Vol. 5 No. 1 (2025): Issue 5
Articles

Deep Ultraviolet Light-emitting Diodes using Logistic Regression

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  • Sara Mendes,
  • Anouk Jansen,
  • Rui Costa,
  • Ana Oliveira
Sara Mendes
Centre for Photonics and Smart Materials, University of Aveiro, Aveiro, 3810-193, Portugal
Rui Costa
Instituto de Investigação em Materiais Avançados, Leiria Polytechnic Institute, Leiria, 2411-901, Portugal
Ana Oliveira
LED Technology Research Unit, University of Trás-os-Montes and Alto Douro, Vila Real, 5000-801, Portugal

Published 2025-01-09

Keywords

  • DUV,
  • Light-Emitting Diodes,
  • Logistic Regression,
  • Performance Optimization,
  • Fabrication Challenges

How to Cite

Mendes, S., Jansen, A., Costa, R., & Oliveira, A. (2025). Deep Ultraviolet Light-emitting Diodes using Logistic Regression. Communications on Electrical and Electronics Engineering, 5(1). Retrieved from https://ojs.mri-pub.com/index.php/CEEE/article/view/138

Abstract

As the demand for high-efficiency deep ultraviolet (DUV) light-emitting diodes (LEDs) continues to rise in various applications such as water purification and sterilization, there is a pressing need for developing cost-effective and reliable sources of DUV light. However, the current state of DUV LED research presents challenges with achieving both high performance and stability due to material limitations and fabrication complexities. In this paper, we propose a novel approach using logistic regression analysis to optimize the design and fabrication process of DUV LEDs. Our innovative method provides a systematic framework for enhancing the efficiency and stability of DUV LEDs, paving the way for practical applications in next-generation lighting and sensing technologies.

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