Photonic Sensors for Detection of VOC Biomarkers
Technological Principles and Medical Applications
- 1st Edition - August 27, 2026
- Latest edition
- Authors: Akhilesh Kumar Pathak, Charusluk Viphavakit, Sridhar Krishnaswamy
- Language: English
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… Read more
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Description
Description
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
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
Readership
Readership
Researchers and graduate students working with Organic Chemistry, Biomedical Engineering, sensing technology, and biomarkers
Table of contents
Table of contents
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
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
Product details
Product details
- Edition: 1
- Latest edition
- Published: August 29, 2026
- Language: English
About the authors
About the authors
AP
Akhilesh Kumar Pathak
Akhilesh Kumar Pathak: Dr. Pathak obtained his Ph.D. degree from the Indian Institute of Technology (Indian School of Mines), India in 2019. During his Ph.D. he was awarded a prestigious EM Leaders fellowship in 2017 to conduct part of his Ph.D. from the City University of London, United Kingdom. In 2020 he was granted C2F post-doctoral fellowship to conduct his two years post-doctoral research at
Chulalongkorn University, Thailand. Currently, he is working as a post-doctoral scholar at Northwestern University, USA under the supervision of Prof. S. Krishnaswamy. He is a Senior Member of IEEE and OPTICA and also serving as an editorial board member for the Journal of Sensors. He has published
more than 30 International Journals, conferences, and book chapters and being cited by more than 591 times with an h-index of 16. He has also reviewed more than 300 journals and edited more than 30 articles for the Journal of Sensors, Photonics, Frontier in Photonics, and Frontier in Physics. His research interest includes optical fiber modeling using the full vectorial finite element method (FV-FEM), femtosecond direct laser-writing, 3D printing using two-photon polymerization, synthesis and
controlled growth of nanoparticles, hydrogels, and specialized optically active material for various sensing applications.
Affiliations and expertise
Post-doctoral scholar, Northwestern University, USACV
Charusluk Viphavakit
C. Viphavakit: Charusluk Viphavakit was born in Bangkok, Thailand. She received the Bachelor’s degree in Nanoelectronic Engineering from Chulalongkorn University, Thailand, in 2010, the Master’s degree in nanotechnology from the Asian Institute of Technology, Thailand, in 2012, and the Ph.D. degree from Frederick University, Cyprus, with ERASMUN MUNDUS scholarship in 2015 and from City, University of London, UK in 2018. She was a Postdoctoral Researcher in Optical Fibre Research Centre, University of
Limerick, Ireland, through Irish Research Council Fellowship for two years. During her postdoctoral career in 2016, she received Harvard Medical School Scholarships and University of Limerick Graduate Entry Medical School funding to enrol in Global Clinical Scholars Research Training Program (GCSRT) 2016-2017 from Harvard Medical School (HMS), Boston, MA, USA, for advanced training and conducting of clinical research. She is a Senior Member of IEEE and IEEE Photonics Society. She is also a member of OPTICA and SPIE. She is currently a full-time Assistant professor, and head of NanoEngineering program at the International School of Engineering, Chulalongkorn University. She is in the editorial board of the Engineering Journal. Her research interests include optical waveguide and optical fiber sensor for biomedical applications.
Affiliations and expertise
Chulalongkorn University, ThailandSK
Sridhar Krishnaswamy
S. Krishnaswamy: Prof. Krishnaswamy has been a member of the faculty of mechanical engineering at Northwestern University since 1990. He received his MS and PhD degrees in aeronautics from California Institute of Technology in 1984 and 1989, respectively. Currently, he is the director of the Center for
Smart Structures and Materials at Northwestern University. He has been actively involved in the areas of nondestructive materials characterization, optical metrology, structural health management, and fiber-optic and 3D printed photonic sensors. He is a fellow of SPIE and ASME.
Affiliations and expertise
Faculty of Mechanical Engineering, Northwestern University, USAView book on ScienceDirect
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