Modeling of NMR processing, toward efficient unattended processing of NMR experiments

Abstract

Many alternative processing techniques have recently been proposed in the literature. Most of these techniques rely on specific acquisition protocols as well as on specific data processing techniques, the need for an efficient versatile and expandable NMR processing tool would be a particularly timely addition to the modern NMR spectroscopy laboratory. The work presented here consists in a modeling of the various possible NMR data processing approaches. This modeling presents a common working frame for most of the modern acquisition/processing protocols. Two different data modeling approaches are presented, strong modeling and weak modeling, depending whether the system under study or the measurement is modeled. The emphasis is placed on the weak modeling approach. This modeling is implemented in a computer program developed in python and called NPK standing (standing for NMR Processing Kernel), organized in four logical layers (i) mathematical kernel; (ii) elementary actions; (iii) processing phases; (iv) processing strategies. This organisation, along with default values for most processing parameters allows the use of the program in an unattended manner, producing close to optimal spectra. Examples are shown for 1D and 2D processing, and liquid and solid NMR spectroscopy. NPK is available from the site: http://abcis.cbs.cnrs.fr/NPK.