title: Atomistic Modelling of Structure Formation and Phase Transitions in Si-Ox Compounds using Machine-Learning Interatomic Potentials
Creators: name: Erhard, Linus Carl
Publisher: name: UNSPECIFIED
Year: 2024

description: Silica is used in a wide range of applications from catalysis to construction to microelectronics. The related silicon monoxide is promising for applications as an anode material in lithium batteries. Although these materials have been extensively studied for more than a century, there are still many open questions. For example, the high-pressure transformations of silica are not fully understood. Moreover, in the case of silicon monoxide, there is not even an atomistic structure model that captures the complexity of the structure.
In this work, we use atomistic modelling to investigate these problems. For this purpose, we developed several machine learning interatomic potentials (MLIP). First, we developed a Gaussian approximation potential (GAP) model based on a database with focus on bulk silica. Later, we switched to the atomic cluster expansion (ACE) framework. The final ACE potential is fitted to a more comprehensive training database labeled with energies and forces from strongly constrained and appropriately normed
(SCAN) exchange-correlation density functional theory (DFT) data. The database covers a wide range of structures, including amorphous and crystalline silica, silica surfaces, high-pressure silica, and silicon-silica interfaces. Several approaches were used to build the database including ‘batch’ learning and active learning. Moreover, we present an active learning technique that extracts DFT feasible small-scale images from large-scale simulations (Chapter 3). The MLIPs are extensively tested in reproducing the thermodynamics of the systems and show excellent behavior, outperforming existing classical models. Nevertheless, to generate realistic amorphous structures of silica, we rely on a ‘hybrid’ protocol using a combination of our MLIP and a classical interatomic potential (Chapter 4). 
We apply the ACE potential to two cases. First, we study the high-pressure be-
havior of amorphous silica and quartz under shock (Chapter 5). We find that there is an intermediate structure between the amorphous state and the crystalline stable state of stishovite. This phase is based on the defective nickel arsenide (d-NiAs)
structure. The structure has a disordered silicon sublattice and an ordered hexagonal close-packed (HCP) oxygen sublattice. While the oxygen lattice appears to form fast on the molecular dynamics (MD) time scales, the ordering of the silicon and hence the formation of stishovite takes significantly longer. Moreover, we found that a direct transition between quartz and rosiaite-structured silica is also possible, which seems to require certain strain boundary conditions. 
Second, we generate structural models of silicon monoxide using melt-quench simulations (Chapter 6). These models show the same nanoscale segregation of silicon and silica as observed in experiment. Moreover, the energetics, grain sizes and X-ray structure factors of these models are in excellent agreement with the experiment. Using 20 ns annealing simulations, we are able to partially crystallize these structures and generate structural models with crystalline silicon in an amorphous silica matrix.