Director(s): Jean-Noël Aqua, Geoffroy Prévot
Funding:
Description :
Start: 2026
End: 2029
PhD Sudent :
Team(s): Chemical Physics and Dynamics of Surfaces  
Teams' Page of thesis : Chemical Physics and Dynamics of Surfaces  
Thesis status: Proposed thesis

Since the discovery of graphene, interest in 2D materials has continued to grow. Graphene itself has remarkable properties, such as a band structure with Dirac cones and high charge carrier mobility. 2D materials based on Group IV elements, such as silicene (Si) and germanene (Ge), as well as transition metal dichalcogenides (TMDCs), are promising alternatives due to their optical and transport properties. These can be obtained by epitaxial growth on a substrate. However, numerous experiments carried out on lamellar or metallic substrates [1] have revealed new growth modes that fall outside the scope of conventional crystal growth theories (see Figure 1). They remain to be understood and mastered [2, 3, 4] in order to overcome the technological barrier associated with the small size of the domains obtained by these methods.

The objective of this thesis is to develop theoretical modelling of 2D material growth in order to explain these new experimental results and determine the optimal parameters for growth. To achieve this, an approach combining modelling and experiments will be implemented, based on kinetic Monte Carlo (KMC) simulations, adapted to describe complex systems at mesoscopic and macroscopic spatial and temporal scales while integrating events at atomic time scales. These simulations will be based on existing experimental data for different systems and on additional experiments that can be carried out in the host laboratory. They will be integrated into a more general description of out-of-equilibrium phenomena using dynamic mean-field models.

The PhD student will study systems such as germanene on Ag(111) or MoSe₂ on lamellar substrates [2, 5]. These systems have revealed new growth modes, in particular surface alloy formation and interlayer Ostwald ripening. The PhD student will use a KMC simulation code developed by the host team, based on a lattice model that describes the various atomic events. These processes will be described as dependent on different configurations (local height, types of neighbours, etc.) in order to account for various effects (local order, wetting, etc.). The PhD student will describe alloy effects and surface structures through fine discretisation of the crystal structure and kinetic processes as functions of local composition.

The simulations, based on the KMC algorithm without rejection, will depend on energy parameters that will be deduced using a methodology that systematically compares the simulations with the morphologies and statistical properties of the microscopy images. Specific experiments may be conducted in the host laboratory to refine the modelling. The doctoral student may also use artificial intelligence methods to systematise the deduction of energy barriers by combining theory and experiment. KMC simulations will make it possible to isolate the kinetic processes that govern growth modes and to effectively estimate their energy barriers. The objective of this thesis is to improve understanding of non-equilibrium processes in complex systems and to control growth in order to produce large, highquality 2D films by epitaxy.

Techniques/methods in use: kinetic Monte-Carlo simulations, epitaxy

Applicant skills: Familiarity with scientific programming (C++, etc.), analytical skills