Real-Time Feedback Control of an Atomic Layer Etching Spatial Reactor

Matthew Tom¹, Henrik Wang¹, Feiyang Ou¹, Gerassimos Orkoulas³, and Panagiotis D. Christofides^1,2

1. Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA
2. Department of Electrical and Computer Engineering, University of California, Los Angeles, CA
3. Department of Chemical Engineering, Widener University, Chester, PA

With the evolution of modern-day electronics, the densification of transistors on semiconducting wafers has been accredited by the downscaling of transistor feature sizes and stacking of transistors, which give rise to high-performance technologies. However, the pursuit of these nanoscale devices has been challenging due to the stringent design criteria in the nanoscale and lack of control over the chemical processes required to assemble the transistors such that transistor surfaces are uniform to enable nanopatterning. To overcome this issue, thin-layer deposition techniques such as atomic layer deposition (ALD) have been implemented to deposit monolayers of film on the surfaces of the substrate in a self-limiting manner. Although this deposition process is effective in templating transistors, the procedure lacks controllability of the adsorption uniformity. Thus, a top-down approach using atomic layer etching (ALE) has been integrated in the semiconductor manufacturing process as a post-processing procedure succeeding ALD. Prior work [1] has established an in silico multiscale computational fluid dynamics (CFD) simulation that simulates an ALE process in a sheet-to-sheet (S2S) spatial reactor configuration as well as ex situ process modeling [2] to establish multivariate control to maintain thin-film conformity. However, this reactor model assumed that constant operating temperatures were maintained throughout the process to minimize the computational cost of simulating simultaneous momentum, heat, and mass differential equations spatiotemporally. Constant temperatures must be maintained due to the pyrolysis of precursor, trimethylaluminum, which decomposes at higher operating temperatures into various species [3] generated by changes in feed temperatures or dimerizes at lower operating temperatures [4] due to the observance of endothermic reactions. Additionally, high operating temperatures are required to ensure complete volatilization of byproducts to obtain an effective surface etch. Therefore, on-line temperature regulation is necessary to minimize the production of byproducts that may interfere with the self-limiting nature of the ALE process and control the fluid dynamics of the substrate exposure to the reagents [5].

This work proposes a CFD model conjoined with an on-line feedback control system to monitor the temperature operating conditions of the reactor, wafer surface, and the feed flow rate temperatures. This work will implement a methodical approach for conducting multivariate temperature adjustment in the presence of temperature disturbances such as ramp, step, and impulse disturbances. A model predictive controller designed on the basis of a data-based model is integrated into the CFD simulation via multiphysics simulation software, Ansys Fluent, through user-defined functions, and the controller performance and robustness properties will be evaluated through extensive closed-loop simulations under practical disturbances.

References:

1. Yun, S., Tom, M., Orkoulas, G., & Christofides, P. D., 2022. “Multiscale computational fluid dynamics modeling of spatial thermal atomic layer etching,” Computers & Chemical Engineering, 163, 107861.
2. Tom, M., Yun, S., Wang, H., Ou, F., Orkoulas, G., & Christofides, P. D., 2022. “Machine learning-based run-to-run control of a spatial thermal atomic layer etching reactor,” Computers & Chemical Engineering, 168, 108044, 2022.
3. Zhang, Z., Pan, Y., Jang, Z., & Fang, H., 2017. “Experimental study of trimethyl aluminum decomposition,” Journal of Crystal Growth, 473, 6-10.
4. Adomaitis, R. A., 2018. “Estimating the thermochemical properties of trimethylaluminum for thin-film processing applications,” Journal of Vacuum Science & Technology A, 36, 050602.
5. He, W., Chu, B., Gu, R., Zhang, H., Shan, B., & Chen, R., 2013. “The application of generalized predictive control in the radiant heating atomic layer deposition reactor,” 2013 IEEE International Symposium on Assembly and Manufacturing (ISAM), Xi'an, 37-40.