
Artificial Intelligence and Spectroscopic Techniques for Gemology Applications.
Title:
Artificial Intelligence and Spectroscopic Techniques for Gemology Applications.
Author:
Shukla, Ashutosh Kumar.
ISBN:
9780750339278
Personal Author:
Edition:
1st ed.
Physical Description:
1 online resource (168 pages)
Series:
IOP Ebooks Series
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.
Abstract:
This volume highlights the applications of different spectroscopic techniques in gems identification and analysis.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Genre:
Electronic Access:
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