Impact of Well Number on High-Efficiency Strain-Balanced Quantum-Well Solar Cells

IEEE JOURNAL OF PHOTOVOLTAICS(2023)

引用 2|浏览5
暂无评分
摘要
The addition of lower energy-gap InGaAs quantum wells to the depletion region of GaAs solar cells is an established approach to enhance photovoltaic performance by extending infrared collection. However, maintaining a high open-circuit voltage (V-oc) when including quantum wells has proven more challenging. In this article, we report on high-efficiency (eta > 23.5% AM0) strain-balanced quantum well (SBQW) solar cells with increased current output and efficiency while maintaining the same high open-circuit voltage of baseline devices without quantum wells (V-oc > 1.02 V). The single-junction GaAs-based device structures discussed herein employ a radiation-tolerant, n-i-p front-junction architecture and include both an InGaP heterojunction (HJ) emitter and in most cases an underlying AlGaAs distributed Bragg reflector. The impact of well number on photovoltaic device characteristics is described using an analytical model that assumes current collection, radiative recombination, and nonradiative recombination all increase with well number and are additive to the baseline cell. The highest V-oc and efficiency SBQW devices employ shallow 9.2 nm In0.07Ga0.93As quantum wells and 11.5 nm GaAs0.90P0.10 barrier layers to maintain strain balancing. Increasing the indium composition in the wells from 7% to 10% to form deeper wells requires a thicker strain-balancing barrier layer and results in an apparent increase in radiative recombination and decreased V-oc. Single-junction high-efficiency SBQW device performance is also demonstrated in thinner base-layer structures with graded HJs-device structures suitable for inclusion in radiation-tolerant multi-junction structures.
更多
查看译文
关键词
Radiative recombination,Photovoltaic cells,Gallium arsenide,Voltage,Photovoltaic systems,Performance evaluation,Junctions,Bragg gratings,III-V and concentrator PV,quantum well devices,radiation effects,strain control
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要