The application of machine learning techniques in silicon photovoltaics research and
production has been gaining traction. Learning from the existing data has given the potential …

The heterojunction (HJ) solar cell is one of the best possible options to upgrade the
conventional single homo-junction c-Si solar cell. In this work, a single HJ solar cell based …

Solar cell simulation software offers an intuitive platform enabling researchers to efficiently
model, simulate, analyze, and optimize photovoltaic devices and accelerate desired …

Increasing silicon solar cell efficiency plays a vital role in improving the dominant market
share of photo-voltaic systems in the renewable energy sector. The performance of the solar …

The effects of single-layer antireflection coatings (SLARCs) on the performance of crystalline
silicon (c-Si)-based solar cells have been analyzed numerically. In this study, amorphous (a …

Minimizing the photon losses by depositing an anti-reflection layer can increase the
conversion efficiency of the solar cells. In this paper, the impact of anti-reflection coating …

This paper uses numerical modeling to describe the design and comprehensive analysis of
cost-effective MXene/n-InP Schottky barrier solar cells. The proposed design utilizes …

This work integrates PC1D simulation, Box–Behnken design (BBD), and machine learning
models (artificial neural network—ANN and particle swarm optimization-artificial neural …

The challenges on Si solar cells are the usage of hazardous phosphorus oxychloride
(POCl3) for emitter formation and silane, and ammonia for the anti-reflective layer. This study …

In this work, calcium fluoride (CaF 2) has been employed as an anti-reflection coating (ARC)
for gallium arsenide (GaAs) based heterojunction solar cell. A numerical analysis was …