ABSTRACT
This chapter demonstrates an application of autonomous investigation using Gaussian process regression. It covers the development of autonomous microscopy experiments to explore the nucleation and growth of DNA crystals via DNA origami nanotechnology. The chapter gives a short background on the problem being investigated, namely, the optimization of crystal growth. The self-assembly of these DNA origami nanoscale building blocks tends to be described by classical nucleation and growth kinetics, typified by a single energy barrier between the transformation between the melt and solid. The assembly of DNA crystals is a large parameter space and exploring how to optimize the assembly process would involve tuning properties such as purity of monomers, salt concentration, the concentration of monomer, and the thermal annealing rate. The thermal pathway function now becomes a facsimile for optimization of the nucleation and growth rate. The authors looked at the problem of parameterization, dimensionality, and interpretation of the experimenter's results in the context of nucleation and growth.
