Controlled formation of nanostructures with desired geometries : robust dynamic paths to robust desired structures

[摘要] (cont.) Given these locations, the Static Problem is solved through the solution of combinatorially-constrained optimization problems. The Dynamic Problem is solved through a genetic algorithm search for the appropriate time-varying system degrees of freedom. Crucial to the achievement of the design goals is the necessity to break the ergodicity of the system phase space and control the subset of system states accessible to the system. More specifically, the static approach requires isolating the desired structure from all competing structures in phase space. The dynamic approach involves a multiresolution view of the system particle number, where we successively restrict the accessible volume of phase space based on coarse-grained particle number (i.e., density) specifications. We illustrate the design problems and solution methods through 1- and 2-dimensional lattice models and simulate the self-assembly process with a dynamic Monte Carlo method.

[发布机构] Massachusetts Institute of Technology