these techniques are limited by the requirement for complex enzymatic reactions. As an alternative strategy that bypasses the need for genetic engineering, combinatorial methods can be employed. These can be used to explore tens to hundreds of reaction conditions, where the most promising or "lead" conditions may be selected based on the structures or properties of the resultant material. [ 17,18 ] Lead conditions can then be used to narrow the reaction landscape in successive screening rounds. Surprisingly, although combinatorial methods are often used in solid-state chemistry to explore, for example, different reagent compositions, [ 18 ] we are not aware of their use in identifying soluble additives capable of directing mineralization.In this article we demonstrate how combinatorial methods can be used in conjunction with effi cient screening processes to rapidly identify combinations of small organic molecules that are capable of directing the formation of photoluminescent quantum dot minerals in aqueous solution and at room temperature. Indeed, a key feature of biomineralization processes is that control over mineral formation is achieved using many soluble additives that operate in concert. That this feature has seldom been addressed in bioinspired methods is almost certainly due to the vast number of potential variables, which renders a full, systematic exploration intractable. As a solution to this challenge, we here utilize a genetic algorithm as a bioinspired heuristic that mimics natural evolution. Genetic algorithms use selection, recombination, and mutation strategies to rapidly identify and optimize the combination of conditions (here, soluble additives), which gives rise to materials with target properties. [ 19 ] Using a pipetting robot to prepare reaction sets and a UV-light table to rapidly assess the reactions for the formation of photoluminescent minerals, we are able to rapidly identify the key additives that promote the formation of quantum dot superstructures from one-pot aqueous reactions.Our initial library of organic mediators included 23 components, of which 17 were amino acids and 6 were surfactants. Stock solutions of the amino acids were prepared to initial concentrations of 100 × 10 −3 M , and explored at concentrations ranging from 0.01 to 50 × 10 −3 M , while surfactants were prepared to near their solubility limits in water. Surfactants were included as potential structure-directing agents to drive hierarchical assembly in aqueous solution. The overall screening approach used to identify the key additive set is summarized in Figure 1 . First, library amino acids and surfactants were randomly mixed in 48 wells of a multi-well plate, such that each well contained between 1-6 amino acids and 1-3 surfactants (Figure 1 A). Cadmium chloride and thioacetic acid (as a sulfur source) [ 20 ] were then added to a concentration of 1 × 10 −3 M in all wells, as precursors for CdS. After 3 d the plate was viewed under UV illumination (Figure 1 A) and with a fl uorimetric Biomineralization, whi...