A new strategy for novel binder discovery in nano and μ powder injection molding: A metaheuristics-assisted virtual combinatorial materials search

Abstract

Binder systems can meet various requirements that include excellent fluidity of injection, good strength of a green body, and rapid thermal debinding. This, however, can be a complex process, and novel binders for practical use in nano powder injection molding (NPIM) as well as in μ powder injection molding (μPIM) can be hidden in a multi-compositional search space that contains an almost infinite number of combinations of well-known waxes, polymers, and surfactants. To establish novel binder materials systematically from a carefully chosen, 7-dimensional search space of (Carnauba wax (CW) - Emulsifying wax (EW) - Paraffin wax (PW)) - (Polyethylene glycol 20,000 (PEG20000) - Ethylene–vinyl acetate (EVA) - Polypropylene (PP)) – (Stearic acid (SA)) a metaheuristics optimization strategy, such as the elitism-involved non-dominated-sorting genetic algorithm (NSGA-II), was coupled with a virtual combinatorial materials search (VCMS) involving the hybrid evaluation of multi-objective functions on the basis of a semi-theoretical and semi-empirical approach. Although the process started with random compositions, it eventually converged into a series of new quaternary compositions including EW, PW, PEG20000, and SA that show strong potential for practical applications to NPIM and μPIM.