Spectra spectrum, interpretation

Other methods consist of algorithms based on multivariate classification techniques or neural networks they are constructed for automatic recognition of structural properties from spectral data, or for simulation of spectra from structural properties [83]. Multivariate data analysis for spectrum interpretation is based on the characterization of spectra by a set of spectral features. A spectrum can be considered as a point in a multidimensional space with the coordinates defined by spectral features. Exploratory data analysis and cluster analysis are used to investigate the multidimensional space and to evaluate rules to distinguish structure classes. 

Neural networks have been applied to IR spectrum interpreting systems in many variations and applications. Anand [108] introduced a neural network approach to analyze the presence of amino acids in protein molecules with a reliability of nearly 90%. Robb and Munk [109] used a linear neural network model for interpreting IR spectra for routine analysis purposes, with a similar performance. Ehrentreich et al. [110] used a counterpropagation network based on a strategy of Novic and Zupan [111] to model the correlation of structures and IR spectra. Penchev and co-workers [112] compared three types of spectral features derived from IR peak tables for their ability to be used in automatic classification of IR spectra. 

The solvent chosen must dissolve the sample, yet be relatively transparent in the spectral region of interest. In order to avoid poor resolution and difficulties in spectrum interpretation, a solvent should not be employed for measurements that are near the wavelength of or are shorter than the wavelength of its ultraviolet cutoff, that is, the wavelength at which absorbance for the solvent alone approaches one absorbance unit. Ultraviolet cutoffs for solvents commonly used are given in Table 7.10. 

It is an intensely reactive and hygoscopic yellow-brown substance (m.p. 75-78°C) its volatility suggests a low molecular mass Mossbauer spectra indicate 6-coordinate gold while the Raman spectrum is interpreted in terms of cw-bridged octahedral units. In the gas phase at 170°C, it comprises dimers and trimers [29] (electron diffraction). 

The determination of the absolute configuration of a carotenoid is only possible by circular dichroism (CD) measurement. The spectrum interpretation can only be done by comparison with reference or model compounds with known chiralities. The sample requirement is as low as 5 to 50 pg, but CD facilities are not so commonly available. Buchecker and Noack reported experimental aspects and discussion of the relationships of carotenoid structures and CD spectra. 

M.E. Munk, M.S. Madison and E.W. Robb, Neural network models for infrared spectrum interpretation. Microchim. Acta, 2 (1991) 505-524. 

The approach enables facile identification of specific biomarkers and can establish the uniqueness of biomarkers. The biomarker spectrum is interpreted rather than matched or correlated. 

Robb EW, Munk ME (1990) A neural network approach to infrared spectrum interpretation. Mikrochim Acta [Wien] 1990/1 131... 

Wehrens R, Lucasius C, Buydens LMC, Kateman G (1993a) HIPS, a hybrid self-adapting expert system for NMR spectrum interpretation using genetic algorithms. Anal Chim Acta 277 313... 

The current protot3rpe system includes three Expert modules, the IR Expert, the STIRS Expert, and the Human. All modules are written in Lisp. The IR Expert is a rule-based infrared interpreter which we have developed. The STIRS Expert is an interface to the STIRS program, a pattern-matching mass spectrum interpreter developed by McLafferty and coworkers at Cornell University, which is written in Fortran. () ) The interface translates the output of STIRS into a form palatable to our program, and handles the message-passing protocol required by the Controller. The Human module controls communication with the user. It allows user-supplied elemental or substructure information to influence the course of the analysis. The power of... 

In many cases, the results of the IR and mass spectrum interpretation are sufficient to allow a complete molecular structure to be deduced. In preliminary tests on 12 unknown compounds of molecular weight 100-200, the author, using the results reported by the program but without access to the original spectra, was able to correctly identify 9 of the unknowns. 

This point is borne out by the structure of tris indenyl samarium (5d). An earlier report of the nmr spectrum was interpreted as evidence of covalent bonding in the tetrahydrofuran adduct of samarium triindenide 66). Indenyl anion. 

TMB (42) was first generated by Roth el al. by photochemical decarbonyla-tion of the ketone 44 in a low-temperature matrix. This preparation was intensely colored, with a main transition at 490 nm and several subsidiary absorptions. Earlier ti-CI quantum chemical computations had predicted ultraviolet-visible (UV-vis) is transitions for the singlet and triplet states of TMB, and the bands observed by the Roth group were in better agreement with the predictions for the triplet. The preparation also showed a narrow ESR spectrum interpreted by the authors as that of a triplet species with D = 0.0042 cm and E = 0.0009 cm, which gave a linear Curie plot. The authors assumed that the carriers of the UV-vis and ESR spectra were the same species, namely, triplet TMB. They concluded that TMB is a ground-state triplet, contrary to the disjoint theory and to the computational results described above. 

The detailed examination of the spectra of simple molecules is a direct source to determine the characteristic NIR frequencies for selected vibration modes. For qualitative and quantitative analyses there is the requirement to interpret as much as possible the NIR spectrum. Although interpretation of spectra in a manner analogous to MIR is not conceivable, attempts exist to define and categorize observed NIR frequencies. Examples of reported frequencies for aliphatic hydrocarbons are given in the following list ... 

After the sample had been heated to —95°C. for 10 minutes, the spectrum was quantitatively transferred into a singlet with the line width of 17 gauss (Affmsi). This spectrum was interpreted as caused by polyenylic radicals (III). After heating to room temperature, no detectable concentration of radicals was found. In another study (4, 5) of ultraviolet-irradiated polyethylene, the sextet spectrum was also observed together with a singlet. The singlet spectrum was ascribed to peroxy radicals formed by the air present in the sample tube. 

On warming to — 30°C., the spectrum of the crystalline samples changed to a sextet with a doublet substructure. By analogy with poly( 1-butene) this spectrum was interpreted as arising from allylic radicals (XXII), but this assignment needs further justification. 

The technique of IR-ATR spectroscopy is easy to apply in reaction analysis as no sampling or flow-through cells are required. As most organic compounds are infrared-active, the technique is useful for many reaction types. However, there are some matters that should always be kept in mind when the reaction s IR-ATR spectrum is interpreted. 

Fig. 2. First derivative of the electron spin resonance spectrum of Me2C OH radicals, together with an integrated spectrum and interpretation.

The H-NMR spectrum of the 1 1 adduct of f-butyllithium-d9 and normal butadiene (DP = 1) in benzene was characterized by complex resonances this spectrum was interpreted by these authors as being a mixture of cis- and trans-1,4-addition products. 

Third, assuming that the required information can be automatically gathered, it will be necessary to use an expert system approach to automate the data interpretation. Such a system will likely employ both library searching and IR and MS spectrum interpreters to analyze the data, making use of intermediate results from one approach to guide the others in the same way that a human operator interprets all of the data in concert. Combined library search approaches have been demonstrated (16,17,T9) and a variety of MS (20-22) and IR (23-25) spectrum interpreters are available. Several laboratories have begun to address the need for a combined expert system (16,22). It seems clear that some of the most useful new developments in GC/IR/MS technology will appear in this area. 

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