条件概率与刚性近似下高分子链非格子模型的Monte Carlo模拟

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

探讨了采用高分子链的实际键长、键角、旋转异构态和无扰链时的条件概率逐个链段地生成样本高分子链进行真实链和受限链分子构象统计研究的可能性.并就无扰链、尾形链、真实链的情况与完全计算法、Flory矩阵方法进行了比较.结果表明:在刚性近似下,使用无扰态时的条件概率生成样本高分子链的Monte Carlo模拟,其样本库能真实地重现平衡态时受限链和真实链的构象分布,适用于受限链和真实链的构象统计研究.

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 0 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.