Area Selective Deposition Workshop 2024
Date & Time - April 14th-17th, 2024
Location - Montreal, Canada
Schrödinger is excited to be participating in Area Selective Deposition Workshop 2024 taking place on April 14th – 17th in Montreal, Canada. Join us for a presentation by Simon Elliott, Director of Atomic Level Process Simulation at Schrödinger, titled “Microkinetic modelling to asses sensitivity of area-selective deposition to aspects of substrate chemistry.”
Speaker:
Simon Elliott, Director
Date/Time:
April 16th | 1:10pm EDT
Abstract:
Microkinetic modelling is a technique for determining the turnover of a gas-surface process by solving the coupled kinetic rate equations of its constituent elementary reaction steps. Here we present a microkinetic model of the atomic layer deposition (ALD) of alumina from trimethylaluminium (TMA) and water and discuss its utility in investigating the selectivity of the process towards various substrates. We first outline the computational scheme, where elementary steps and their activation energies have been computed with density functional theory. We emphasize the importance of converting the DFT energies to free energies at the temperatures and pressures of interest. The resulting microkinetic model for alumina-on-alumina growth yields measurable quantities (relative growth per cycle and sticking coefficients) as a function of temperature and pressure, which are validated against experiment. For instance, the values of sticking coefficient from the model, s0(TMA)=7 x 10-3 and s0(H2O)= 3 x 10-4 at 1 Torr and 300°C, compare well with experiment. We then systematically adjust the activation energies to represent the different chemistry that may exist during nucleation on a substrate, without explicitly modelling any one substrate at the atomic scale. Specifically, we examine the sensitivity of each sticking coefficient towards adsorption energy and towards acidity of substrate protons, as both of these mechanistic features are candidates for tuning the area-selectivity of oxide ALD towards a substrate. The influence of temperature and pressure is quantified, with the latter giving information on conformality. The results thus increase our understanding of how various aspects of substrate chemistry affect area-selective deposition. This example illustrates more generally how existing mechanistic data from atomic-scale DFT can be leveraged in computationally-inexpensive higher-scale models to allow ‘what-if’ experiments to be carried out that link directly to measurements.