## Description

Diffusion-ordered spectroscopy experiments in which existing delays in a parent pulse sequence are used for diffusion encoding – iDOSY experiments – are potentially attractive because of their simplicity and sensitivity. However the calculation of diffusional attenuation in Zangger-Sterk pure shift iDOSY experiments is a very difficult problem to attack analytically, and is more easily approached numerically. Numerical simulations show that for typical experimental conditions, the dependence of diffusional attenuation on diffusion-encoding gradient amplitude is well represented by a shifted Gaussian function. The shift in gradient can be calculated analytically for the limiting case where the selective pulse is replaced by a hard 180° pulse at its midpoint; numerical simulations show that the effect of using different shapes of selective pulse is to scale down this limiting gradient shift by a constant factor that depends on the pulse shape used. The practical consequence is that under the experimental conditions appropriate for small molecules, the pure shift iDOSY method should allow good diffusion coefficient measurements to be made if appropriate allowance is made for the change in effective diffusion-encoding gradient. Parallel sets of numerical simulations and experiments are presented, and a practical application of a Zangger-Sterk pure shift iDOSY experiment to a simple test mixture is illustrated.

Files provided:

Data

====

Figs. 2 to 4 and S1 to S4

Figure 6a Oneshot-45

Figure 6b ZS-iDOSY

Code

====

Mathematica code

MGC analysis and figures.nb

Process simulated / experimental data for figs. 2 to 5 and S1 to S4

Matlab code

gradient_shift_analysis.m

gradient_shift_test.m

idosyzs.m

Simulate data for figs. 2 to 4 and S1 to S4

Sequence code

gmmgc

Fig. 1c, for figs. 2 to 4 and S1 to S4

kp_ifZS-iDOSY_03

Fig. 1a, for fig. 6b ZS-iDOSY

kp_oneshot45_02

Fig. 1d, for fig. 6a Oneshot-45

N.B. The definition of d20 has been corrected to match the diffusion delay

in these sequences, correcting errors in the sequences used for acquisition

of, and found in, the data directories “Figs. 2 to 4 and S1 to S4” and “Figure

6b ZS-iDOSY”

VnmrJ macros

GMgshift

Calculate and apply gradient value shift

GMPKBrukerNUG

Calculate and apply amplitude and diffusion coefficient correction

for gradient non-uniformity

GMprocPK22

Produce Fig. 6a

GMprocPK1002

Produce Fig. 6b

Files provided:

Data

====

Figs. 2 to 4 and S1 to S4

Figure 6a Oneshot-45

Figure 6b ZS-iDOSY

Code

====

Mathematica code

MGC analysis and figures.nb

Process simulated / experimental data for figs. 2 to 5 and S1 to S4

Matlab code

gradient_shift_analysis.m

gradient_shift_test.m

idosyzs.m

Simulate data for figs. 2 to 4 and S1 to S4

Sequence code

gmmgc

Fig. 1c, for figs. 2 to 4 and S1 to S4

kp_ifZS-iDOSY_03

Fig. 1a, for fig. 6b ZS-iDOSY

kp_oneshot45_02

Fig. 1d, for fig. 6a Oneshot-45

N.B. The definition of d20 has been corrected to match the diffusion delay

in these sequences, correcting errors in the sequences used for acquisition

of, and found in, the data directories “Figs. 2 to 4 and S1 to S4” and “Figure

6b ZS-iDOSY”

VnmrJ macros

GMgshift

Calculate and apply gradient value shift

GMPKBrukerNUG

Calculate and apply amplitude and diffusion coefficient correction

for gradient non-uniformity

GMprocPK22

Produce Fig. 6a

GMprocPK1002

Produce Fig. 6b

Date made available | 23 Nov 2018 |
---|---|

Publisher | Mendeley Data |