bullet  Advances in Biosensors: Reviews, Vol. 1

    (Open Access Book)


  Title: Advances in Biosensors: Reviews, Vol. 1. Book Series

  Editor: Sergey Y. Yurish

  Publisher: International Frequency Sensor Association (IFSA) Publishing, S. L.

  Formats: hardcover (print book with full colour illustrations) and printable pdf Acrobat (e-book), 198 pages

  Price: 115.00 EUR for print book in hardcover

  Delivery time for print book: 7-17 days. Please contact us for priority (5-9 days), ground (3-8 days) and express (2-3 days) delivery options by e-mail

  Pubdate: 31 May 2017

  ISBN: 978-84-697-3467-4

  e-ISBN: 978-84-697-3468-1


  Creative Commons License




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Advances in Biosensors: Reviews, Vol. 1


 Book Description


Every research and development in biosensors (as well as in any other research fields) is started from a state-of-the-art review. Such review is one of the most labor- and time consuming parts of research. It is strongly necessary to take into account and reflect in the review the current stage of development, including existing sensing principles, methods of measurements, technologies and existing devices. This open access book is intended to help researchers to find appropriate references, to read it and make a critical analysis to determine what was done well before and what was not solved till now and formulate the future scientific aims and objectives. The first volume of Advances in Biosensors: Reviews, Book Series contains seven chapters written by 14 authors from 9 countries: Australia, Bulgaria, China, Germany, Poland, Russia, Spain, Turkey and USA. We hope that readers enjoy this book and that can be a valuable tool for those who are involved in research and development different biosensors and biosensing systems.







1. Printed and Flexible BioChemical Sensors/Electronics

1.1. Electronic Sensors
1.2. Intersecting Technologies and Overlapping Needs
1.2.1. An Optical Probe for Biogeochemical Sensing of Peat Bogs
1.2.2. Sensing for Asset Monitoring and Fault Diagnosis in Electrical Systems
1.2.3. Remote Sensing of CH4 Using a Laser Tomographic Technique
1.2.4. Large-scale Sensing
1.2.5. Common Theme Common Need
1.3. Printed Sensors and Electronics
1.3.1. Passive Wireless Sensors
1.3.2. Advanced Printed Sensors: SAW and Retroreflectors
1.4. Conclusions


2. Development and Applications of Upconversion Nanoparticle in Biosensing
2.1. Introduction
2.2. Optical Properties of UCNPs
2.2.1. Large anti-Stokes Shift and Narrow Multicolour Emission
2.2.2. Tuneable Upconversion Luminescence
2.2.3. Non-invasive and Sensitive Bioassay in Deep Tissues
2.2.4. Superb Photostability
2.3. Development of UCNP-based Biosensors
2.3.1. Synthesis of UCNPs Thermal Decomposition Hydro(solvo)thermal Synthesis Coprecipitation
2.3.2. Fabrication of UCNPs-based Sensing Platforms Physical Adsorption Coordination Bond Covalent Coupling
2.4. Applications of UCNPs in Biosensing
2.4.1. UCNPs Nanosensors for the Detection of Ions
2.4.2. UCNPs Nanosensors for the Detection of Biomolecules Application of UCNPs in DNA Detection Application of UCNPs in the Detection of Small Molecules, Proteins and Enzymes
2.4.3. UCNPs Nanosensors for the Detection of Gas Molecules
2.5. Conclusions


3. A Review of Nano-Particle Analysis with the PAMONO-Sensor
3.1. Introduction
3.2. Technical Aspects of the PAMONO-Sensor
3.3. Processing of PAMONO Sensor Data
3.3.1. Detection, Classification and Quantification of Nano-Objects
3.3.2. Particle Size Distributions
3.3.3. Software Parameter Optimization
3.3.4. Miniaturization and Resource-Aware Optimizations
3.4. Results and Discussion
3.4.1. Measurements of Detection Quality using Optimized Pipeline Parameters
3.4.2. Particle Size Classification
3.4.3. Energy-Aware Optimization and Offloading
3.5. Conclusion and Outlook


4. MEMS Magnetic Biosensors
4.1. Introduction to MEMS Magnetic Biosensor
4.1.1. MEMS Technology
4.1.2. What are BioMEMS?
4.1.3. Magnetic Biosensors
4.2. Fabrication of MEMS-based Magnetic Biosensors
4.2.1. Giant Magnetoimpedance (GMI) Sensors GMI Effect MEMS Process of GMI Sensor GMI Bio-sensing Principle
4.2.2. Giant Magnetoresistance (GMR) Sensors GMR Sensor GMR Sensor GMR Bio-sensing Principle
4.2.3. Micro Fluxgate Sensors MEMS Fluxgate Sensors Design and Fabrication of MEMS Fluxgate Sensors Micro Fluxgate Bio-sensing Principle
4.3. Detection of Magnetic Labels
4.4. Detection of Biomarker Based Magnetic Measurement
4.4.1. GMI Biosensor for Detection of Biomarkers
4.4.2. GMR Biosensor for Detection of Biomarkers
4.4.3. Micro Fluxgate Biosensor for Detection of Biomarkers

4.5. Conclusion


5. Application of Surface Photo-Charge Effect for Control of Fluids
5.1. Introduction
5.2. SPCE
5.3. SPCE at the Liquid-Solid Interface
5.4. Applications
5.4.1. SPCE-Signal for Liquid Identification
5.4.2. Monitoring of the Octane Factor of Gasoline
5.4.3. Detection of Impurities in Liquids
5.4.4. Monitoring of Material Deposition from a Solution
5.4.5. Level Meter
5.4.6. Milk Quality Control
5.5. Conclusions


6. Electronic Nose

6.1. Introduction
6.2. Physiology of Human Nose
6.3. E-nose
6.4. Sensors Employed in E-nose Systems
6.4.1. Metal Oxide Semiconductor (MOS) Sensors
6.4.2. Metal Oxide Semiconductor Field-Effect Transistor (MOSFET) Sensors
6.4.3. Conducting Polymer (CP) Sensors
6.4.4. Piezoelectric Crystal Sensors (Acoustic Sensors)
6.4.5. Biosensors
6.5. Application Areas of E-nose
6.5.1. Medical Diagnosis and Health Monitoring Respiratory Disease Diagnosis Cancer Detection
6.5.2. Environmental Applications
6.5.3. Food Industry
6.5.4. Crime Prevention
6.5.5. Space Applications (E-nose and NASA)
6.6. Conclusions


7. Electronic Noses and Electronic Tongues
7.1. Introduction
7.2. Senses of Smell and Taste
7.3. Electronic Nose
7.4. Electronic Tongue
7.5. Sensors Used in Electronic Noses and Electronic Tongues
7.5.1. Conductometric Sensors
7.5.2. Potentiometric Sensors
7.5.3. Amperometric and Voltammetric Sensors

7.5.4. Impedimetric Sensors
7.5.5. Piezoelectric Sensors
7.5.6. Optical Sensors
7.5.7. Biosensors
7.6. Data Analysis Methods
7.6.1. Artificial Neural Networks (ANN)
7.6.2. Cluster Analysis (CA)
7.6.3. k-Nearest Neighbour (k-NN)
7.6.4. Discriminant Function Analysis (DFA)
7.6.5. Partial Least Squares (PLS)
7.6.6. Linear Discriminant Analysis (LDA)
7.6.7. Soft Independent Modelling of Class Analogies (SIMCA)
7.6.8. Support Vector Machines (SVMs)
7.6.9. Analysis of Variance (ANOVA)
7.7. Applications
7.7.1. Food Investigations
7.7.2. Environmental Monitoring
7.8. Summary

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