Diffusion Spectrum of Polymer Melt Measured by Varying Magnetic Field Gradient Pulse Width in PGSE NMR

The translational motion of polymers is a complex process and has a big impact on polymer structure and chemical reactivity. The process can be described by the segment velocity autocorrelation function or its diffusion spectrum, which exhibit several characteristic features depending on the observational time scale—from the Brownian delta function on a large time scale, to complex details in a very short range. Several stepwise, more-complex models of translational dynamics thus exist—from the Rouse regime over reptation motion to a combination of reptation and tube-Rouse motion. Accordingly, different methods of measurement are applicable, from neutron scattering for very short times to optical methods for very long times. In the intermediate regime, nuclear magnetic resonance (NMR) is applicable—for microseconds, relaxometry, and for milliseconds, diffusometry. We used a variation of the established diffusometric method of pulsed gradient spin-echo NMR to measure the diffusion spectrum of a linear polyethylene melt by varying the gradient pulse width. We were able to determine the characteristic relaxation time of the first mode of the tube-Rouse motion. This result is a deviation from a Rouse model of polymer chain displacement at the crossover from a square-root to linear time dependence, indicating a new long-term diffusion regime in which the dynamics of the tube are also described by the Rouse model.

Sparse Correlated Diffusion Imaging: A New Computational Diffusion MRI Modality for Prostate Cancer Detection

Diffusion weighted imaging (DWI) is a promising magnetic resonanceimaging (MRI) modality with wide applications in diagnosisof different types of diseases such as prostate cancer. DWI providesa large amount of imaging data which often makes it difficultto interpret accurately, mainly due to the fact that much of informationin diffusion imaging cannot be deciphered by human expertsalone. Computational diffusion MRI (CD-MRI) aims to leveragecomputational means to generate imagery from diffusion signalswhich are easier to interpret by human experts. Recently, anew CD-MRI modality called correlated diffusion imaging (CDI) hasbeen proposed which takes advantage of the joint correlation of diffusionsignal attenuation across multiple gradient pulse strengthsand timings to improve the separability of cancerous and healthytissues. In this paper, we propose a new CD-MRI modality calledSparse CDI (sCDI) where an optimally sparse subset of diffusionsignals contributes to the formation of the final diffusion signal leadingto further separation of cancerous and healthy tissue in prostategland compared to CDI and conventional DWI.