In this work, the added value of machine learning (ML) molecular force fields (FF) for the community of molecular simulations is showcased by successfully calculating transport properties of aqueous potassium hydroxide (KOH (aq)). Classical FFs use relatively simple interatomic potentials to simulate the nano scale. These simulations can predict macroscopic properties, such as density, heat of evaporation, viscosity, and self-diffusivity of the modeled materials. However, these FFs struggle to model materials in which more complicated interactions are relevant for the macroscopic behavior. Examples of such interactions are three-body interactions and chemical reactions. Quantum scale simulation methods are able to compute properties of materials in which these challenging interactions occur, although these methods are limited in length and time scales that can be modeled with realistic computational costs. Transport properties, such as viscosity, self-diffusivity and electric conductivity need these larger length and time scales to be determined accurately. ML can be used for a multi scale approach, bridging the gap between the quantum and the nano scale by training coefficients of general interatomic potentials. This provides the possibility of reaching the time and length scales of traditional molecular simulations with the accuracy of quantum mechanic models. KOH (aq) is selected to highlight the prospects of these multi scale techniques, as the self-diffusion of OH- in this electrolyte is dominated by proton transfer reactions, which has not been modeled successfully with classical FFs.

Results of structure properties produced with ab initio molecular dynamics (AIMD, at quantum scale) simulations are compared with machine learning molecular dynamics (MLMD, at multi scale) simulations. There are no significant differences in the calculated shortest typical atomic distances and coordination numbers for both KOH (aq) and pure water systems. The determined transport properties are in the same order of magnitude as experimental results, although the calculated viscosity is overestimated and the self-diffusion of H2O and K+ are underestimated. This is because the system is simulated at a higher than experimental density and hydrogen bonding is overestimated with the selected quantum mechanics model. The proton transfer reactions are captured in the MLMD simulations, calculating the enhanced self-diffusion of OH- to be (6±2)e-9 m squared per second, which matches experimental results at infinite dilution.

Climate change is one of the top global issues that the United Nations has identified that can adversely impact people all around the globe. Moving towards a hydrogen economy can reduce greenhouse emissions produced from burning fossil fuels which is one of the biggest contributors to global warming and climate change. Hydrogen fuel has a high gravimetric density and being a clean fuel it has the potential to become a sustainable energy source for the growing market. However, its low volumetric density makes it a difficult fuel to store, thus making storage technologies in the hydrogen supply chain an important part. The current storage technologies, however, are impeded by shortcomings such as low hydrogen densities, extreme pressure and temperature operating conditions and inefficiencies during the storage process. Combining existing hydrogen storage technologies such as compressed hydrogen gas and metal hydrides with 2D materials comes across as an excellent option as they can complement each other in their functioning. In this regard, borophene is considered a viable material for hydrogen storage due to its lightweight, good thermal, mechanical and electrical properties. Most of the studies performed so far on hydrogen storage in borophene were on hydrogen physisorption via weak van der Waals forces. In this thesis work, the chemisorption of hydrogen on borophene via strong covalent bonds is studied. This is because borophene with chemisorbed hydrogen is more energetically stable than with physisorbed hydrogen. Also, chemisorbed hydrogen on borophene performs better than physisorbed hydrogen in terms of safety and long-term storage. Hydrogen chemisorption on pristine, defective (i.e. with single and double vacancies) and metal decorated borophene are studied in this work, using density functional theory (DFT) and nudged elastic band (NEB) calculations to compute quantities such as enthalpy and activation energy barriers of chemisorption. Using Bader charge analysis and partial density of states analysis, it was observed that the addition of charge on the hydrogen bond weakens the bond, expediting the chemisorption reaction. The charge transfer from borophene to the chemisorbed H atoms was found to stabilize the final chemisorbed state. In the case of metal decorations, there is an additional steric factor that influences the activation barrier height for chemisorption. In general, metal decorations performed better than pristine and defective borophene systems in terms of the desorption barrier height, among which double decorated K atoms on borophene substrate had the best performance, improving the barrier height by 20% compared to the corresponding value for the pristine system.