Atomic layer deposition (ALD) relies on alternated, self-limiting reactions between gaseous reactants and an exposed solid surface to deposit highly conformal coatings with a thickness controlled at the submonolayer level. These advantages have rendered ALD a mainstream technique in microelectronics and have triggered growing interest in ALD for a variety of nanotechnology applications, including energy technologies. Often, the choice for ALD is related to the need for a conformal coating on a 3D nanostructured surface, making the conformality of ALD processes a key factor in actual applications. In this work, we aim to review the current status of knowledge about the conformality of ALD processes. We describe the basic concepts related to the conformality of ALD, including an overview of relevant gas transport regimes, definitions of exposure and sticking probability, and a distinction between different ALD growth types observed in high aspect ratio structures. In addition, aiming for a more standardized and direct comparison of reported results concerning the conformality of ALD processes, we propose a new concept, Equivalent Aspect Ratio (EAR), to describe 3D substrates and introduce standard ways to express thin film conformality. Other than the conventional aspect ratio, the EAR provides a measure for the ease of coatability by referring to a cylindrical hole as the reference structure. The different types of high aspect ratio structures and characterization approaches that have been used for quantifying the conformality of ALD processes are reviewed. The published experimental data on the conformality of thermal, plasma-enhanced, and ozone-based ALD processes are tabulated and discussed. Besides discussing the experimental results of conformality of ALD, we will also give an overview of the reported models for simulating the conformality of ALD. The different classes of models are discussed with special attention for the key assumptions typically used in the different modelling approaches. The influence of certain assumptions on simulated deposition thickness profiles is illustrated and discussed with the aim of shedding light on how deposition thickness profiles can provide insights into factors governing the surface chemistry of ALD processes. We hope that this review can serve as a starting point and reference work for new and expert researchers interested in the conformality of ALD and, at the same time, will trigger new research to further improve our understanding of this famous characteristic of ALD processes.

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Conformality in atomic layer deposition : current status overview of analysis and modelling

The conformality of thin films grown by atomic layer deposition (ALD) is studied using all-silicon test structures with long narrow lateral channels. A diffusion model, developed in this work, is used for studying the propagation of ALD growth in narrow channels. The diffusion model takes into account the gas transportation at low pressures, the dynamic Langmuir adsorption model for the film growth and the effect of channel narrowing due to film growth. The film growth is calculated by solving the diffusion equation with surface reactions. An efficient analytic approximate solution of the diffusion equation is developed for fitting the model to the measured thickness profile. The fitting gives the equilibrium constant of adsorption and the sticking coefficient. This model and Gordon's plug flow model are compared. The simulations predict the experimental measurement results quite well for Al2O3 and TiO2 ALD processes.

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Modeling growth kinetics of thin films made by atomic layer deposition in lateral high-aspect-ratio structures

This work develops a first-principles-based three-dimensional, multiscale computational fluid dynamics (CFD) model, together with reactor geometry optimizations, of SiO2 thin-film thermal atomic layer deposition (ALD) using bis(tertiary-butylamino)silane (BTBAS) and ozone as precursors. Specifically, an accurate macroscopic CFD model of the ALD reactor chamber gas-phase development is integrated with a detailed microscopic kinetic Monte Carlo (kMC) model that was developed in Ding et al. (2019) , accounting for the microscopic lattice structure, atomic interactions and detailed surface chemical reactions. The multiscale information exchange and the transient simulation of the microscopic distributed kMC algorithms and the macroscopic CFD model are achieved through a parallel processing message passing interface (MPI) structure. Additionally, density functional theory (DFT)-based calculations are adopted to compute the key thermodynamic and kinetic parameters for the microscopic thin-film growth process. Recognizing the transient non-uniformity and the possibility to reduce the current ALD cycle time, the optimal configuration of reactor geometry is designed and evaluated including a showerhead panel adjustment and geometry modifications on reactor inlet and upstream. It is demonstrated that with suitable reactor chamber design the required BTBAS ALD half-cycle time can be reduced by 39.6%.

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Multiscale computational fluid dynamics modeling of thermal atomic layer deposition with application to chamber design

Atomic layer deposition in porous electrodes: A pore-scale modeling study

This work develops a comprehensive framework for first-principles-based microscopic modeling, data-driven input/output modeling and optimal operation of thermal atomic layer deposition (ALD) of SiO2 thin-films using bis(tertiary-butylamino)silane (BTBAS) and ozone as precursors. Specifically, we initially utilize Density Functional Theory (DFT)-based calculations for the computation of the key thermodynamic and kinetic parameters, which are then used in the microscopic modeling of the ALD process. Subsequently, a detailed microscopic model is constructed, accounting for the microscopic lattice structure and atomic interactions, as well as multiple microscopic film growth processes including physisorption, abstraction and competing chemical reaction pathways. Kinetic Monte-Carlo (kMC) algorithms are utilized to obtain computationally efficient microscopic model solutions while preserving model fidelity. The obtained kMC simulation results are used to train Artificial Neural Network (ANN)-based data-driven models that capture the relationship between operating process parameters and time to ALD cycle completion. Specifically, a dense two-hidden-layer feed-forward ANN is constructed to find a feasible range of ALD operating conditions accounting for industrial considerations, and a Bayesian Regularized ANN is constructed to implement the cycle-to-cycle optimization of ALD cycle time. Extensive simulation results demonstrate the effectiveness of the proposed approaches. The kMC models successfully achieves a growth per cycle (GPC) of 1.8 A per cycle, which is in the range of reported experimental values. The ANN models accurately predict deposition time to steady-state from the given operating condition input, and the cycle time optimization using BRANN model reduces the conventional BTBAS cycle time by 60%.

Microscopic modeling and optimal operation of thermal atomic layer deposition

The authors present a new method to determine film thicknesses and sticking coefficients (SC) of precursor molecules for atomic layer deposition (ALD) in high aspect ratio three dimensional (3D) geometries as they appear in microelectromechanical system manufacturing. The method combines a specifically designed experimental test structure with the theoretical predictions from a novel 3D Monte Carlo process simulation for large structures. The authors exemplify our method using Al2O3 and SiO2 ALD processes. SCs for trimethylaluminium and bis-diethyl aminosilane (BDEAS) are extracted. The SC for BDEAS is determined for the first time.

Arnim Höchst

Papers

Experimental and simulation approach for process optimization of atomic layer deposited thin films in high aspect ratio 3D structures