Hello, A change in allocation has been requested: Requester: zmei (Zhigang Mei) Project: DFT_ALD_SiC Title: Computational Design of Novel Precursors for Atomic Layer Deposition of SiC Description: Our strategy to discover and develop new low-temperature, conformal process for SiC growth will be composed of the following steps: 1. Screening of Potential New Precursors Using Computational Methods To utilize computational methods to screen for potential new precursors, we will examine the available commercial crystal structure databases (e.g. Cambridge Structural Database) for Si- and C-containing materials and perform DFT calculations to determine the enthalpy of formation of SiC with these precursors. A thermodynamic database of chemical reactions between existing and hypothetical Si-containing and C-containing precursors (both organic and inorganic compounds) will be developed and pairs of precursors with the potentially lowest reaction temperatures will be selected for further study. The second step of the screening process is to carry out a fast evaluation of the precursor-surface interaction. We will use a simple slab model to study the precursor-surface interaction. The reaction energetics of the silicon and carbon precursors will be calculated by DFT and the activation energies of reactions will be predicted using Nudged Elastic Band method. At this level of detail, we will focus solely on the interaction of a single precursor molecule with growing surfaces. Under these conditions, we have demonstrated that the precursor surface interaction can be casted as a Markov chain process with the transition probabilities between states determined by the DFT calculations. This allows us to extract the exact probabilistic outcome of the precursor-surface interaction process by carrying out a single matrix inversion. We will incorporate the predicted thermodynamic properties of potential precursors into thermodynamic and kinetic models to evaluate their feasibil ity for the synthesis of SiC. These models, which were originally developed to study the epitaxial growth of SiC by CVD are based on the open source software Cantera, and can be interfaced with existing thermodynamic databases. This investigation can reveal the mechanism of film growth by ALD, identify the critical reactions during the ALD process, and estimate the temperature of deposition. 2. Detailed Simulation of the Precursor-Surface Interaction. It is well known that the complete ALD growth mechanism is extremely complicated, as it consists of surface reactions, structural relaxation and self-limiting surface chemistry. In this integrated approach (DFT+KMC), the ability to retain the accuracy of the atomistic model into the higher-scale model can lead to remarkable breakthroughs in our understanding of ALD process. To describe the ALD reactions of SiC from a combination of silicon-containing and carbon-containing precursors, a 3D on-lattice KMC model will be developed, similar to the model developed for HfO2 [Chem. Mater. 25, 878 (2013)]. All atomistic reaction pathways in DFT will be implemented as reaction events on the lattice. This contains all steps, from the early stage of adsorption of each ALD precursor, kinetics of the surface protons, interaction between the remaining precursors, influence of remaining fragments on adsorption sites, densification of each ALD precursor, migration of each precursor, and coope ration between the remaining precursors. The essential chemistry of the ALD reactions depends on the local environment at the surface. The coordination number and a neighbor list will be used to incorporate these dependencies. The validity and necessity of the proposed reaction pathways will be statistically established at the mesoscale. The formation of one monolayer of precursor fragments will be shown at the end of the pulse. The migration of the low coordinated remaining precursor fragments will be also proposed. This process introduces a slow re-ordering motion at the mesoscale, leading to the smooth and conformal thin film that is characteristic of ALD. The ALD application will be developed as a new feature in the stochastic parallel particle kinetic simulator (SPPARKS) code. In the first year, we will focus on screening of potential new precursors using high-throughput DFT computations. Our initial tests show that the computational time for a typical precursor pair such as SiI4 and CI4, takes about 800 cpu-hours. Due to the huge number of precursors for Si and C, we expect that about 500 pair of precursors will be studied. The total computational time is estimated to be about 400,000 cpu-hours. Current: undetermined amount Justification: Requested: 300000 A specific reason has been given: My allocation for the FY2017 is running out already. This needs to be approved and the final allocation amount decided upon. Thank You, The LCRC Accounts System