Predictive Modeling and CIGS Integration for Multi-Junction Solar Cell Efficiency Enhancement

Ziani Zakarya; Mahdad Moustafa Yassine; Baghdadli Tewfik; Sekkal Mohammed Chakib; Bessenouci Mohammed Zakaria; Ghellai Nassera

doi:10.20944/preprints202309.1265.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 19 September 2023 / Approved: 19 September 2023 / Online: 19 September 2023 (07:48:35 CEST)

Multi-junction solar cells comprised of stacked III-V semiconductor junctions represent the highest-efficiency photovoltaic technology, with recent demonstrations exceeding 47% efficiency . Optimizing the design and thickness of each junction is critical for maximizing performance . This work utilizes Silvaco TCAD tools to systematically optimize a 5-junction cell based on AlInP, AlGaInP, AlGaInAs, GaInP, GaAs, InGaAs, and Ge similar to recent record cells . The junction thicknesses are varied using a predictive profiler to sample the parameter space . For each combination, the spectral absorption and I-V characteristics are simulated to determine the efficiency . Statistical analysis identifies the optimal thickness set that maximizes performance to 26% under 1 sun illumination .

Multijunction solar cells; IIIV semiconductors; TCAD simulation; cell optimization; predictive profiling; CIGS absorbers; spectral utilization; currentvoltage characteristics; external quantum efficiency; GaAs replacement; bottom junction; thin films; high efficiency; photovoltaics; epitaxial growth; stacked junctions; light absorption

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Predictive Modeling and CIGS Integration for Multi-Junction Solar Cell Efficiency Enhancement

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