Boron-based two-dimensional materials showcase promise in variety of fields like hydrogen storage, fabrication of electronic devices and catalytic applications. These materials have garnered interest owing to their unique properties such as high electron mobility, high gravimetric capacity for hydrogen especially after metal decoration, thermal conductivity and tensile strength amongst others. However, for sustained operations of the devices involving these materials, their chemical stability against oxygen is of paramount importance. Especially in the applications involving exposure of the material to air. Abundance of oxygen in the air and its high reactivity increases the likelihood of oxidation of the material. In this work, chemical stability of hydrogen passivated 2D Boron structures; Borophane and 2D Boron Hydride against oxygen were analysed. First-principles calculations reveal that Borophane and 2D Boron Hydride have a less negative binding energy thus indicating that the oxygen binds less strongly to compared to Borophene which does not possess surface passivation by hydrogen. Experimental studies in the literature involving synthesis of 2D Boron Hydride reported presence of vacancies. The effect of vacancy site towards the reaction with oxygen was therefore analysed to maintain consistency with the synthesized materials. The simulations were performed on Borophane and 2D Boron Hydride by introducing a Boron vacancy in the system. The DFT simulation of defect containing Borophane revealed that oxygen binds less strongly in the physisorbed state and more strongly in the chemisorbed state, relative to the values obtained for Borophane without any defects. In case of 2D Boron Hydride it was observed that the vacancies provide a stable site for oxygen, for both physisorbed and chemisorbed state. From these simulations we can conclude that presence of vacancies in Boron based 2D materials generally leads to a stable site for oxygen.

The current industrial application of carbon capture utilization and storage (CCUS) is limited due to technological drawbacks such as high energy demand and environmental pollution. Ionic liquids (ILs) and deep eutectic solvents (DESs) are considered promising alternative solvents for the capture of carbon dioxide (CO2). DESs are often characterized by high viscosities, which hinders industrial application. This problem might be solved by mixing the DES with an organic solvent. This study aims to assess the DESs choline chloride-ethylene glycol (ethaline) and choline chloride-urea (reline) mixed with methanol and propylene carbonate (PC) for their suitability as a medium for the combined capture and electrochemical conversion of CO2. Molecular dynamics (MD) simulations are performed to obtain the densities, the viscosities, the self-diffusivities, the ionic conductivities and insight into the molecular interactions of these mixtures. Independent MD simulations are performed of these mixtures with low concentrations of the solutes CO2, oxalic acid and formic acid. Complementary studies within the Bio-cel project are conducted to characterize the solubility and electrochemical reaction of CO2 and the techno-economics. The viscosities of the mixtures monotonically decrease for an increase of mole fraction of organic solvent, which is benign for the application of CCUS. The self-diffusivities of all constituents increase monotonically for an increase of mole fraction of organic solvent. The ionic conductivity is calculated based on the ion self-diffusivities. Ionic conductivity optima are found at a mole fraction of DES of approximately 0.6 for ethaline-PC and approximately 0.2 for ethaline-methanol and reline-methanol. For higher mole fractions of organic solvent, the ionic conductivity decreases due to a depletion of ions. Radial distribution functions (RDFs) are used to analyse the intermolecular interactions. RDF peaks between chloride-choline and chloride-ethylene glycol show an increase for an increasing mole fraction of organic solvent, which was unexpected. The numbers of hydrogen bonds decrease for addition of methanol to pure deep eutectic solvent. For addition of propylene carbonate, this decrease is less pronounced. The depletion of hydrogen bonds at low mole fractions of deep eutectic solvent is in correspondence with the decrease in viscosity and increase in self-diffusivities. The results indicate that, for the studied properties, deep eutectic solvents mixed with organic solvents are more favourable than pure deep eutectic solvents for the absorption and electrochemical conversion of CO2.

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.

As a result of the Paris Agreement, energy technologies require to shift from fossil fuel based to carbon neutral. In 2015, the maritime sector was responsible for 2.6 % of the global CO2 emissions. The combination of the solid oxide fuel cell fueled by sustainable synthesized ammonia is seen as a potential solution to reduce emissions. Ammonia is considered as a balanced solution in terms of ease of storage, volumetric energy density and cost of production. The solid oxide fuel cell is generally regarded to be a promising technology owing to its high eciency and combined heat and power usage. This MSc thesis investigates the technical viability of a sustainable SOFC propulsion system fueled by ammonia. Technical viability is expressed in equipment weight and volume, whereas sustainability is determined by efficiency and emissions. The solid oxide propulsion system is subjected to a case study: A diesel engine powered vessel from the Watertaxi Rotterdam company with an assumed shaft power of 25 kW. A model was compiled to determine the efficiency, weight and volume of the solid oxide fuel cell system. The model covers activation losses, ohmic losses and diffusion losses within the solid oxide fuel cell stack. With the model, a sensitivity study with a selected set of system parameters was performed to gain insight in the solid oxide fuel cell system. The selected system parameters are: Number of cells in the stack, single-pass fuel utilization, cathode off-gas recirculation rate and anode off-gas recirculation rate. The final solid oxide fuel cell system has a signicantly higher efficiency based on the higher heating value than the diesel engine system: 46.0 % versus 35.0 % respectively. Also, no carbon dioxide is emitted, leading to a reduction of 56.9 ton per year. Furthermore, nitrogen oxide emissions are considered to be negligible compared to the diesel engine system. However, the weight and volume of the solid oxide fuel cell system are signicantly larger: 1199 kg versus 278 kg and 1175 L versus 432 L respectively. Mainly caused by the battery module, required for compensating for temporarily imbalances between power demand and power supply. As a result, it is concluded that the solid oxide fuel cell system is unpractical for the small inland vessel selected for the case study. Larger sized vessels have more potential for the application, because large sized vessel sail more continuously, reducing the battery capacity requirement, may allow for more tolerance regarding heavy and bulky equipment and have more benefit of the higher efficiency due to a lower refuel frequency.

In this thesis, molecular simulations of porous materials are performed, ranging from testing theories using simple models to predicting thermodynamic properties of realistic complex systems. Porous materials such as zeolites, MOFs, and cyclodextrins (CDs) are studied for waste water treatment and energy related applications. The purpose of the presented studies is twofold: (1) identify the best performing materials for a specific application from a large pool of structures, (2) obtain molecular insight into the molecular level phenomena involved in a specific application. These studies aim to provide guidance for experimentalist in finding new, better performing materials, and a more detailed understanding of the involved phenomena...@en

Knowledge on transport properties of fluids is of great interest for process and product design development in the chemical, food, pharmaceutical, and biotechnological industry. In the past few decades, molecular simulation has become a powerful tool to calculate these properties. In this context, Molecular Dynamics (MD) is important for the calculation of transport properties of complex systems, where currently available models are not valid, or at extreme conditions at which performing an experiment is dangerous or not feasible. MD simulations provide detailed information about the dynamics of the system at the molecular level. In this thesis, the aim is to investigate the computation of transport properties using force field-based MD simulations. @en