[24p-12M-1~21] 16.3 Bulk, thin-film and other silicon-based solar cells

2:15 PM - 2:30 PM JST(5:15 AM - 5:30 AM UTC)Presentation by Applicant for JSAP Young Scientists Presentation Award

[24p-12M-6] Optimization of a-Si:H/O/c-Si interface using on-the-fly machine learning potential molecular dynamics simulations

〇Semba Takayuki¹, Ryoji Asahi¹, Ryosuke Jinnnouchi¹, Jacob Mckibbin² (1.Nagoya Univ., 2.North Carolina Univ.)

Keywords:

Machine Learning Force Field,Molecular Dynamics,Amorphous Silicon

Passivation contact using a-Si:H is an important technology for improving solar cell efficiency. A detailed understanding of the a-Si:H/c-Si interface at the atomic level is necessary to further improve solar cell performance. In this study, MD calculations using machine learning potentials (MLP) were performed on a-Si:H/O/c-Si interface models with different interfacial oxygen concentrations and hydrogen distributions to investigate the correlation with defect concentration and optimize the conditions.