Abstract
Background & Objective: In this article, a nano-cell coupled 2D photonic crystal waveguide bio- detection platform is proposed for the detection of organic liquids such as water, ethanol, glycerol, benzene and bromine for different refractive indices (n).
Methods: The detection characteristics are analyzed and obtained for the band diagram, before and after change of radius (r) as well as after the injection of liquids into the heart of the nanostructure cell at the resonant wavelength (λ res). Also, we extracted variations from the power flow norm (P) to the resonance and the transmission (T) for each material. This nanostructure for different (n) materials used, gives (P) at different levels to the resonance. This explains the importance of the refractive index parameter (n) which plays a crucial role in the detection of materials. Results & Conclusion: The proposed biosensor enables the detection of liquids. This is shown through the numerical results obtained. These results give a good observation of the different behavior of the signal in the presence of the liquids used which depend on their refractive indices 'n'. This parameter 'n' is very important for detection when it varies from material to material. The proposed biosensor can be used in several research areas, particularly in medical and environmental applications.Keywords: Photonic crystals, finite element method (FEM), photonic sensor, organic liquids, resonant wavelength, refractive index.
Graphical Abstract
Call for Papers in Thematic Issues
Federated learning for biomedical applications
Federated learning, also known as distributed AI/machine learning, is a method that enables cooperative learning from big datasets owned by several parties without compromising the privacy of each person's raw data. FL is especially helpful when the needed information is not open source or easily accessible due to tactical or ...read more
Information, Trust, and Risk: Exploring the Intersection of Sensing, Wireless Communications, and Control
Sensing technologies, wireless communications, and control systems are becoming ubiquitous in our daily lives, with the potential to enhance and streamline many aspects of modern society. However, this also creates new challenges in terms of ensuring trust and managing risks associated with the use of these technologies. The sheer volume ...read more
Machine Learning for Industry 4.0 manufacturing applications
This thematic issue will focus on the intersection of Machine Learning and the manufacturing industry within the context of Industry 4.0. Industry 4.0 involves the use of smart sensors, devices, and machines to enable the creation of smart factories that constantly collect data related to production. Machine Learning techniques can ...read more
Next-Generation Network Architecture, Algorithms, and Security
Design of new network architectures, algorithms and protocols is one of the fundamental challenges in next-generation networking. To this end, novel networking techniques and applications are required for advancing today?s complex communication networks. This thematic issue provides researchers, industry professionals and practitioners with a forum to present the latest research ...read more
Related Books
IoT-enabled Sensor Networks: Architecture, Methodologies, Security, and Futuristic Applications
AIoT and Big Data Analytics for Smart Healthcare Applications
Research Trends in Artificial Intelligence: Internet of Things
Artificial Intelligence and Multimedia Data Engineering
Basics of Python Programming: A Quick Guide for Beginners
Blockchain Technology in Healthcare - Concepts, Methodologies, and Applications
Artificial Intelligence and Knowledge Processing: Methods and Applications
Handbook of Artificial Intelligence
Amazon Web Services: the Definitive Guide for Beginners and Advanced Users
The Role of AI in Enhancing IoT-Cloud Applications
3