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The Handbook of Infrared and Raman Characteristic Frequencies of Organic Molecules

22 Oct 1991-
TL;DR: The -NH2, -NHR, and -NR2 groups as discussed by the authors are the most commonly used groups for double bonds containing Nitrogen Atoms, and the -C=N and -N=C groups.
Abstract: Alkanes. Halocompounds. Alcohols and Phenols. Ethers and Peroxides. Alkenes. Acetylenes. The -C=N and -N=C Groups. Compounds Containing the Carbonyl Group. Compounds Containing -NH2, -NHR, and -NR2 Groups. The Nitro Group. Double Bonds Containing Nitrogen Atoms. Cumulated Double Bonds. Organic Sulfur Compounds. Organosilicon Compounds. Organophosphorous Compounds. Aromatic and Heteroaromatic Rings. Selected Infrared and Raman Spectra. Appendices. Index.
Citations
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Journal ArticleDOI
TL;DR: In this paper, a model and theoretical understanding of the Raman spectra in disordered and amorphous carbon is given, and the nature of the G and D vibration modes in graphite is analyzed in terms of the resonant excitation of \ensuremath{\pi} states and the long-range polarizability of the long range bonding.
Abstract: The model and theoretical understanding of the Raman spectra in disordered and amorphous carbon are given. The nature of the G and D vibration modes in graphite is analyzed in terms of the resonant excitation of \ensuremath{\pi} states and the long-range polarizability of \ensuremath{\pi} bonding. Visible Raman data on disordered, amorphous, and diamondlike carbon are classified in a three-stage model to show the factors that control the position, intensity, and widths of the G and D peaks. It is shown that the visible Raman spectra depend formally on the configuration of the ${\mathrm{sp}}^{2}$ sites in ${\mathrm{sp}}^{2}$-bonded clusters. In cases where the ${\mathrm{sp}}^{2}$ clustering is controlled by the ${\mathrm{sp}}^{3}$ fraction, such as in as-deposited tetrahedral amorphous carbon (ta-C) or hydrogenated amorphous carbon (a-C:H) films, the visible Raman parameters can be used to derive the ${\mathrm{sp}}^{3}$ fraction.

12,593 citations

Reference EntryDOI
15 Sep 2006
TL;DR: In this paper, the authors present a first-pass interpretation of the infrared spectrum of a molecule, based on structural features of the molecule, whether they are the backbone of the molecules or the functional groups attached to the molecule.
Abstract: The vibrational spectrum of a molecule is considered to be a unique physical property and is characteristic of the molecule. As such, the infrared spectrum can be used as a fingerprint for identification by the comparison of the spectrum from an “unknown” with previously recorded reference spectra. This is the basis of computer-based spectral searching. In the absence of a suitable reference database, it is possible to effect a basic interpretation of the spectrum from first principles, leading to characterization, and possibly even identification of an unknown sample. This first principles approach is based on the fact that structural features of the molecule, whether they are the backbone of the molecule or the functional groups attached to the molecule, produce characteristic and reproducible absorptions in the spectrum. This information can indicate whether there is backbone to the structure and, if so, whether the backbone consists of linear or branched chains. Next it is possible to determine if there is unsaturation and/or aromatic rings in the structure. Finally, it is possible to deduce whether specific functional groups are present. If detected, one is also able to determine local orientation of the group and its local environment and/or location in the structure. The origins of the sample, its prehistory, and the manner in which the sample is handled all have impact on the final result. Basic rules of interpretation exist and, if followed, a simple, first-pass interpretation leading to material characterization is possible. This article addresses these issues in a simple, logical fashion. Practical examples are included to help guide the reader through the basic concepts of infrared spectral interpretation.

