BIPARTITE GRAPHICAL INTEGRATION OF DIELECTROPHORESIS PROCESS MODELS FOR ASSEMBLY OF CARBON NANOTUBES

Dielectrophoresis is the process where nonuniform electric field causes the translational motion of uncharged, polarized particles. Recently dielectrophoresis has become the most widely used process in the field of nanomanufacturing as the translational motion of a carbon nanotube caused by the dielectrophoresis assembles it in the spacing between the electrodes. This process enables engineers to replace the traditional metal (copper or aluminum) wire with carbon nanotubes (CNTs) in the miniature electronic devices. Various process models have been developed and parametric studies have been carried out to understand the process better and to improve the quality and reliability of assembly of CNTs. We consolidate the scattered knowledge of the dielectrophoresis process and represent the integrated knowledge in the form of a complex network by connecting the process parameters based on the relationships they shares. We find that the bipartite relationships exist between some of the process parameters and we represent them in the form of bipartite graphs. We also represent these graphs as incidence matrices and verify whether each graph fulfills the condition of being bipartite. We apply the shortest path algorithm to find an even length path between the any two process parameters which turns out to be an efficient method to estimate the unknown state variables of the process and to access the real time state of the assembly process quickly and efficiently. One can also use bipartite graph to identify the non-contributing variables and eliminate the over constraint situation by applying Gauss elimination method.