PModels :: Predictive models for polymer systems

• PModels can predict properties of polymer blends and composites.
• Input: properties of the components + composition + additional parameters.
• Output: property of the final system (i.e. of the polymer blend or composite).

Principle

>>> # Standard import of PModels package
>>> import pmodels as pm
>>>
>>> # Estimate arbitrary property P of a polymer blend
>>> # (P1,P2) = properties of components, v2 = vol.fraction of component 2
>>> P = pm.lin.P(P1=1, P2=3, v2=0.5)
>>>
>>> # Estimate elastic modulus, E, and yield stress, Y, of a polymer blend
>>> # (E1,E2 and Y1,Y2) = props of the components, v2 = vol.fract., A = adhesion 
>>> E = pm.ebm.E(E1=1, E2=3, v2=0.5)
>>> Y = pm.ebm.Y(Y1=20, Y2=100, v2=0.5, A=1)

Installation

• Requirement: Python with sci-modules = numpy, matplotlib, scipy, pandas
• pip install pmodels = PModels package itself (uses all packages above)

Quick start

• Worked example = basic calculations with PModels.
• DropBox folder with more examples, including test data.

Documentation, help and examples

• PyPI repository - the stable version to install.
• GitHub repository - the current version under development.
• GitHub Pages with examples and complete package documentation.

Versions of PModels

• Version 0.1 = key calculations
• Version 0.2 = basic docstrings added
• Version 0.3 = improved init file = simple API
• Version 0.4 = standard docstrings, improved code, deployed in GitHub