Package: pyPRISM
pyPRISMPolymer Reference Interaction Site Model (PRISM) theory describes the
equilibrium spatial-correlations of liquid-like polymer systems including
melts, blends, solutions, block copolymers, ionomers, liquid crystal forming
polymers and nanocomposites. Using PRISM theory, one can calculate
thermodynamic (e.g., second virial coefficients, Flory-Huggins interaction
parameters, potentials of mean force) and structural (eg., pair correlation
functions, structure factors) information for these macromolecular materials.
pyPRISM is a Python-based, open-source framework for conducting PRISM theory
calculations. This framework aims to simplify PRISM-based studies by providing
a user-friendly scripting interface for setting up and numerically solving the
PRISM equations. pyPRISM also provides data structures, functions, and classes
that streamline PRISM calculations, allowing pyPRISM to be extended for use in
other tasks such as the coarse-graining of atomistic simulation force-fields or
the modeling of experimental scattering data. The goal of this framework is to
reduce the barrier to correctly and appropriately using PRISM theory and to
provide a platform for rapid calculations of the structure and thermodynamics
of polymeric fluids and nanocomposites.CitationIf you use pyPRISM in your work, we ask that you please cite both of the following articlesMartin, T.B.; Gartner, T.E III; Jones, R.L.; Snyder, C.R.; Jayaraman, A.;
pyPRISM: A Computational Tool for Liquid State Theory Calculations of
Macromolecular Materials, Macromolecules, 2018, 51 (8), p2906-2922linkSchweizer, K.S.; Curro, J.G.; Integral Equation Theory of the Structure of
Polymer Melts, Physical Review Letters, 1987, 58 (3) p246-249linkExampleBelow is an example python script where we use pyPRISM to calculate the pair
correlation functions for a nanocomposite (polymer + particle) system with
attractive polymer-particle interactions. Below the script is a plot of the
pair correlation functions from this calculation. Seeherefor a more detailed discussion of this example.importpyPRISMsys=pyPRISM.System(['particle','polymer'],kT=1.0)sys.domain=pyPRISM.Domain(dr=0.01,length=4096)sys.density['polymer']=0.75sys.density['particle']=6e-6sys.diameter['polymer']=1.0sys.diameter['particle']=5.0sys.omega['polymer','polymer']=pyPRISM.omega.FreelyJointedChain(length=100,l=4.0/3.0)sys.omega['polymer','particle']=pyPRISM.omega.InterMolecular()sys.omega['particle','particle']=pyPRISM.omega.SingleSite()sys.potential['polymer','polymer']=pyPRISM.potential.HardSphere()sys.potential['polymer','particle']=pyPRISM.potential.Exponential(alpha=0.5,epsilon=1.0)sys.potential['particle','particle']=pyPRISM.potential.HardSphere()sys.closure['polymer','polymer']=pyPRISM.closure.PercusYevick()sys.closure['polymer','particle']=pyPRISM.closure.PercusYevick()sys.closure['particle','particle']=pyPRISM.closure.HyperNettedChain()PRISM=sys.solve()pcf=pyPRISM.calculate.prism.pair_correlation(PRISM)Quick InstallThe commands below should install pyPRISM with all basic dependences via conda
or pip. These commands should be platform agnostic and work for Linux, macOS, and
Windowsifyou have Anaconda or pip installed.  For full installation
instructions please see the documentation.$condainstall-cconda-forgepyPRISMor$pipinstallpyPRISMDocumentationCode documentation is hosted onpyprism.readthedocs.io. The most up to
date code documentation can always be found bycompilingfrom source.Contact UsPlease use theIssuetracker to submit questions or suggestions for the project. For other correspondence, please contact one of the team-members below.Dr. Tyler Martin, NIST,GitHub,Webpage,ScholarDr. Thomas Gartner, Princeton University,GitHub,ScholarDr. Ronald Jones, NIST,Webpage,ScholarDr. Chad Snyder, NIST,Webpage,ScholarProf. Arthi Jayaraman, University of Delaware,Webpage,ScholarLegalNIST DisclaimerAny identification of commercial or open-source software in this document is
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