Abstract:
In this paper we presented Monte Carlo simulations of polymer diffusion in
a disordered media. A Monte Carlo (MC) simulation method in two dimensions with a bond fluctuation model (BFM) has been used to achieve this goal .
In polymer diffusion, we present a new effective algorithm to simulate dynamic
properties of polymeric systems confined to lattice. The algorithm displays Rouse
behavior for all spatial dimensions. The systems are simulated by bond fluctuation method to study both the static and dynamic properties of the polymer
chains. For static properties we calculated the average mean-square end-to-end
distance hR2(N)iand the mean-square radius of gyration hRg 2(N)i. In the absence
of obstacles (free media) both the end-to-end distance and the radius of gyration
are proportional to some power of the number of monomers (N), hR2(N)i ∝ N 3/2
and hRg 2(N)i ∝ N 3/2. However in the presence of obstacles, the scaling exponent
changes with the concentration of the obstacles. The end-to-end distance of the
polymer increases, as concentration(c) increases. As the concentration of the
obstacles increases, the bead obstacles close to the monomers, this causes the
polymers to stretch. In the presence of obstacles the mean radius of gyration
increases, and the universal power law the scaling deviates from the universal
power law relations. For disordered systems diffusion is anomalous, and the
mean-square displacement is proportional to a fractional power of time not equal
to one. For dynamical properties we look at the mean-square displacement of
the total chain. For short times the mean-square displacement of the monomers
g1(t) and the mean-square displacement of the monomers relative to the chains
center of mass g2(t) show the same behavior and for long times the mean-square
displacement of the center of mass g3(t) takes over
