A Non-Lattice Model with Conditional Probability for Monte Carlo Simulation of Conformational Statistics of Polyethylene Chain

A new Monte Carlo simulation was suggested for the conformational calculation of tail polymer chains.Real bond length,real bond angle and rotational isomeric state models are adopted to simulate the model chains.During the simulation,the conditional probabilities of rotational isomeric states under Θ condition was used to substitute the ones under refined conditions.The dependability of this substitution was investigated and compared with the exact enunciation method and Flory matrix method.The results showed that the sample stock of chain molecules so simulated can accurately render the real conformational distribution equilibrium state both for confined conditions chains and real chains under the rigidity approximation.The calculated results using this method are in accordance with those from exact enumeration and Flory matrix method.