Photonic Sensors for Detection of VOC Biomarkers

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Photonic Sensors for Detection of VOC Biomarkers,

Edition 1 Technological Principles and Medical Applications

Editors: By Sridhar Krishnaswamy, Akhilesh Kumar Pathak and Charusluk Viphavakit

Publication Date: 27 Aug 2026

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VOCs available in exhaled human breath are the products of metabolic activity in the body and, therefore, any changes in their control level can be utilized to diagnose specific diseases. More than 3000 VOCs have been identified in exhaled human breath along with the respiratory droplets which provide useful information on overall health conditions. This book covers the introductory information on VOCs, their source in the human body, associated diseases, potential sensing materials used for selective detection, and the advancement in the VOC sensing technologies. However, developing a rapid, highly selective, and sensitive VOC sensor remains a great challenge. This book analyzes all the challenges and their possible solutions that can be used to achieve target-specific detection and real-time monitoring of the VOC molecules in the exhaled breath. It also covers a detailed discussion of various sensing materials developed for selective and sensitive detection of VOC molecules and their integration with photonic devices in order to develop miniature technology. It covers various miniature sensing systems that are being exploited in VOC sensing such as interferometer, fiber Bragg gratings (FBGs), microstructured optical fiber (MOF), integrated photonics, 3D-printed optical devices, etc. Additionally, the book provides an overview of the FEM technique and computational methods used to optimize the optical sensing devices before practical realization. This book aims to provide comprehensive information to early career professionals and boost their existing knowledge in the area of Chemistry and Biomedical Engineering.

Key Features

Bridges clinical breath analysis and photonic sensing, covering VOC biomarkers, associated diseases, and conventional non-invasive detection methodology
Guides material selection for VOC sensing, comparing the sensitivity, selectivity, and limitations of various sensing materials
Covers key photonic platforms for VOC sensing, including interferometers, FBGs, MOFs, and integrated photonic systems, with FEM-based computational optimization
Addresses semi-volatile organic compounds and AI-integrated photonic sensors for next generation VOC detection

About the author

By Sridhar Krishnaswamy, Faculty of Mechanical Engineering, Northwestern University, USA; Akhilesh Kumar Pathak, Post-doctoral scholar, Northwestern University, USA and Charusluk Viphavakit, Chulalongkorn University, Thailand

1. Introduction to volatile organic compounds
1.1. Introduction
1.2. Types of volatile organic compounds
1.3. Sources of volatile organic compound emissions
1.4. Environmental impacts of volatile organic compounds and climate change
1.5. Origin of volatile organic compounds in the human body
1.6. Biomedical diagnosis applications
1.7. Conclusion

2. Classical approaches to breath VOC monitoring for disease diagnosis
2.1. Introduction
2.2. Breath collection
2.3. Breath analysis techniques
2.4. Disease identification using conventional breath analyzers
2.5. Challenges
2.6. Conclusion

3. Advances in photonic sensors for health and environmental monitoring
3.1. Introduction
3.2. Classification of photonic sensors
3.3. Optical fiber sensors
3.4. Optical waveguide
3.5. Wearable sensor
3.6. Metasurface based sensors
3.7. Plasmonic sensors
3.8. Photonics sensors market
3.9. Fabrication method of photonic sensors
3.10. Application of photonic devices in volatile organic compound monitoring
3.11. Advantages, limitations, and challenges of photonic devices
3.12. Conclusion

4. Simulation and design optimization of optical VOC sensors using the finite element method
4.1. Introduction
4.2. Fundamentals of the finite element method
4.3. Guided-mode analysis
4.4. Beam propagation methods
4.5. Types of finite element method used for analysis
4.6. Applications
4.7. Conclusion

5. VOC sensing materials: Principles and recent advances
5.1. Introduction
5.2. Metal oxides
5.3. Carbon and composites
5.4. Polymers
5.5. Other sensing materials
5.6. Prospects
5.7. Conclusion

6. Interferometric photonic sensors for VOC detection: Advancements and applications
6.1. Introduction
6.2. Principles of interferometry
6.3. Mach–Zehnder interferometer
6.4. Fabry–Perot interferometer
6.5. Pohl interferometer
6.6. Sagnac interferometer
6.7. Future prospects and challenges
6.8. Conclusion

7. Fundamentals and applications of fiber Bragg gratings in VOC sensing
7.1. Introduction
7.2. Photosensitivity types of fiber Bragg gratings
7.3. Fabrication of fiber Bragg gratings
7.4. Classification by grating structure
7.5. Sensing mechanism
7.6. Detection of volatile organic compound
7.7. Detection of semi-volatile organic compounds
7.8. Detection of other organic pollutants
7.9. Challenges and prospects
7.10. Conclusion

8. Microstructured optical fiber sensors for VOC detection
8.1. Introduction
8.2. Fabrication of microstructured optical fibers
8.3. Types of microstructured optical fibers
8.4. Application of photonic crystal fibers for monitoring various volatile organic compound molecules
8.5. Prospects and challenges
8.6. Conclusion

9. On-chip photonic sensors for volatile organic compound detection
9.1. Introduction
9.2. Basic elements of integrated photonics
9.3. Integrated photonic-based volatile organic compounds sensors
9.4. Manufacturing strategies for integrated photonic systems
9.5. Prospects and challenges
9.6. Conclusion

10. Advances in photonic sensors for semi-volatile organic compound detection
10.1. Introduction
10.2. Semi-volatile organic compounds in consumer products
10.3. Difference between volatile organic compounds and semi-volatile organic compounds
10.4. Semi-volatile organic compounds in the indoor environment
10.5. Photonic sensors for the detection of semi-volatile organic compounds
10.6. Future prospects and challenges
10.7. Conclusion

11. Next-gen VOC sensing: AI-driven non-invasive detection
11.1. Introduction
11.2. Fundamentals of machine learning algorithms
11.3. Popular artificial intelligence methods in gas sensing
11.4. Artificial intelligence-integrated volatile organic compounds sensors
11.5. Case studies
11.6. Challenges and opportunities for artificial intelligence in gas sensing
11.7. Conclusion

Photonic Sensors for Detection of VOC Biomarkers,

Editors: By Sridhar Krishnaswamy, Akhilesh Kumar Pathak and Charusluk Viphavakit

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Key Features

About the author

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