Opto-vibrational coupling in molecular solar thermal storage materials: Electronic structure calculations and neural-networkbased analysis Giannis Kostaras Degree project

Abstract

Molecular solar thermal storage materials are proposed as a clean, renewable energy solution for a world with ever increasing energy needs. Norbornadiene is an organic compound suitable for molecular solar thermal storage systems. Computational methods such as density functional theory offer solutions for improvement of norbornadiene-based molecular solar thermal storage systems via theoretical spectroscopy. Machine learning methods, such as artificial neural networks may offer useful insights to improve theoretical spectroscopy methods.