Laser induced breakdown spectroscopy (LIBS) . Volume 2. : concepts, instrumentation, data analysis and applications / / edited by Vivek K. Singh [and three others]

• Pubblicazione: Chichester, England : , : John Wiley & Sons Ltd, , [2023]; ©2023
• Descrizione fisica: 1 online resource (1004 pages)
• Disciplina: 543.52
• Soggetto topico: Laser-induced breakdown spectroscopy; Laser-plasma interactions
• Persona (resp. second.): SinghVivek K.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Cover -- Title Page -- Copyright -- Contents -- Preface -- Part I Fundamental Aspects of LIBS and Laser‐Induced Plasma -- Chapter 1 Nanosecond and Femtosecond Laser‐Induced Breakdown Spectroscopy: Fundamentals and Applications -- 1.1 Introduction -- 1.2 LIBS: ns‐LIBS and fs‐LIBS -- 1.3 Plasma‐Plume Dynamics -- 1.4 Filamentation -- 1.5 Signal‐Enhancing Strategies in LIBS -- 1.6 Applications -- 1.7 Summary -- References -- Chapter 2 Elementary Processes and Emission Spectra in Laser‐Induced Plasma -- 2.1 Introduction -- 2.2 Laser‐Ablation Mechanism -- 2.3 Plasma Characteristics and Elementary Processes -- 2.4 Plasma in Thermodynamic Equilibrium -- 2.5 Plasma Emission Features -- 2.6 Conclusion -- References -- Chapter 3 Diagnostics of Laser‐Induced Plasma -- 3.1 Introduction -- 3.2 LIBS Plasmas and Its Characteristics -- 3.2.1 Laser‐Induced Plasma -- 3.2.2 Plasma Temperature Measurements -- 3.2.3 Electron Density Measurements -- 3.2.3.1 Nonlinear Stark Broadening -- 3.2.3.2 Linear Stark Broadening -- 3.2.4 Additional Comments on the Characteristics of LIBS Plasmas -- 3.2.4.1 Matrix Effect -- 3.2.4.2 McWhirter Criterion -- 3.3 Factors Affecting the LIBS Plasma -- 3.3.1 Laser Characteristics -- 3.3.2 Wavelength and Pulse Duration of Laser -- 3.3.3 Properties of Target Material -- 3.3.4 Time Window of Observation -- 3.3.5 Geometric Setup -- 3.3.6 Ambient Gas -- 3.4 Methods of Enhancing LIBS Sensitivity -- 3.5 LTE Plasmas and Non‐LTE Plasmas -- 3.6 Laser-Plasma Expansion in Gas and Liquids: Modeling and Validation -- 3.7 Chemistry in Laser Plasmas (Biological, Medical, and Isotopic Applications) -- 3.8 Conclusion -- References -- Chapter 4 Double and Multiple Pulse LIBS Techniques -- 4.1 Introduction -- 4.2 Double‐Pulse LIBS: Geometries and Configurations -- 4.2.1 Collinear DP‐LIBS -- 4.2.2 Orthogonal DP‐LIBS -- 4.2.3 Parallel DP‐LIBS. ; 4.2.4 Variable Pulse Duration in DP‐LIBS -- 4.2.5 Variable Pulse Wavelength in DP‐LIBS -- 4.2.6 Multiple Pulse LIBS -- 4.3 Signal Enhancement in DP‐LIBS: Principles and Theory -- 4.4 Applications of DP‐LIBS -- 4.4.1 DP‐LIBS of Archaeological Artifacts -- 4.4.2 DP‐LIBS for the Stand‐Off Detection of Explosives -- 4.4.3 DP‐LIBS for the Analysis of Biological Materials -- 4.4.4 DP‐μ‐LIBS Mapping -- 4.5 Conclusions -- References -- Chapter 5 Calibration‐Free Laser‐Induced Breakdown Spectroscopy -- 5.1 Introduction -- 5.2 Validity Conditions of the Physical Model -- 5.2.1 Congruent Mass Transfer from the Solid Sample Toward Plasma -- 5.2.2 Local Thermodynamic Equilibrium -- 5.2.3 Spatial Distribution of Plasma -- 5.2.4 Self‐Absorption -- 5.2.5 Chemical Reactions -- 5.3 Methods of Calibration‐Free Measurements -- 5.3.1 The Mathematical Problem of a Multielemental Equilibrium Plasma -- 5.3.2 First CF‐LIBS Method for Ideal Plasma -- 5.3.3 Amended Methods -- 5.3.4 Methods Based on