Genetic algorithm-guided discovery of additive combinations that direct quantum dot assembly

An evolutionary algorithm for the discovery of porous organic cages

The chemical and structural space of possible molecular materials is enormous, as they can, in principle, be built from any combination of organic building blocks. Here we have developed an evolutionary algorithm (EA) that can assist in the efficient exploration of chemical space for molecular materials, helping to guide synthesis to materials with promising applications. We demonstrate the utility of our EA to porous organic cages, predicting both promising targets and identifying the chemical features that emerge as important for a cage to be shape persistent or to adopt a particular cavity size. We identify that shape persistent cages require a low percentage of rotatable bonds in their precursors (<20%) and that the higher topicity building block in particular should use double bonds for rigidity. We can use the EA to explore what size ranges for precursors are required for achieving a given pore size in a cage and show that 16 Å pores, which are absent in the literature, should be synthetically achievable. Our EA implementation is adaptable and easily extendable, not only to target specific properties of porous organic cages, such as optimal encapsulants or molecular separation materials, but also to any easily calculable property of other molecular materials.

Amino Acid Assisted Incorporation of Dye Molecules within Calcite Crystals

Biomineralisation processes invariably occur in the presence of multiple organic additives, which act in combination to give exceptional control over structures and properties. However, few synthetic studies have investigated the cooperative effects of soluble additives. This work addresses this challenge and focuses on the combined effects of amino acids and coloured dye molecules. The experiments demonstrate that strongly coloured calcite crystals only form in the presence of Brilliant Blue R (BBR) and four of the seventeen soluble amino acids, as compared with almost colourless crystals using the dye alone. The active amino acids are identified as those which themselves effectively occlude in calcite, suggesting a mechanism where they can act as chaperones for individual molecules or even aggregates of dyes molecules. These results provide new insight into crystal–additive interactions and suggest a novel strategy for generating materials with target properties.

Enzymatically-controlled biomimetic synthesis of titania/protein hybrid thin films

Although it is widely recognised that enzymes play a significant role in sculpting complex silica skeletons in marine sponges, the potential for exploiting enzymes in materials synthesis has not yet been fully harnessed. In this work we show that the digestive enzyme papain can self-assemble into monolayers on oxide surfaces, where they then drive the formation of crystalline titanium dioxide nanoparticles. This dual functionality of thin film formation and mineralization promotion has the potential to enable the construction of hierarchical inorganic/organic structures in the form of continuous amorphous titania/protein films which can be refined to 93% anatase post annealing. Additional control over the film thickness is afforded by layer-by-layer processing using a simple dip-coating approach. Papain's TiO₂-mineralizing activity displays complex kinetics that deviates from the native Michaelis-Menten kinetic activity, yet deactivation studies demonstrate that this activity relies upon residues that are essential for catalytic site function. These parameters provide unique insight into enzymatic biomineralization, allowing a flexible route to achieving bioengineered titania heterostructures, and potentially providing a green-chemistry solution to photovoltaic cell development.

Exploring experimental fitness landscapes for chemical synthesis and property optimization

The topology of experimental fitness landscapes for chemical optimization objectives is assessed through svr-based HDMR modeling.

Combinatorial microfluidic droplet engineering for biomimetic material synthesis

Although droplet-based systems are used in a wide range of technologies, opportunities for systematically customizing their interface chemistries remain relatively unexplored. This article describes a new microfluidic strategy for rapidly tailoring emulsion droplet compositions and properties. The approach uses a simple platform for screening arrays of droplet-based microfluidic devices and couples this with combinatorial selection of the droplet compositions. Through the application of genetic algorithms over multiple screening rounds, droplets with target properties can be rapidly generated. The potential of this method is demonstrated by creating droplets with enhanced stability, where this is achieved by selecting carrier fluid chemistries that promote titanium dioxide formation at the droplet interfaces. The interface is a mixture of amorphous and crystalline phases, and the resulting composite droplets are biocompatible, supporting in vitro protein expression in their interiors. This general strategy will find widespread application in advancing emulsion properties for use in chemistry, biology, materials, and medicine.