AI-Enhanced GWO-FDTD Co-Design of Multi-Band Plasmonic Nanorings for Multiplexed Biosensing

Journal of Optoelectronical Nanostructures

مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 03 مرداد 1404

نوع مقاله: Articles

شناسه دیجیتال (DOI): 10.30495/jopn.2025.33680.1327

نویسندگان

Mohsen Nasrolahi¹؛ Ali farmani^{* 2}؛ Ashkan Horri³؛ Hossein Hatami⁴

¹Department of Electrical Engineering, Arak branch, Islamic Azad University, Arak, Iran

²Faculty of Engineering, Lorestan University

³Department of Electrical Engineering, Engineering Faculty, Arak Branch, Islamic Azad University, Arak, Iran

⁴Faculty of Engineering

تاریخ دریافت: 25 تیر 1403،  تاریخ بازنگری: 28 تیر 1404،  تاریخ پذیرش: 03 مرداد 1404 

چکیده

Abstract

In this paper, we explore the notable advancements in optical biosensors that have emerged over the past decade. This analysis includes innovative fabrication techniques and the growing areas of application. A historical overview of the development of optical biosensors since the 1970s is also presented, drawing from key literature. We further categorize biosensors and their typical architectures, highlighting new developments that may shape the current decade. Additionally, we discuss significant and creative application domains from the last ten years, illustrating the versatility of these sensors. The paper concludes by addressing the challenges and future possibilities of emerging technologies in optical biosensing for the current decade. By utilizing the GWO algorithm, researchers and engineers can efficiently explore the design space, identify optimal solutions, and enhance the performance of plasmonic nanoring resonators for various applications such as biosensing, optical communications, and photonics devices. When applied to the design of nanoring resonators, the grey wolf optimization algorithm can be used to optimize the parameters such as the dimensions of the nanoring, the material properties, and the operating conditions to achieve specific resonant frequencies or other desired characteristics. By iteratively updating the positions of a population of virtual wolves based on their fitness in the solution space, the algorithm can efficiently search for the best set of parameters for the nanoring resonator design.

کلیدواژه‌ها

Ring resonator؛ Plasmonics sensor؛ FDTD