Nuclear magnetic resonance predicting spectra

Certain functional groups in a molecule (e.g., hydroxyl, carbonyl, and amine) absorb IR radiation and exhibit absorption bands at characteristic frequencies regions regardless of the structure of the rest of the molecule. These bands are termed group frequencies. They are predictable and allow the analyst to deduce important structural information about an unknown molecule. An IR spectrum can be rapidly recorded for any phase, i.e., solid, liquid, or vapor. By coupling IR spectroscopy with other analytical techniques such as nuclear magnetic resonance (NMR)... 

The selection rules help to predict the probability of a transition but are not always strictly followed. If the transition obeys the rules it is allowed, otherwise it is forbidden. A molecule can become excited in a variety of ways, corresponding to absorption in different regions of the spectrum. Thus certain properties of the radiation that emerges from the sample are measured. The fraction of the incident radiation absorbed or dissipated by the sample is measured in optical (ultraviolet and visible) absorption spectroscopy and some modes of nuclear magnetic resonance spectrometry (NMR). Because the relative positions of the energy levels depend characteristically on the molecular structure, absorption spectra provide subtle tools for structural investigation. 

Part Nuclear Magnetic Resonance Spectroscopy by W. Robien focuses on structure elucidation of organic compounds. Spectra similarity searches, spectrum prediction (from a given chemical structure), recognition of substructures and automatic isomer generation are the main topics they are still areas of scientific research in computer-assisted structure elucidation. 

Molecular dynamics attempts to solve the dynamically evolving ensemble of molecules given the interactions between molecules. The form of the forces between molecules or atoms, the number of interactions (i.e., two- or three-body interactions), and the number of molecules that can be tackled by the program determine the success of the model. Molecular dynamics simulations can predict the internal energy, heat capacity, viscosity, and infrared spectrum of the studied compound and form an integral part in the determination and refinement of structures from X-ray crystallography or nuclear magnetic resonance (NMR) experiments. 

Hgure 6 The 90 MHz methyl spectrum of atactic polypropylene in 1,2,4-trichlorobenzene at 100°. Empirical shift predictions for different stereoisomers reflecting the meso (m) or racemic (r) relative orientation of neighboring methyl groups. (Reprinted with permissbn from Schilling FC and Tonelli AE (1980) Carbon-13 nuclear magnetic resonance of atactic polypropylene. Macromolecules 13 270 American Chemical Society.)... 

Nuclear magnetic resonance (NMR) line width studies of crystalline polymers are based on the work of Wilson and Pake [102], This method was, however, unsuccessful due to the rather arbitrary decomposition procedures used, which yielded a crystalline fraction that was not in agreement with crystallinity results obtained by the X-ray method. To overcome this difficulty Bergmann [103-105] decomposed the spectrum into three components and this resulted in an excellent agreement between NMR and X-ray crystallinities. Unfortunately, with this method it was not possible to prove the existence of the two amorphous components of the polymer examined. Also, the two amorphous mobilities could not be predicted theoretically. Bergmann [106] succeeded eventually, as discussed next, in improving the separation procedure by finding more suitable line widths for the crystalline and amorphous components of the polymer. In this procedure a new method was evolved for the determination of the crystalline component and of the amorphous component based on a distribution of correlation times, instead of the two discrete correlation times as used in earlier work [103-105],... 

CONTEXT Once we ve solved a Schrodinger equation to get the wavefunction for the electrons in an atom or molecule, we can calculate the distribution of the electrons. This tells us, for example, how much charge from the electron is at each point in the system, allowing us to predict dipole moments or nuclear magnetic resonance spectra (such as the spectrum below more on this topic in Section 5.5). In this example, we show how the wavefunction for a 2p electron, if properly normalized, can tell us how much electron density lies close to the plane through the middle of the orbital. 

Nuclear magnetic resonance (NMR) spectroscopy is the most informative analytical technique and is widely applied in combinatorial chemistry. However, an automated interpretation of the NMR spectral results is difficult (3,4). Usually the interpretation can be supported by use of spectrum calculation (5-18) and structure generator programs (8,12,18-21). Automated structure validation methods rely on NMR signal comparison using substructure/ subspectra correlated databases or shift prediction methods (8,15,22,23). We have recently introduced a novel NMR method called AutoDROP (Automated Definition and Recognition of Patterns) to rapidly analyze compounds libraries (24-29). The method is based on experimental data obtained from the measured ID or 2D iH,i C correlated (HSQC) spectra. 

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