Our department has extensive experience in the development and application of numerical models of complex reacting fluid flows. Numerical models describing coupled mass transport, gas-phase and surface chemistry are used to help understand growth processes in a variety of semiconductor systems. The models include heat transfer, energy balances and chemical reaction mechanisms of varying degrees of complexity.
The models are used to analyze and understand the effects of reaction parameters such as gas flow rates, pressure, reagent composition, temperature on growth rates, thin-film composition, growth uniformity, and morphology evolution. A close collaboration between experiment and theory is used to validate and test our modeling predictions.
In a recent project we used a combination of experiments, reactor modeling, and quantum chemical calculations to investigate parasitic chemical reactions that occur during AlGaInN metal-organic chemical vapor deposition (MOCVD). Our results indicate that the parasitic chemical reactions require high temperatures and occur in the boundary layer near the growing surface. These reactions ultimately lead to the formation of nanoparticles, which we observed using in situ laser light scattering. Thermophoresis keeps the nanoparticles from reaching the surface, so the material tied-up in nanoparticles cannot participate in the thin film deposition process. Fluid-flow simulations of the growth reactor were used to predict the spatial location of the thin layer of nanoparticles that form near the heated surface (see the light-scattering image on the left side of the false color image; the yellow line below the red substrate). The layer of particles resides at the position where the downward thermophoretic velocity pushing the particles away from the surface equals the convective velocity of the upward gas flow. Predictions from our modeling are shown as the right side of the figure and they are in excellent agreement with the experimental observation.
Using our results in combination with the existing literature we also developed a 9-step chemical reaction mechanism describing the Ga-precursor decomposition, Al-adduct formation and methane elimination, particle nucleation, and particle growth in the AlGaN system. Growth rates for GaN, AlN, and AlGaN were measured in situ using reflectometry over a wide range of reactor conditions. Reacting flow simulations were used to predict film growth rates and alloy compositions and were in good agreement with our rotating-disk reactor experiments.
In a different project, we conducted a combined experimental and modeling study of the dependence of solution-based ZnO selective-area growth rates on pattern dimension (in collaboration with Julia Hsu, Surface & Interface Sciences department); see illustration below. Selective growth is achieved by patterning a portion of the substrate with an organic template that inhibits growth. The density of ZnO nanorods and the mass grown per unit area of exposed surface was found to increase as the distance between the exposed growth regions is increased and as the area of the exposed zones is decreased. A 2-D model was developed to model the selective growth process at the exposed surface regions, the loss of reactant material due to a competing reaction in solution, liquid-phase and surface diffusive mass transport to (or on) the growth surface, and the ZnO growth reaction at the surface. To explain the experimental results, we found it necessary to include a reaction by-product in the chemistry model, the desorption of which is the rate limiting step. A relatively simple, three-step reaction mechanism, combined with the species mass transport model, provides a good, semi-quantitative description of the experimental observations in the selective-area growth of ZnO from supersaturated solutions.