.  Statistical Physics Problems in Adaptive Resolution Computer Simulations of Complex Fluids , 2011 .

[52]  Geoffrey C. Fox,et al.  Examining the Challenges of Scientific Workflows , 2007, Computer.

[53]  Evans,et al.  Equivalence of thermostatted nonlinear responses. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[54]  Y. Mukaigawa,et al.  Large Deviations Estimates for Some Non-local Equations I. Fast Decaying Kernels and Explicit Bounds , 2022 .

[55]  Carsten Kutzner,et al.  GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. , 2008, Journal of chemical theory and computation.

[56]  Dirk Reith,et al.  CG-OPT: A software package for automatic force field design , 2002 .

[57]  Kurt Binder,et al.  Computational Soft Matter: from Synthetic Polymers to Proteins ; NIC Winter School, 29 February - 6 March 2004, Gustav-Stresemann-Institut, Bonn, Germany - Poster Abstracts , 2004 .

[58]  P. Kollman,et al.  Settle: An analytical version of the SHAKE and RATTLE algorithm for rigid water models , 1992 .

[59]  Steve Plimpton,et al.  Fast parallel algorithms for short-range molecular dynamics , 1993 .

[60]  J. Banavar,et al.  Computer Simulation of Liquids , 1988 .

[61]  Xiaoyu Chen,et al.  IBIsCO: A molecular dynamics simulation package for coarse‐grained simulation , 2011, J. Comput. Chem..

[62]  Dirk Reith,et al.  Automated force field optimisation of small molecules using a gradient-based workflow package , 2010 .

[63]  J. Koelman,et al.  Simulating microscopic hydrodynamic phenomena with dissipative particle dynamics , 1992 .

[64]  Hans-Jörg Limbach,et al.  ESPResSo - an extensible simulation package for research on soft matter systems , 2006, Comput. Phys. Commun..

[65]  David E. Shaw,et al.  A fast, scalable method for the parallel evaluation of distance‐limited pairwise particle interactions , 2005, J. Comput. Chem..

[66]  Bjarne Stroustrup,et al.  The C++ Programming Language: Special Edition , 2000 .

[67]  Matej Praprotnik,et al.  Simulation approaches to soft matter: Generic statistical properties vs. chemical details , 2008, Comput. Phys. Commun..

[68]  David E. Shaw,et al.  Zonal methods for the parallel execution of range-limited N-body simulations , 2007, J. Comput. Phys..

[69]  Dirk Reith,et al.  Deriving effective mesoscale potentials from atomistic simulations , 2002, J. Comput. Chem..

[70]  D. Heyes,et al.  MOLECULAR DYNAMICS AT CONSTANT PRESSURE AND TEMPERATURE , 1983 .

[71]  Bjarne Stroustrup A C++ tutorial , 1985, ACM '85.

[72]  P. Strevens Iii , 1985 .

[73]  L Delle Site,et al.  Adaptive resolution molecular dynamics simulation through coupling to an internal particle reservoir. , 2011, Physical review letters.

[74]  David E. Shaw,et al.  Overview of neutral territory methods for the parallel evaluation of pairwise particle interactions , 2005 .

[75]  M. Parrinello,et al.  Canonical sampling through velocity rescaling. , 2007, The Journal of chemical physics.

[76]  Berend Smit,et al.  Understanding Molecular Simulation , 2001 .

[77]  D. C. Rapaport,et al.  Large-scale molecular dynamics simulation using vector and parallel computers , 1988 .

[78]  Kurt Kremer,et al.  Kirkwood-Buff Analysis of Liquid Mixtures in an Open Boundary Simulation. , 2012, Journal of chemical theory and computation.

[79]  Kurt Kremer,et al.  Rheology and Microscopic Topology of Entangled Polymeric Liquids , 2004, Science.

[80]  Dirk Reith,et al.  GROW: A gradient-based optimization workflow for the automated development of molecular models , 2010, Comput. Phys. Commun..

[81]  Christoph J. Brabec,et al.  Influence of Blend Microstructure on Bulk Heterojunction Organic Photovoltaic Performance , 2011 .

[82]  Matej Praprotnik,et al.  Concurrent triple-scale simulation of molecular liquids. , 2008, The Journal of chemical physics.

[83]  O. Lenz,et al.  The optimal P3M algorithm for computing electrostatic energies in periodic systems. , 2007, The Journal of chemical physics.

[84]  Matej Praprotnik,et al.  Adaptive resolution simulation of liquid water , 2007 .

[85]  H. Berendsen,et al.  Molecular dynamics with coupling to an external bath , 1984 .

[86]  A. Dobrynin,et al.  Theory of polyelectrolytes in solutions and at surfaces , 2005 .

[87]  Joshua A. Anderson,et al.  General purpose molecular dynamics simulations fully implemented on graphics processing units , 2008, J. Comput. Phys..

[88]  Matej Praprotnik,et al.  Multiscale simulation of soft matter: from scale bridging to adaptive resolution. , 2008, Annual review of physical chemistry.