Ensemble Monte Carlo Growth simulations of polymers in confined environments

We apply a recent Ensemble Monte Carlo Growth algorithm to sample the microcanonical density of states of polymers in confined geometries. The main advantage of computing the entropy directly, is that it allows to locate and characterize phase transitions accurately, while circumventing problems associated with long time scales. However, when the accessible phase space is restrained, such as in geometrically confined polymers, entropic forces exerted on the confining walls lead to changes in several statistical mechanical properties of the polymers. We test the performance of the microcanonical ensemble Monte Carlo growth algorithm for confined interacting self avoiding walks. We discuss also how to extend the model to include electrostatic interactions.