3,824 citations

Book
30 Jul 2004
TL;DR: In this paper, the authors present a set of techniques for detecting anomalous infrared spectra, including Fourier Transform Infrared Spectrometers (FTIS) and Spectral Spectral Transform Transform (STT) this paper.
Abstract: Series Preface.Preface.Acronyms, Abbreviations and Symbols.About the Author.1. Introduction.1.1 Electromagnetic Radiation.1.2 Infrared Absorptions.1.3 Normal Modes of Vibration.1.4 Complicating Factors.1.4.1 Overtone and Combination Bands.1.4.2 Fermi Resonance.1.4.3 Coupling.1.4.4 Vibration-Rotation Bands.References.2. Experimental Methods.2.1 Introduction.2.2 Dispersive Infrared Spectrometers.2.3 Fourier-Transform Infrared Spectrometers.2.3.1 Michelson Interferometers.2.3.2 Sources and Detectors.2.3.3 Fourier-Transformation.2.3.4 Moving Mirrors.2.3.5 Signal-Averaging.2.3.6 Advantages.2.3.7 Computers.2.3.8 Spectra.2.4 Transmission Methods.2.4.1 Liquids and Solutions.2.4.2 Solids.2.4.3 Gases.2.4.4 Pathlength Calibration.2.5 Reflectance Methods.2.5.1 Attenuated Total Reflectance Spectroscopy.2.5.2 Specular Reflectance Spectroscopy.2.5.3 Diffuse Reflectance Spectroscopy.2.5.4 Photoacoustic Spectroscopy.2.6 Microsampling Methods.2.7 Chromatography-Infrared Spectroscopy.2.8 Thermal Analysis-Infrared Spectroscopy.2.9 Other Techniques.References.3. Spectral Analysis.3.1 Introduction.3.2 Group Frequencies.3.2.1 Mid-Infrared Region.3.2.2 Near-Infrared Region.3.2.3 Far-Infrared Region.3.3 Identification.3.4 Hydrogen Bonding.3.5 Spectrum Manipulation.3.5.1 Baseline Correction.3.5.2 Smoothing.3.5.3 Difference Spectra.3.5.4 Derivatives.3.5.5 Deconvolution.3.5.6 Curve-Fitting.3.6 Concentration.3.7 Simple Quantitative Analysis.3.7.1 Analysis of Liquid Samples.3.7.2 Analysis of Solid Samples.3.8 Multi-Component Analysis.3.9 Calibration Methods.References.4. Organic Molecules.4.1 Introduction.4.2 Aliphatic Hydrocarbons.4.3 Aromatic Compounds.4.4 Oxygen-Containing Compounds.4.4.1 Alcohols and Phenols.4.4.2 Ethers.4.4.3 Aldehydes and Ketones.4.4.4 Esters.4.4.5 Carboxylic Acids and Anhydrides.4.5 Nitrogen-Containing Compounds.4.5.1 Amines.4.5.2 Amides.4.6 Halogen-Containing Compounds.4.7 Heterocyclic Compounds.4.8 Boron Compounds.4.9 Silicon Compounds.4.10 Phosphorus Compounds.4.11 Sulfur Compounds.4.12 Near-Infrared Spectra.4.13 Identification.References.5. Inorganic Molecules.5.1 Introduction.5.2 General Considerations.5.3 Normal Modes of Vibration.5.4 Coordination Compounds.5.5 Isomerism.5.6 Metal Carbonyls.5.7 Organometallic Compounds.5.8 Minerals.References.6. Polymers.6.1 Introduction.6.2 Identification.6.3 Polymerization.6.4 Structure.6.5 Surfaces.6.6 Degradation.References.7. Biological Applications.7.1 Introduction.7.2 Lipids.7.3 Proteins and Peptides.7.4 Nucleic Acids.7.5 Disease Diagnosis.7.6 Microbial Cells.7.7 Plants.7.8 Clinical Chemistry.References.8. Industrial and Environmental Applications.8.1 Introduction.8.2 Pharmaceutical Applications.8.3 Food Science.8.4 Agricultural Applications.8.5 Pulp and Paper Industries.8.6 Paint Industry.8.7 Environmental Applications.References.Responses to Self-Assessment Questions.Bibliography.Glossary of Terms.SI Units and Physical Constants.Periodic Table.Index.

2,802 citations


Cites background from "The Handbook of Infrared and Raman ..."

  • ...The programs work by hunting through stored data to match intensities and wavenumbers of absorption bands [3]....

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  • ...It is possible to combine an infrared spectrometer with a microscope facility in order to study very small samples [3–6]....

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  • ...For further reference, there is a range of books and book chapters available which provide an overview of the theory behind infrared spectroscopy [3–7]....

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Journal ArticleDOI
01 Jan 1999-Carbon
TL;DR: In this paper, a deconvolution method is proposed to analyze the TPD spectra, allowing for the quantitative determination of the amount of each functional group on the surface. But the deconvolutions are not suitable for the analysis of a large number of functional groups.

2,674 citations

Journal ArticleDOI
TL;DR: A collection of Raman spectra of biomolecules that can serve as references for the interpretation of biological materials is presented in this paper, where the most important components present in a cell are included.
Abstract: Raman spectra of biological materials are very complex, because they consist of signals from all molecules present in cells. In order to obtain chemical information from these spectra, it is necessary to know the Raman patterns of the possible components of a cell. In this paper, we present a collection of Raman spectra of biomolecules that can serve as references for the interpretation of Raman spectra of biological materials. We included the most important components present in a cell: (1) DNA and RNA bases (adenine, cytosine, guanine, thymine and uracil), (2) amino acids (glycine, L-alanine, L-valine, L-serine, L-glutamic acid, L-arginine, L-phenylalanine, L-tyrosine, L-tryptophan, L-histidine, L-proline), (3) fatty acids and fats (lauric acid, myristic acid, palmitic acid, stearic acid, 12-methyltetradecanoic acid, 13-methylmyristic acid, 14-methylpentadecanoic acid, 14-methylhexadecanoic acid, 15-methylpalmitic acid, oleic acid, vaccenic acid, glycerol, triolein, trilinolein, trilinolenin), (4) saccharides (β-D-glucose, lactose, cellulose, D-(+)-dextrose, D-(+)-trehalose, amylose, amylopectine, D-(+)-mannose, D-(+)-fucose, D-(−)-arabinose, D-(+)-xylose, D-(−)-fructose, D-(+)-galactosamine, N-acetyl-D-glucosamine, chitin), (5) primary metabolites (citric acid, succinic acid, fumarate, malic acid, pyruvate, phosphoenolpyruvate, coenzyme A, acetyl coenzyme A, acetoacetate, D-fructose-6-phosphate) and (6) others (β-carotene, ascorbic acid, riboflavin, glutathione). Examples of Raman spectra of bacteria and fungal spores are shown, together with band assignments to the reference products. Copyright © 2007 John Wiley & Sons, Ltd.

1,157 citations