RESUMO
We describe a complete methodology to bridge the scales between nanoscale molecular dynamics and (micrometer) mesoscale Monte Carlo simulations in lipid membranes and vesicles undergoing phase separation, in which curving molecular species are furthermore embedded. To go from the molecular to the mesoscale, we notably appeal to physical renormalization arguments enabling us to rigorously infer the mesoscale interaction parameters from its molecular counterpart. We also explain how to deal with the physical timescales at stake at the mesoscale. Simulating the as-obtained mesoscale system enables us to equilibrate the long wavelengths of the vesicles of interest, up to the vesicle size. Conversely, we then backmap from the meso- to the nano-scale, which enables us to equilibrate in turn the short wavelengths down to the molecular length-scales. By applying our approach to the specific situation of patterning a vesicle membrane, we show that macroscopic membranes can thus be equilibrated at all length-scales in achievable computational time offering an original strategy to address the fundamental challenge of timescale in simulations of large bio-membrane systems.
RESUMO
Using phase-ordering kinetics and of renormalization group theories, we derive analytically the relaxation times of the long wavelength fluctuations of a phase-separated domain boundary in the vicinity of (and below) the critical temperature in the planar Ising universality class. For a conserved order parameter, the relaxation time grows like Λ^{3} at wavelength Λ and can be expressed in terms of parameters relevant at the microscopic scale: lattice spacing, bulk diffusion coefficient of the minority phase, and temperature. These results are supported by numerical simulations of 2D Ising models, enabling in addition calculating the nonuniversal numerical prefactor. We discuss the applications of these findings to the determination of the real timescale associated with elementary Monte Carlo moves from the measurement of long wavelength relaxation times on experimental systems or molecular dynamics simulations.