Application of Bayesian optimization for high-performance TiOx/SiOy/c-Si passivating contact

We report on the application of Bayesian optimization (BO), which could accelerate the time-intensive process optimization of many parameters, to fabrication of the high-performance titanium oxide/silicon oxide/crystalline silicon passivating contact. The process contains pre-deposition treatment to form SiOy interlayer, atomic layer deposition (ALD) of TiOx, and hydrogen plasma treatment (HPT) as post-process. We attempted to optimize seven parameters for ALD and HPT by dealing with samples treated by three kinds of chemical solutions in the same batch. This permits to perform BO for each structure at the same time and determine the superior predeposition treatment. Consequently, carrier selectivity S10 estimated by independent measurements of the saturation current density and contact resistance was significantly improved by BO of only 12 cycles and 10 initial random experiments. These results certify that BO could efficiently provide experimental conditions in multidimensional parameter space although we need to consider the impact of the metallization process on the passivation performance.

Automated summary

The use of Bayesian optimization in the fabrication of high-performance titanium oxide/silicon oxide/crystalline silicon passivating contact accelerated the process optimization, significantly improving carrier selectivity S10 through simultaneous optimization of multiple parameters with samples treated in the same batch.