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Multi-Physics Simulation-Based Prognosis of Titanium Dioxide Nanoparticles-Embedded Solar Cell
Conference proceeding

Multi-Physics Simulation-Based Prognosis of Titanium Dioxide Nanoparticles-Embedded Solar Cell

Allah Rakhio Junejo, Hyunseung Ryu, Wooseung Noh, Nagarajan Raghavan, Sanghoon Kim, Jaehyeok Doh and IEEE
Proceedings of the ... International Symposium on the Physical & Failure Analysis of Integrated Circuits, Vol.2022-, pp.1-5
18/07/2022

Abstract

Absorption Data-Driven Prognosis Degradation Dye-Sensitized Solar Cell (DSSC) Multi-Physic Simulation NPs Optical device fabrication Optical diffraction Photovoltaic cells Power Energy Conversion (PEC) Stimulated emission Titanium Dioxide Nanoparticle (TiO 2 X-ray diffraction
This study focuses on the multi-physics simulation-based prognosis of titanium dioxide nanoparticles (TiO 2 , NPs) doped in dye-sensitized solar cells (DSSCs), considering optical and electrical properties. The fabrication of TiO 2 , NPs using the Sol-Gel method (400 o C) is the optimal calcination temperature to achieve an anatase phase. Various physical-chemical properties tests for TiO 2, NPs are conducted to understand optical and electrical characterizations utilizing X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) and Ultraviolet-Visible (UV-vis) absorption spectrophotometry. Optical properties such as absorption, bandgap, deflection, and photoluminescence emission are also observed. Based on the best case of high-power energy conversion (PEC) amongst semiconductor material characterizations, multi-physics simulation (optical and electrical properties) for three-dimensional (3D) TiO 2 , NPs is carried out to acquire time-dependent current data, which is relative to degradation for DSSC. A data-driven prognosis of solar cells is then conducted by using degradation data. According to dye molecule layers, the remaining useful life (RUL) is stochastically predicted. The main contribution is to suggest the framework of multi-physics simulation-based prognosis for power energy applications.

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