У статті розглядається методика використання інформаційних технологій для вивчення явища ядерного магнітного резонансу і експериментальних методів спектроскопії ядерного магнітного резонансу.
The article deals with the technique of usage informational technologies for studying phenomenon of a nuclear magnetic resonance and an experimental method of spectroscopy of a nuclear magnetic resonance is considered. Nuclear magnetic resonance (NMR) is a physical phenomenon in which nuclei in a magnetic field absorb and reemit electromagnetic radiation. This energy is at a specific resonance frequency which depends on the strength of the magnetic field and the magnetic properties of the isotope of the atoms; in practical applications, the frequency is 60–1000 MHz. NMR allows the observation of specific quantum mechanical magnetic properties of the atomic nucleus. Many scientific techniques exploit NMR phenomena to study molecular physics, crystals, and noncrystalline materials through NMR spectroscopy. NMR is also routinely used in advanced medical imaging techniques, such as in magnetic resonance imaging (MRI). We will be taking a "classical" view of the behavior of the nucleus – that is, the behavior of a charged particle in a magnetic field. Imagine a nucleus (of spin 1/2) in a magnetic field. This nucleus is in the lower energy level (i.e. its magnetic moment does not oppose the applied field). The nucleus is spinning on its axis. In the presence of a magnetic field, this axis of rotation will precess around the magnetic field. There are many computer programs for NMR-spectroscopy. These programs have main goals: 1) To save a pedagogic function in teaching and learning NMR-spectroscopy; 2) To perform simulations of research NMR-spectra; 3) Measurement of rate constants by dynamic NMR line shape simulations; 4) Analysis of integration of overlapping peaks. MestReNova (Mnova) is Nuclear Magnetic Resonance and LC/GC/MS data processing, visualization, simulation, prediction, presentation and analysis software package . The handling of molecular structures within Mnova also allows the user to carry out spectral predictions.