Spectra Simulation -- 5.3.4.1 Calculation of Spectral Radiance -- 5.3.4.2 Implementation in Measurement Algorithm -- 5.3.4.3 Illustration for Alloy -- 5.4 Critical Review of Analytical Performance -- 5.4.1 Model Validity -- 5.4.2 Error Evaluation -- 5.4.2.1 Minor and Trace Element Quantification -- 5.4.2.2 Error due to Self‐Absorption -- 5.4.3 Recommendations -- 5.4.3.1 Apparatus Requirements -- 5.4.3.2 Setting the Experimental Conditions -- 5.4.3.3 Selection of Spectral Lines -- 5.4.4 Expected Improvements -- 5.4.4.1 Evolution of the Spectroscopic Database -- 5.4.4.2 Advanced Instrumentation -- 5.4.4.3 Improved Knowledge of Laser‐Induced Plasma -- 5.5 Conclusion -- References -- Part II Molecular LIBS and Instrumentation Developments -- Chapter 6 Molecular Species Formation in Laser‐Produced Plasma -- 6.1 Introduction -- 6.2 Atmospheric Contribution in LIBS Spectra. ; 6.3 CN and C2 Molecular Formation in LIP -- 6.4 Summary -- References -- Chapter 7 Recent Developments in Standoff Laser‐Induced Breakdown Spectroscopy -- 7.1 Introduction -- 7.2 Laser Systems Used -- 7.3 Instrumentation in Standoff LIBS -- 7.4 Gated and Non‐Gated CCDs/Spectrometers -- 7.5 Experimental Setup -- 7.6 Reviews on Standoff LIBS -- 7.7 Studies in Standoff LIBS -- 7.8 Variants in Standoff LIBS -- 7.9 Machine‐Learning for Data Analysis in Standoff Mode -- 7.10 Advancements in Standoff LIBS Methods -- 7.11 Ongoing Study at ACRHEM, University of Hyderabad -- 7.12 Conclusions and Outlook -- Acknowledgments -- References -- Chapter 8 Nanoparticle‐Enhanced Laser‐Induced Breakdown Spectroscopy -- 8.1 Introduction -- 8.2 Fundamentals -- 8.2.1 Plasmon Excitation in NPs During NELIBS -- 8.2.2 Broadening of the Plasmon Frequency due to Plasmon Coupling -- 8.2.3 Local Field Enhancement -- 8.2.4 Influence of Sample Properties on Laser Ablation Mechanism During NELIBS -- 8.2.5 Nanoparticles Under a Strong Electromagnetic Field and Consequently in the Plasma Phase -- 8.2.6 Origin of Plasma Emission Enhancement -- 8.3 Applications -- 8.3.1 Sample Preparation and Setup -- 8.3.2 Application in the Field of Analytical Chemistry -- 8.4 Conclusion -- References -- Chapter 9 Nanoparticle‐Enhanced Laser‐Induced Breakdown Spectroscopy for Sensing Applications -- 9.1 Introduction -- 9.2 Previous Reviews -- 9.3 Experimental Setup -- 9.4 Enhancement Via Different Conditions -- 9.5 Perspectives on the Mechanism(s) of Enhancement -- 9.6 Variations in NE‐LIBS -- 9.7 Beyond NE‐LIBS -- 9.8 Further Application of Nanoparticles in LIBS -- 9.9 Ongoing Study in the Lab -- 9.10 Conclusions -- References -- Part III Data Analysis and Chemometrics in LIBS -- Chapter 10 Full‐Spectrum Multivariate Analysis of LIBS Data -- 10.1 Introduction. ; 10.2 Full‐Spectrum Multivariate Analysis -- 10.3 Analysis of Geologic Samples -- 10.4 Identification of Pharmaceuticals -- 10.4.1 Methods -- 10.4.2 Acetaminophen -- 10.4.3 Aspirin -- 10.5 Conclusions -- References -- Chapter 11 Chemometrics for Data Analysis -- 11.1 Introduction -- 11.2 Data -- 11.3 Machine Learning -- 11.3.1 Principal Component Analysis -- 11.4 Classification of the Data -- 11.4.1 Artificial Neural Network -- 11.5 Conclusion -- References -- Chapter 12 Chemometric Processing of LIBS Data -- 12.1 Introduction -- 12.2 Exploratory Analysis Methods for Visualization -- 12.2.1 Principal Component Analysis -- 12.3 Quantitative Analysis Methods -- 12.3.1 Main Steps of Multivariate Calibration Before and After LIBS Measurements -- 12.3.2 Multiple Linear Regression -- 12.3.3 Principal Component Regression -- 12.3.4 Partial Least Squares -- 12.4 Classification -- 12.4.1 Soft Independent Modeling of Class Analogy -- 12.4.2 Partial Least Squares‐Discriminant Analysis -- 12.5 Data Preprocessing -- 12.5.1 Baseline Correction -- 12.5.2 Normalization -- 12.5.2.1 Normalization to the Background -- 12.5.2.2 Normalization to the Total Area -- 12.5.2.3 Normalization to an Internal Standard -- 12.5.2.4 Standard Normal Variate -- 12.5.3 Scaling -- 12.6 Validation and Generalization -- 12.6.1 Validation -- 12.6.2 Generalization -- 12.6.3 Figure of Merit -- 12.6.3.1 Figures of Merit for Quantitative Models -- 12.6.3.2 Figures of Merit for Classification Models -- 12.7 Conclusions -- Acknowledgments -- References -- Chapter 13 How Chemometrics Allowed the Development of LIBS in the Quantification and Detection of Isotopes: A Case Study of Uranium -- 13.1 Introduction -- 13.2 The LIBS Method -- 13.3 Detection and Quantification -- 13.4 Chemometrics Solution -- 13.4.1 LIBS Spectrum Processing -- 13.4.2 Spectra Preprocessing. ; 13.4.3 Identification and Classification of Samples -- 13.4.4 Concentration Measurement -- 13.4.4.1 Subsets of Data and Cross‐Validation -- 13.4.5 PLS Algorithm -- 13.4.6 Results Using Orange Software -- 13.5 Conclusions -- References -- Chapter 14 Application of Multivariate Analysis to the Problem of the Provenance of Gem Stones (Ruby, Sapphire, Emerald, Diamond) -- 14.1 Introduction -- 14.1.1 The Problem of Gem Provenance -- 14.1.2 Analytical Methods Employed in the Determination of Gem Provenance -- 14.2 Gem Mineral Genesis -- 14.2.1 Corundum: Ruby and Sapphire Genesis -- 14.2.2 Diamond Genesis -- 14.2.3 Emerald Genesis -- 14.2.4 Characteristics of a System to Determine Gem Provenance -- 14.3 Laser‐Induced Breakdown Spectroscopy and Multivariate Analysis -- 14.3.1 Laser‐Induced Breakdown Spectroscopy -- 14.3.2 Multivariate Data Analysis -- 14.4 Gem Provenance Studies -- 14.4.1 Ruby and Sapphire -- 14.4.2 Diamond -- 14.4.3 Emerald -- 14.5 Conclusions -- References -- Chapter 15 Machine Learning in the Context of Laser‐Induced Breakdown Spectroscopy -- 15.1 Introduction -- 15.2 Fundamental Concepts of Machine Learning -- 15.3 Decision Trees and Related Ensemble Methods -- 15.3.1 Decision Trees -- 15.3.2 Ensemble Models -- 15.4 Support Vector Machines -- 15.5 Artificial Neural Networks -- 15.5.1 Artificial Neuron -- 15.5.2 Fully Connected Multilayer Perceptrons -- 15.5.3 Convolutional Neural Networks -- 15.5.4 Training of Artificial Neural Networks -- 15.6 Unsupervised Learning -- 15.6.1 K‐Means Clustering -- 15.6.2 Autoencoder -- 15.7 Self‐Organizing Maps -- 15.8 Concluding Remarks -- Acknowledgement -- References -- Chapter 16 Analysis of LIBS Data from Coal and Biomass Using Artificial Intelligence Techniques -- 16.1 Introduction -- 16.2 LIBS Coal and Biomass Laboratory Experimental Results. ; 16.3 Application of Artificial Intelligence Techniques to LIBS Spectral Data.
• Titolo autorizzato: Laser induced breakdown spectroscopy (LIBS)
• ISBN: 1-119-75839-4; 1-119-75842-4; 1-119-75846-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910684596403321
• Lo trovi qui: Univ. Federico II