The original intent was to have a larger focus on 3D characterization (researcher's main expertise) of existing photonic material samples in the host research group to cumulate a large database of different structures and their optical response to draw structure-property relationships. However it was soon realized, via extensive literature reviews, that there was vast amount of computational models developed (independently in separate scientific disciplines) to simulate various disordered structures that had been mostly unemployed in the field of disordered optics.
In other words, such in-silico approaches offered access to much broader range of interesting structures than what was trivially accessible via traditional chemical synthesis. More importantly the former was much more efficient as in-silico synthesis takes from few up to twenty minutes resulting direct 3D data. In comparison chemical synthesis is often tedious, and structural characterization required to obtain necessary 3D information wa likewise very time consuming.
The major draw back in the in-silico approach was that information on optical properties were relatively slow to obtain, where as scattering experiments deliver results from real world samples in usually matter of few minutes per sample. E.g.~a single optical simulations took up to four hours per sample on desktop pc. The situation was quickly addressed by the researcher by conducting the simulations on the Cambridge high performance cluster (HPC) which permitted the use of hundreds of CPU cores reducing the computation time to 30 minutes per sample, thus removing the computational bottle next.
The established workflow allowed us to investigate copious amounts different disordered systems. We decided to focus on 10 different structural morphologies, that represent a wide range of different disordered systems, in hundreds of different configurations (length scale, anisotropy, void content). During the course of the project we conducted over 4000 finite difference time domain (FDTD) optical simulations thanks to combination of in-silico synthesis and HPC resources.
In addition, the extensive literature survey allowed us to identify important tools, such as Minkowski functions, that can be used quantify structural differences in the simulated structures using comprehensive descriptors such as surface area, mean and Gaussian curvatures, and anisotropy value, which was essential for establishing structure-property relationships.
