Efficient molecular simulations for environmentally benign processes

Abstract

An efficient sampling technique namely the Hammersley sequence sampling (HSS) technique based on quasi-random numbers is applied to molecular simulations to increase computational efficiency and reduce the error in property calculations for efficient and environmentally friendly product and process design. Due to its k-dimensional uniformity properties, this sampling technique reduces the computational intensity and converges faster as compared to conventional Monte Carlo (MC) method based on pseudo-random numbers. Two case studies are presented in order to show the effect of the sampling technique on molecular simulations. The first case study involves the computation of equation of state (EOS) for a Lennard Jones fluid and the second case study concerns the prediction of Gibbs free energies of transfer for the calculation of octanol–water partition coefficients. The results show that the HSS technique provides about 3-fold gain in efficiency and reduces the number of cycles required to reach equilibration. Furthermore, the errors in property calculations are reduced for both of the case studies.