## 2 Computational Details  
### The Simulation Approach  
[PERSON] et al. describes the complicated nature of the ALD growth. Because of the physicochemical mechanisms that regulate ALD growth, a simulation that can depict the time evolution of interacting atoms during the ALD process is critical. An empirical interatomic potential is a well-suited approach to describing ALD process and relaxation processes in MD simulations [8]. The study proposes two ALD, half-reactions equations. The equations are as follows [8]:  
\[\text{AlOH}+\text{Al}(\text{CH3})_{3}\rightarrow\text{Al}-\text{O}-\text{Al}( \text{CH3})_{2}+\text{CH}_{4} \tag{1}\]  
\[\text{Al}-\text{O}-\text{Al}(\text{CH3})_{2}+2\text{H}_{2}\text{O}\rightarrow \text{Al}-\text{O}-\text{Al}(\text{OH})_{2}+2\text{CH}_{4} \tag{2}\]  
The interatomic potentials for the hydroxylated alumina surface were determined by [PERSON] [22]. They are of the Buckingham type. The pair's interaction potential between atoms \(i\) and \(j\) as a function of the inter-atomic distance \(r_{ij}\) is given by Equation (3) as:  
\[U_{ij}=\frac{q_{i}q_{j}}{r_{ij}}+D\big{(}B_{i}+B_{j}\big{)}\exp\left(\frac{A_{ i}+A_{j}-r_{ij}}{B_{i}+B_{j}}\right)-\frac{C_{i}C_{j}}{r_{ij}^{6}} \tag{3}\]  
The repulsion and dispersion interactions are included in this potential, which comprises a long-ranged electrostatic potential and a short-ranged Buckingham potential. D (4.184 kJ\({}^{-1}\)mol\({}^{-1}\)) is the force constant, \(r_{ij}\) is the relative distance between atoms \(i\) and \(j\), and q is the effective charge on each atom in the equation above. A, B, and C, the empirically fitted parameters, are provided in Table 1.  
The molecular dynamics simulation was built in the LAMMPS-code (Large-scale Atomic/Molecular Massively Parallel Simulator) offered by SANDIA [23]. The visualization and post-processing of results were performed in OVITO (open visualization tool) [24]. In LAMMPS, the cut-off radius is specified by the potential. Short-range interactions are only taken into account in some MD implementations. All MD simulations were performed in the canonical ensemble with a time step of 0.1 fs (NVT). The number of particles (N), the volume of the simulation box (V), and the temperature (T) were all kept constant [20]. The short-range Buckingham interactions were determined using a cut-off of 1 A. The long-range Coulombic interaction cut-off was set at 50 A, accommodating the changing periodic boundary. In all MD simulations, the Nose-Hoover chain technique [25] was employed to integrate the equations of motion. A two-dimensional correction was made to the Ewald summation below \(1\times 10^{-7}\) for Coulombic forces. The number of computations is lowered by including neighbor lists, which track which atoms are predicted to interact on the next timestep. This strategy saves time by avoiding the need to calculate all-atom pair distances in the simulation at each timestep. Binning is considered to divide the simulation domain into smaller portions, as another alternative. After then, atoms need to look for interactions in their bin and neighboring bins within the cut-off radius [26]. At 1 A above the surface, the atoms' mobility was stopped. As a result, any molecules attempting to escape the simulation box by breaking loose from the surface were repelled. Zero velocities were subjected to a setforce, fix-command of LAMMPS. The fix-command froze certain atoms in the simulation by reducing their force to zero throughout a specified range.