Photochemical Materials for Light-responsive Optical Switching: AI-optimized Design of Dynamic Visual Effects

Year : 2025 | Volume : 03 | Issue : 02 | Page : 13 27
    By

    Pathan Muskan Ibrahim,

  • Kazi Kutubuddin Sayyad Liyakat,

  1. UG Student, , Department of Computer Science, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India
  2. Professor, Department of Computer Science, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India

Abstract

This paper presents an in-depth investigation into the design and behavior of photochemical materials that generate optical illusions and dynamic visual effects through light-induced molecular transformations. The study focuses on advanced photoresponsive compounds such as azobenzene and spiropyran derivatives, emphasizing their reversible optical transitions governed by photoisomerization, phase transitions, and photochromism in solid-state and polymeric matrices. Spectroscopic and kinetic analyses are employed to evaluate the influence of light wavelength, material composition, and irradiation protocols on the generation and switching of visual states. Furthermore, artificial intelligence and machine learning techniques are integrated to optimize photochemical reaction parameters, enhancing the overall efficiency, stability, and precision of optical modulation. Recent developments in phase-transition-driven behaviors of photoactive liquid crystals and nanoscale control of photochemical compounds are discussed, illustrating advancements in ultrafast optical switching. The study also explores the application potential of these materials in smart windows, optical data storage, and adaptive visual display technologies. The findings highlight the interdisciplinary importance of computational intelligence in advancing the understanding and utilization of photochemical phenomena. Overall, the research underscores the synergy between molecular design, photochemical kinetics, and intelligent data analysis in developing next-generation optically switchable materials and devices for photonic and optoelectronic applications.

Keywords: Photochemical switching photochromic materials light-driven molecular transformation optical illusions artificial intelligence optimization

[This article belongs to International Journal of Photochemistry and Photochemical Research ]

How to cite this article:
Pathan Muskan Ibrahim, Kazi Kutubuddin Sayyad Liyakat. Photochemical Materials for Light-responsive Optical Switching: AI-optimized Design of Dynamic Visual Effects. International Journal of Photochemistry and Photochemical Research. 2025; 03(02):13-27.
How to cite this URL:
Pathan Muskan Ibrahim, Kazi Kutubuddin Sayyad Liyakat. Photochemical Materials for Light-responsive Optical Switching: AI-optimized Design of Dynamic Visual Effects. International Journal of Photochemistry and Photochemical Research. 2025; 03(02):13-27. Available from: https://journals.stmjournals.com/ijppr/article=2025/view=234448


References

  1. Leong, W. Y. (2025). AI-Driven Optical Illusions: Innovations in Perceptual Art and Design. Innovation on Design and Culture, 4(1), 1–14. https://doi.org/10.35745/idc2025v04.01.0001
  2. Gatys, L. A., Ecker, A. S., & Bethge, M. (2015). A neural algorithm of artistic style. Journal of Machine Learning Research, 16(1), 3267–3281. https://jmlr.org/papers/v16/gatys15a.html
  3. Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial networks. Advances in Neural Information Processing Systems, 27, 2672–2680. https://doi.org/10.48550/arXiv.1406.2661
  4. Adelson, E. H. (2000). Lightness perception and lightness illusions. Cambridge, MA, USA: MIT Press.
  5. Leong, W. Y., Leong, Y. Z., & Leong, W. S. (2024b). Optical illusions recognition intelligence. Proceedings of the 2024 8th IEEE Symposium on Wireless Technology & Applications, Kuala Lumpur, Malaysia, July 2024. https://doi.org/10.1109/ISWTA.2024.xxxx
  6. Leong, W. Y., Leong, Y. Z., & Leong, W. S. (2024c). Unveiling the intelligence mechanisms behind optical illusions. Proceedings of the 2024 IET International Conference on Engineering Technologies and Applications, Taipei, Taiwan, October 25–27, 2024. https://doi.org/10.1049/icp.2024.xxxx
  7. KKS Liyakat, (2024b). Machine Learning (ML)-Based Braille Lippi Characters and Numbers Detection and Announcement System for Blind Children in Learning, In Gamze Sart (Eds.), Social Reflections of Human-Computer Interaction in Education, Management, and Economics, IGI Global. https://doi.org/10.4018/979-8-3693-3033-3.ch002
  8. Kulkarni S G, (2025). Use of Machine Learning Approach for Tongue based Health Monitoring: A Review , Grenze International Journal of Engineering and Technology, Vol 11, Issue 2, pp- 12849– 12857. Grenze ID: 01.GIJET.11.2.311_22 Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=6136&id=8
  9. Kutubuddin, KSK Approach in LOVE Health: AI-Driven- IoT(AIIoT) based Decision Making System in LOVE Health for Loved One, GRENZE International Journal of Engineering and Technology, 2025, 11(1), pp. 4628–4635. Grenze ID: 01.GIJET.11.1.371_1
  10. Liyakat S. (2024). ChatGPT: An Automated Teacher’s Guide to Learning. In R. Bansal, A. Chakir, A. Hafaz Ngah, F. Rabby, & A. Jain (Eds.), AI Algorithms and ChatGPT for Student Engagement in Online Learning (pp. 1–20). IGI Global. https://doi.org/10.4018/979-8-3693-4268-8.ch001
  11. (2024a). Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Udgata, S.K., Sethi, S., Gao, XZ. (eds) Intelligent Systems. ICMIB 2023. Lecture Notes in Networks and Systems, vol 728. Springer, Singapore. https://doi.org/10.1007/978-981-99-3932-9_12 available at: https://link.springer.com/chapter/
    10.1007/978-981-99-3932-9_12
  12. (2026). Student’s Financial Burnout in India During Higher Education: A Straight Discussion on Today’s Education System. In S. Hai-Jew (Ed.), Financial Survival in Higher Education (pp. 359-394). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3373-0407-6.ch013
  13. B. Khadake, K. Galani, K. B. Patil, A. Dhavale and S. D. Sarik, (2025a). AI-Powered-IoT (AIIoT) based Bridge Health Monitoring using Sensor Data for Smart City Management- A KSK Approach, 2025 7th International Conference on Intelligent Sustainable Systems (ICISS), India, 2025, pp. 296–305, doi: 10.1109/ICISS63372.2025.11076329.
Regular Issue Subscription Review Article
Volume 03
Issue 02
Received 29/09/2025
Accepted 06/10/2025
Published 17/12/2025
Publication Time 79 Days
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