The Laplace NMR (LNMR) relies on phenomena like relaxation and diffusion. LNMR provides detailed information about the dynamics of molecules as well as chemical information complementary to conventional NMR spectra. Furthermore, as it is based on the use of the spin echoes, the experiment can be carried out even in the very inhomogeneous magnetic fields. Additionally, the LNMR method allows to achieve resolution in systems where chemical shift provides no information.
Therefore, Laplace NMR is a versatile tool for the analysis of heterogeneous materials where the chemical resolution used in conventional NMR is not achievable. The relaxation and diffusion data can provide information about surface interactions, pore structure, chemical exchange, and many others.
Analogically to FNMR, LNMR can provide much richer information about a measured system by utilizing a multidimensional approach. Similarly to conventional NMR, multidimensional LNMR provides more information in a single experiment but at the cost of longer experimental time, as each indirectly measured point requires the repetition of the entire pulse sequence.
This problem excludes the classically acquired 2D LNMR spectra from usage for studies of dynamic or time-dependent processes. Therefore, there is a need for a novel, faster approach.
One of the methods proposed to shorten the acquisition time of a multidimensional NMR experiment is Ultra-Fast NMR (UF NMR)
The method utilizes the idea of spatial encoding to measure all the indirect dimension in single-scan. The method was first introduced to multidimensional Laplace NMR by the group of prof. Ville Telkki (see: “Ultrafast methods for relaxation and diffusion”)
The complementary method to UF-LNMR is Time-Resolved Laplace NMR (TR-LNMR) concept based on Time-Resolved Non-Uniform Sampling (TR-NUS) (also known as a Moving Frame). The idea is based on the NUS acquisition of the spectra with an extended over-sampled NUS scheme of indirect dimension and later division of the data into overlapping subsets (frames) and reconstructs them. The resulting set of spectra allows for a good temporal resolution as each subset highly overlaps with previous in the reaction-time dimension.
The idea was also adapted for diffusion-based reaction monitoring utilizing the concept of permuted DOSY (p-DOSY). (see: “Monitoring polydispersity by NMR diffusometry with tailored norm regularisation and moving-frame processing”, “Time-Resolved Diffusion NMR Measurements for Transient Processes” )
In our research we utilize both mentioned methods to study time dependent processes like:
Parahydrogen based hyperpolarization
The reasearch is supported by the OPUS grant for National Science Centre, Poland titled: Fast Laplace NMR methods for time-dependent processes analysis