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Table of Contents
Intro
Preface
Editor biography
Ashutosh Kumar Shukla
List of contributors
Chapter 1 Laser-induced breakdown spectroscopy for gemological testing
1.1 Introduction
1.2 What is LIBS
1.3 Applications of LIBS in gemology
1.4 Conclusion
References
Chapter 2 Raman spectroscopy for the non-destructive analysis of gemstones
2.1 Raman spectroscopy on gemstones
2.1.1 A short introduction to Raman spectroscopy
2.2 Benchtop and mobile Raman spectroscopy
2.3 Selected topics of Raman spectroscopy for gemological purposes, including forgeries
2.3.1 Garnets
2.3.2 Jade
2.3.3 Beryls
2.3.4 Corundum and other gemstones
2.3.5 Raman and photoluminescence emission
2.3.6 Glass
2.3.7 Pearls and corals
2.3.8 Forgeries
2.4 Conclusions
Acknowledgments
References
Chapter 3 Application of Fourier-transformed infrared spectroscopy and machine learning algorithm for gem identification
3.1 Introduction
3.2 Concept of IR spectroscopy
3.2.1 FT-IR sampling techniques for gem analysis
3.3 Diamond
3.3.1 Classification of diamond types
3.3.2 Characterization of synthetic diamonds and treated diamonds
3.3.3 Identification of diamond imitations
3.4 Rubies and sapphires
3.4.1 General information on rubies and sapphires
3.4.2 Application of FITR for corundum analysis
3.5 Emerald
3.5.1 Identification of natural and synthetic emeralds
3.5.2 Origin determination
3.5.3 Identification of resin-filled emeralds
3.6 Quartz
3.6.1 Identification of natural and synthetic quartz
3.6.2 Characterization of heat treatment and irradiation
3.7 Jade
3.7.1 Identification of jade enhancement
3.8 Turquoise
3.8.1 Characterization of turquoise
3.8.2 Identification of treated and imitated turquoise.
3.9 Application of machine learning algorithm to gemstone classification
3.10 Conclusions
References
Chapter 4 A ruby stone grading inspection using an optical tomography system
4.1 Introduction
4.2 Methodology
4.2.1 Mathematical expression
4.2.2 Image reconstruction
4.3 Results and discussion
4.3.1 Analysis on image reconstruction
4.3.2 Statistical ANOVA test analysis
4.4 Conclusion
Acknowledgments
References
Chapter 5 Trace elements and big data application to gemology by x-ray fluorescence
5.1 Introduction to XRF technique
5.1.1 The fundamentals of XRF
5.1.2 The advantages of XRF
5.2 Trace elements and analysis in gemstones
5.3 Case study of XRF and big data gemology
5.3.1 Identification of species and varieties
5.3.2 Color origin and fluorescence
5.3.3 Treatment detection
5.4 Big data application in gemology: geographic origin determination
5.4.1 Ruby
5.4.2 Spinel
References and further reading.
Preface
Editor biography
Ashutosh Kumar Shukla
List of contributors
Chapter 1 Laser-induced breakdown spectroscopy for gemological testing
1.1 Introduction
1.2 What is LIBS
1.3 Applications of LIBS in gemology
1.4 Conclusion
References
Chapter 2 Raman spectroscopy for the non-destructive analysis of gemstones
2.1 Raman spectroscopy on gemstones
2.1.1 A short introduction to Raman spectroscopy
2.2 Benchtop and mobile Raman spectroscopy
2.3 Selected topics of Raman spectroscopy for gemological purposes, including forgeries
2.3.1 Garnets
2.3.2 Jade
2.3.3 Beryls
2.3.4 Corundum and other gemstones
2.3.5 Raman and photoluminescence emission
2.3.6 Glass
2.3.7 Pearls and corals
2.3.8 Forgeries
2.4 Conclusions
Acknowledgments
References
Chapter 3 Application of Fourier-transformed infrared spectroscopy and machine learning algorithm for gem identification
3.1 Introduction
3.2 Concept of IR spectroscopy
3.2.1 FT-IR sampling techniques for gem analysis
3.3 Diamond
3.3.1 Classification of diamond types
3.3.2 Characterization of synthetic diamonds and treated diamonds
3.3.3 Identification of diamond imitations
3.4 Rubies and sapphires
3.4.1 General information on rubies and sapphires
3.4.2 Application of FITR for corundum analysis
3.5 Emerald
3.5.1 Identification of natural and synthetic emeralds
3.5.2 Origin determination
3.5.3 Identification of resin-filled emeralds
3.6 Quartz
3.6.1 Identification of natural and synthetic quartz
3.6.2 Characterization of heat treatment and irradiation
3.7 Jade
3.7.1 Identification of jade enhancement
3.8 Turquoise
3.8.1 Characterization of turquoise
3.8.2 Identification of treated and imitated turquoise.
3.9 Application of machine learning algorithm to gemstone classification
3.10 Conclusions
References
Chapter 4 A ruby stone grading inspection using an optical tomography system
4.1 Introduction
4.2 Methodology
4.2.1 Mathematical expression
4.2.2 Image reconstruction
4.3 Results and discussion
4.3.1 Analysis on image reconstruction
4.3.2 Statistical ANOVA test analysis
4.4 Conclusion
Acknowledgments
References
Chapter 5 Trace elements and big data application to gemology by x-ray fluorescence
5.1 Introduction to XRF technique
5.1.1 The fundamentals of XRF
5.1.2 The advantages of XRF
5.2 Trace elements and analysis in gemstones
5.3 Case study of XRF and big data gemology
5.3.1 Identification of species and varieties
5.3.2 Color origin and fluorescence
5.3.3 Treatment detection
5.4 Big data application in gemology: geographic origin determination
5.4.1 Ruby
5.4.2 Spinel
References and further reading.