NDLI: End-to-end predictive modeling of silicon solar cell performance: From process recipe to device simulation

Content Provider	IEEE Xplore Digital Library
Author	Trzynadlowski, B.C. Wenjun Jiang Renyu Chen Dunham, S.T.
Copyright Year	2011
Description	Author affiliation: Department of Physics, University of Washington, Seattle, WA, USA (Wenjun Jiang) \|\| Department of Electrical Engineering, University of Washington, Seattle, WA, USA (Trzynadlowski, B.C.; Renyu Chen; Dunham, S.T.)
Abstract	We demonstrate the use of end-to-end predictive modeling to optimize silicon solar cell fabrication processes. Coupled continuum models for boron, phosphorus, iron, and oxygen are used to predict the distribution of electronically active defects. The models include point defect-mediated diffusion of boron and phosphorus from solid sources (e.g., POCl) at both the emitter and back surface field. Interactions between iron and boron, boron and oxygen, and phosphorus and vacancies are modeled. From the resulting dopant and defect distributions, carrier lifetimes are computed and, along with the solar cell structure, are passed to a device simulation. We find a competing effect between lifetime-enhancing iron segregation to the boron-rich region and lifetime-degrading BO complex formation. Guided by modeling results, we suggest strategies to restore device performance in the presence of iron contamination and moderate oxygen concentrations, demonstrating the utility of an “end-to-end” modeling framework.
Starting Page	002952
Ending Page	002956
File Size	322570
Page Count	5
File Format	PDF
ISBN	9781424499663
ISSN	01608371
e-ISBN	9781424499656
DOI	10.1109/PVSC.2011.6186565
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Iron Boron Silicon Semiconductor process modeling Performance evaluation Charge carrier lifetime Computational modeling
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Electrical and Electronic Engineering

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