From database-powered models to quantum chemistry: NMR data estimation in modern interdisciplinary researchThursday (29.09.2016) 12:30 - 12:33 Part of:
NMR spectroscopy is one of the most powerful non-destructive measurement methods, allowing to investigate the structure and dynamics of modern materials. NMR techniques offer a number of possible measurements, ranging from chemical shielding constants to diffusion rates, structural dynamics and 3-dimensional imaging with MRI techniques. All these parameters create a broad and interesting field for computational studies.
For NMR shielding constants and other data derived from NMR measurement, an array of computational methods is available, ranging from simple semi-empirical models based on experimental spectra databases, to “heavyweight” quantum chemical methods, which enable ab initio NMR parameters estimation with high accuracy. While the simple computational models help in the day-to-day work of organic chemists, facilitating the interpretation of complex NMR spectra; quantum-chemical computations enable to predict NMR parameters for more sophisticated systems and reveal subtle details of chemical structure.
Within this contribution, tools for prediction of NMR spectra and other NMR-derived data will be outlined, ranging from simple models to more refined quantum chemistry methods, with examples including chemical shits estimation for novel chiral organic systems, applicable for chiral polymer coatings or metal-organic framework (MOF) construction.