Combinatorial Evolution of Biomimetic Magnetite Nanoparticles

Inspired by Nature's capacity to synthesize well-defined inorganic nanostructures, such as the magnetite particles produced by magnetotactic bacteria, genetic algorithms are employed to combinatorially optimize the aqueous synthesis of magnetite (Fe3O4) nanoparticles through the action of copolypeptide additives. An automated dispensing system is used to prepare and rapidly screen hundreds of mineralization reactions with randomized conditions, varying ferrous iron, base, oxidant, and polypeptide chemistry. Optimization over multiple generations allows identification of conditions under which the copolypeptides promote magnetite formation where this does not occur in their absence. It is found that nanoparticle size, size distribution, and shape can be tuned by the concentrations and compositions of the copolypeptides, and that the reaction pH is the most important factor in controlling the crystalline phase. This approach should be broadly applicable to the syntheses of solid-state materials and represents a valuable strategy for extending biomimetic mineralization to the production of technological materials