Influence Of Surface Preparation And Cleaning On The Passivation Of Boron Diffused Silicon Surfaces For High Efficiency Photovoltaics

Keywords

Aluminum oxide; Silicon; Silicon nitride; Surface passivation; Surface preparation; Wafer cleaning

Abstract

The use of proper surface preparation and cleaning methods for Si wafers prior to the deposition of passivation layers is essential to minimize surface recombination and realize high efficiencies (> 20%) in crystalline Si photovoltaic cells. In this work, the influence of wafer cleaning on the quality of surface passivation achievable for boron-doped emitters was investigated, including the use of different combinations of HCl, HF, HNO3, and ozonated deionized water (DIO3). These different surface preparations and cleaning sequences were performed on undiffused and boron diffused n-type Cz Si wafers, followed by the deposition of either silicon nitride (SiNx) or an aluminum oxide film capped with SiNx (Al2O3/SiNx stack). Additionally, both planar and anisotropically textured wafers were used. Injection-level dependent photoconductance measurements and calibrated photoluminescence imaging were performed on symmetrical boron diffused samples based on the different cleaning processes and passivation materials described above. Additionally, non-contact corona-Kelvin measurements were used to extract the total charge and interface defect density at the Si surfaces. We found that cleaning variations strongly influence carrier lifetime for SiNx passivated Si, but the effect is less pronounced in the case of Al2O3/SiNx stacks. It was further observed that DIO3-last treatment resulted in higher lifetimes for the SiNx stacks. Overall, it emerged that the (DIO3 + HF + HCl → HF → DIO3) clean is a promising and potentially low cost cleaning sequence for the photovoltaics industry.

Publication Date

8-31-2017

Publication Title

Thin Solid Films

Volume

636

Number of Pages

412-418

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.tsf.2017.06.043

Socpus ID

85021318056 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85021318056

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