The worldwide consumption of energy is increasing in a rapid rate. We need to find new alternatives for our energy mix that are abundant, secure and environmentally friendly. The current prospective solutions involve the integration of intermittent renewable energy sources (e.g. solar and wind) into the grid, the widespread deployment/adoption of electric vehicles (EV) and the development of sustainable systems to power portable electronics. Such a transition to a long-term sustainable energy system relies heavily on the development of suitable advanced energy materials. The primary objective of the current research program is to develop novel methods for computer-aided design of energy-relevant materials employing first-principles theory. More specifically, our research focuses on the following three main branches: (i) energy storage materials (organic electrodes and Li metal anode in battery devices), (ii) computational photo-electro-catalysis (2D-materials and polymeric compounds) and (iii) operando spectroscopy. One key methodology to be developed, common for all projects, is the high-throughput computational materials design machinery (HCMD), which will incorporate machine learning methods and will facilitate the selection of potential candidates from a large materials-library. The successful realization of this data-driven materials design project will significantly contribute in the transition to a long-term sustainable energy system. Such theoretical framework will combine density functional theory, implicit solvation models, molecular dynamics and Monte Carlo simulations, spectroscopy and thermodynamics assessment to investigate systems spanning solvated molecules, interfaces and bulk materials.