Spectral Data Base System

Several excellent print collections of spectra are available but are beyond the budgets of most col lege libraries Fortunately vast numbers of NMR IR and mass spectra are freely accessible via the Spectral Data Base System (SDBS) maintained by the Japanese National Institute of Advanced Industrial Science and Technology at... 

Integrated Spectral Data Base System for Organic Compounds... 

National Institute of Standards and Technology (NIST). This site includes gas phase infrared spectra and mass spectral data, http //webbook.nist.gov/chemistrv/ Integrated Spectral Data Base System for Organic Compounds, National Institute of Materials and Chemical Research, Tsukuba, Ibaraki 305-8565, Japan. This database includes infrared, mass spectra, and NMR data (proton and carbon-13). 

While most spectral libraries are fee-based, the Web offers a few free options for locating chemical spectra as well. One is the NIST Chemistry WebBook (webbook.nist.gov/chemistry), maintained by the National Institute of Standards and Technology. Another worthwhile free tool is the Integrated Spectral Data Base System for Organic Compounds (SDBS), maintained by the National Institute of Advanced Industrial Science and Technology in Japan (www.aist.go.jp/RIODB/ SDBS/menu-e.html). 

Another web-based integrated spectral data base. system for organic compounds (SDBS) was developed by the National Institute of Materials and Chemical Research of Tsukuba (Japan) [135]. This system includes six different types of spectra C NMR (ca. 11000 spectra), H NMR (ca. 13500 spectra), MS, IR, laser-Raman, and ESR (ca. 2000 spectra). The studies on the SDBS started already in early 1970. This system only... 

The following abbreviations are used d = doublet t = triplet q = quartet m = multiplet. Significant portions of the proton ( H) and carbon ( C) data are taken from the SDBS, Integrated Spectral Data Base System for Organic Compounds, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan (http //riodb01.ibase.aist.go.jp/sdbs/cgi-bin/direct frame top.cgi). The data shown are taken from Rao, N. S. Rao, G. B. Murthy, B. N. Das, M. M. Prabhakar, T. Lalitha, M. Spectrochim. Acta A, 2002,58, ITil. 

Confirmation for any of them could then be sought in the spectral data bases, the registry number being all that is necessary to locate and retrieve data. One can even speculate further to the day when synthetic pathways to any likely candidates could be designed by the computer system which could easily add the very practical touch of checking that any starting materials for such syntheses are commercially available at an appropriately low cost ... 

Instrument automation may be required to provide us with more powerful techniques of data analysis and data handling using statistical techniques that would be otherwise too time consuming to be practical or computer graphics to gain greater flexibility in data analysis. Small data base systems of spectral libraries can help address a problem of faster component identification. 

The equipment used for this work consisted of a Hewlett-Packard 5710A GC, with on-coluitm injection, directly coupled to a VG7070E medium resolution double-focusing mass spectrometer. The GC coluitm employed was a 60 m fused silica capillary colurrm coated with a cross-linked methyl silicone stationary phase, DB-1. The initial temperature of the colurrm was 30°C, and after 4 minutes, the temperature was linearly programmed at 8°C/min to 270°C, and held at this final temperature for 15 minutes. The mass spectrometer was operated in the electron impact (El) mode, and the mass range of 20-700u was scanned once a second. The mass spectrometer was linked to an Incos data system which stored the acqnired mass spectra, and allowed these to be compared to the EPA/NIH Mass Spectral Data Base to assist with the identification of compounds detected. 

Mass spectral studies have also been used more extensively. Soviet investigators at Tashkent in their mass spectral analyses of the Aconitum and Delphinium alkaloids have provided a mass spectral data base of great utility in the structure elucidation of new alkaloids with the lycoctonine skeleton. A study employing trimethylsilyl derivatives in a gas chromatograph-mass spectrometer system has also been reported. A brief review of mass spectral studies on diterpene alkaloids has appeared. ... 

Fe—Fe bond can be assigned structures 201 or 202 based on spectral data. The other product of this reaction is 193 (R = r-Bu), however, it is produced in minor amounts. Complexes 199 (R = R = r-Bu, R = Ph, R = r-Bu) were obtained. Reaction of 146 (M = Mo, R = Ph, R = R = Ft, R = r" = Me) with (benzyli-deneacetone)iron carbonyl gives rise to the bimetallic complex 200 (M = Mo), which reacts further with the free phosphole to form the bimetallic heteronuclear sandwich 203. The preferable coordination of the molybdenum atom to the dienic system of the second phosphole nucleus is rather unusual. The molybdenum atom is believed to have a greater tendency to coordinate via the trivalent phosphorus atom than via the dienic system. 

Mass spectral data on l-(arylsulfonyl)-l//-azepines have been amassed,73 and the fragmentation patterns of several 1-acyl-1//-azepines elucidated.61 For the latter systems, the base peaks correspond to the azatropylium cation (m/z 92). Loss of hydrogen cyanide to yield the cyclo-pentadienyl cation (m/z 65) has also been noted. 

H.J. Luinge, A knowledge-based system for structure analysis from infrared and mass spectral data. 

On the other hand, when latent variables instead of the original variables are used in inverse calibration then powerful methods of multivariate calibration arise which are frequently used in multispecies analysis and single species analysis in multispecies systems. These so-called soft modeling methods are based, like the P-matrix, on the inverse calibration model by which the analytical values are regressed on the spectral data ... 

The second new compound, pseudopterosin Y (2) was also purified a yellow gum. Its UV and IR spectra were identical to those of compound 1, indicating the presence of same n system and functional groups in 2. The HREIMS of 2 showed the M+ at m/z 516.2420 corresponding to the molecular formula A combination of H-, C-NMR, COSY, HSQC and HMBC spectral data revealed that compound 2 was C-3 acetyl derivative of compound 1. Based on these spectral data, stmcture 2 was assigned to this new compound. 

Recently, on-line FBRM, ATR-FTIR spectroscopy, Raman spectroscopy and PLS were used to moifitor a complex crystallization system a racemic free base of a given componnd and a chiral acid. The anthors first demonstrate that the diastereomeric composition can be estimated nsing Raman spectral data, slnrry density and temperature using a PLS model. Consequently the issne of on-line slurry density prediction, which is not readily available, arises. An additional PLS model was constructed that used the ATR-FTIR spectral data to infer slurry density. Slurry density as predicted in real-time via ATR-FTIR spectroscopy was fed into the aforementioned Raman, slurry density and temperatnre PLS model to yield a more accnrate estimate of the fractional solid composition of the two diastereomers. ... 

An example of CQV of the batch cultivation of a vaccine has been demonstrated, where univariate (temperature, dissolved oxygen, pH) as well as spectroscopic tools were used to develop process models. The measurements were used for a consistency analysis of the batch process, providing better process understanding which includes the understanding of the variations in the data. MSPC analysis of four batches of data was performed to monitor the batch trajectories, and indicated that one batch had a deviation in the pH. From the MSPC information, combined with calibration models for the composition of the process based on NIR spectral data, improved monitoring and control systems can be developed for the process, consistent with concept of CQV. The data from the univariate sensors and NIR were also fused for a global analysis of the process with a model comprised of all the measurements. 

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