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Abstract
Since the isolation of graphene back in 2004, twodimensional (2D) materials have been at the cutting edge of materials research in both physics and chemistry. Their fascinating electronic structure, unique mechanical properties and unmatched versatility has made them them over the years an ideal platform for exploring a number of applications in electronics, optics, quantum technologies, catalysis and many more. In this thesis, we investigate the electronic and catalytic properties of a wide range of 2D materials by means of Density Functional Theory (DFT) calculations. We show how computational approaches can be employed in order to drive the discovery of novel 2D materials, make predictions on the catalytic activity, assess the stability in acqueous environment and reproduce fine hybridization effects.
One of the most interesting classes of 2D materials is represented by van der Waals heterostructures. By stacking different 2D monolayers one can obtain a virtually infinite number of new hybrid structures with unique properties. The latter are influenced not only by the nature of the individual layers, but also by their relative rotation angle, which can be freely modulated thanks to the dispersive nature of the layerlayer interactions. Herein, we first introduce a lattice matching procedure necessary for generating input structures of van der Waals heterobilayers for abinitio calculations. Then, we implement a selfconsistent scissors operator able to reproduce the quasiparticle electronic structure of large heterostructures at the cost of a PBE calculation. The method is benchmarked against experimental data, showing that twist angledependent interlayer hybridization effects can be effectively reproduced for a MoSe_{2}WS_{2} heterobilayer.
A less explored family of 2D materials is obtained by selfintercalation, i.e. incorporation of native metallic atoms in the van der Waals gap of the pristine layered structure. By adopting an automated workflow, we automatically generate a large number of selfintercalated bilayers (ic2D) and evaluate their thermodynamic stability, identifying dozens of stable structures that have yet to be explored experimentally. We find that selfintercalation significantly enhances the metallic behaviour, completely eliminating the band gap in most materials that are semiconducting in their pristine form. Additionally, it can introduce a magnetic ground state in otherwise nonmagnetic systems. After calculating the hydrogen adsorption energies, we find that the catalytic activity of the ic2D can be tuned by varying the degree of intercalation. 7 of the newfound materials are predicted to be promising hydrogen evolution reaction catalysts.
The applicability of any material in electrocatalysis is often limited by its tendency to degrade in present of a solvent and electrolytes under applied potentials. Here, we address the problem by presenting a new Pourbaix diagram utility, coded in Python language and openly accessible through the software package ASE. This diagram construction method can directly utilize preexisting experimental or theoretical bulk phase data, without the necessity of performing any DFT calculations. The utility will soon be implemented in the Computational 2D Materials Database (C2DB).
Alternatively, the acqueuos stability problem can be tackled from a microscopic point of view by shifting the focus on the material surface, rather than relying on bulk phase properties. In this thesis, we introduce the concept of Extended Surface Pourbaix Diagram (ESPD). The ESPD expands the capabilities of existing surface Pourbaix diagram methods which aim to predict the status of a material surface in electrochemical environment in terms of coverage by water dissociation products. By including surface vacancies in the list of explored configurations, we are able to explicitly model the material dissolution into ions, completing the list of possible degradation processes. Furthermore, we improve the description of the chemical potential of ions by accounting for the surface excess. The resulting diagrams, calculated herein for a selected set of materials, provide useful mechanistic information on degradation processes and a remarkable agreement with experimental observations.
One of the most interesting classes of 2D materials is represented by van der Waals heterostructures. By stacking different 2D monolayers one can obtain a virtually infinite number of new hybrid structures with unique properties. The latter are influenced not only by the nature of the individual layers, but also by their relative rotation angle, which can be freely modulated thanks to the dispersive nature of the layerlayer interactions. Herein, we first introduce a lattice matching procedure necessary for generating input structures of van der Waals heterobilayers for abinitio calculations. Then, we implement a selfconsistent scissors operator able to reproduce the quasiparticle electronic structure of large heterostructures at the cost of a PBE calculation. The method is benchmarked against experimental data, showing that twist angledependent interlayer hybridization effects can be effectively reproduced for a MoSe_{2}WS_{2} heterobilayer.
A less explored family of 2D materials is obtained by selfintercalation, i.e. incorporation of native metallic atoms in the van der Waals gap of the pristine layered structure. By adopting an automated workflow, we automatically generate a large number of selfintercalated bilayers (ic2D) and evaluate their thermodynamic stability, identifying dozens of stable structures that have yet to be explored experimentally. We find that selfintercalation significantly enhances the metallic behaviour, completely eliminating the band gap in most materials that are semiconducting in their pristine form. Additionally, it can introduce a magnetic ground state in otherwise nonmagnetic systems. After calculating the hydrogen adsorption energies, we find that the catalytic activity of the ic2D can be tuned by varying the degree of intercalation. 7 of the newfound materials are predicted to be promising hydrogen evolution reaction catalysts.
The applicability of any material in electrocatalysis is often limited by its tendency to degrade in present of a solvent and electrolytes under applied potentials. Here, we address the problem by presenting a new Pourbaix diagram utility, coded in Python language and openly accessible through the software package ASE. This diagram construction method can directly utilize preexisting experimental or theoretical bulk phase data, without the necessity of performing any DFT calculations. The utility will soon be implemented in the Computational 2D Materials Database (C2DB).
Alternatively, the acqueuos stability problem can be tackled from a microscopic point of view by shifting the focus on the material surface, rather than relying on bulk phase properties. In this thesis, we introduce the concept of Extended Surface Pourbaix Diagram (ESPD). The ESPD expands the capabilities of existing surface Pourbaix diagram methods which aim to predict the status of a material surface in electrochemical environment in terms of coverage by water dissociation products. By including surface vacancies in the list of explored configurations, we are able to explicitly model the material dissolution into ions, completing the list of possible degradation processes. Furthermore, we improve the description of the chemical potential of ions by accounting for the surface excess. The resulting diagrams, calculated herein for a selected set of materials, provide useful mechanistic information on degradation processes and a remarkable agreement with experimental observations.
Original language  English 

Publisher  Department of Physics, Technical University of Denmark 

Number of pages  145 
Publication status  Published  2023 
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 1 Finished

Electronic and catalytic properties of twodimensional materials and van der Waals heterostructures
Americo, S., Thygesen, K. S., Olsen, T., Batzill, M. M. & Foster, A. S.
01/08/2020 → 11/01/2024
Project: PhD