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Theoretical Framework of Novel Oxide Compounds for Visible Range Light-Emitting Devices
Abstract
Composite oxides have been proved to be valuable materials in optoelectronic applications. The combination of indium oxide and gallium oxide and other oxides can lead to enhanced optical and electronic properties, making them suitable for a variety of optoelectronic devices. A favorable energy band gap is needed in the visible region of the spectrum, indicating the applicability in optoelectronic devices such as LEDs and solar cells. Overall band gap engineering and tuning the radiative recombination is a challenge for new age semiconductors. Artificial Intelligence and Machine Learning have become powerful tools in the theoretical study and discovery of oxide materials for LEDs. By analyzing vast datasets, models can predict material properties, optimize synthesis parameters, and even generate new compounds with desired characteristics. This data-driven approach accelerates the material discovery process and enhances the precision of theoretical predictions, allowing researchers to explore a broader chemical space and identify optimal candidates for visible range light emission.
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