Improving Industrial Solar Cell Fabrication using Neural Networks and Genetic Algorithms

The present thesis approaches the improvement of the performance metrics of industrially fabricated solar cells. It aims to develop an optimization method that uses machine learning to identify an improved configuration of solar cell production lines. Conventional methods for process improvement rely on modelling experimental data to improve a...

Data - driven design of a metamaterial unit cell using sparse Gaussian processes

Metamaterials are a new class of materials where the properties crucially depend on the design of the unit cell that is periodically repeated in space. In this study a new metamaterial unit cell concept has been proposed, inspired by a class of space structures known as deployable masts. The ability of these structures to contract to a fraction...