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Permeability characterizes how saturating fluids penetrate and flow through porous rocks. It is an important quantity that can be used to model the behavior of reservoir rocks and to optimize underground resource exploration. Permeability can be characterized via nuclear magnetic resonance (NMR) relaxometry techniques by utilizing the yielded pore volume and pore length scales. However, for heterogeneous rocks a simple estimation of a permeability value based on the existing models may be inadequate. In this work, a new relaxation technique is applied to rock cores in conjunction with magnetic resonance imaging schemes. This allows the interior structures of studied rock cores to be recorded along a chosen sample axis. Based on the spatially resolved relaxation maps obtained, a factor of local connectivity was introduced for the first time and calculated by using the correlation degree between adjacent relaxation time distributions originating from neighboring image slices. Consequently, a permeability profile was estimated by consecutively considering the local porosity, the spatially resolved relaxation time distribution, and the connectivity factor. Experimental results prove that permeability profiles trace the heterogeneity of rock samples. Furthermore, averaged permeabilities of rock cores were calculated while taking into account local connectivity. The values obtained approach better to brine‐permeability measurements as compared to data processing disregarding connectivity. Key Points: A rapid, nondestructive method was proposed to estimate rock permeabilityRock heterogeneity can be visualized by using obtained permeability profilesThe obtained permeability values from the proposed technique were comparable to conventional approach [ABSTRACT FROM AUTHOR]

Complex materials are ubiquitous in science, engineering and nature. One important parameter for characterising their morphology is the degree of anisotropy. Magnetic resonance imaging offers non-invasive methods for quantitative measurements of the materials anisotropy, most commonly via diffusion tensor imaging and the subsequent extraction of the spatially resolved fractional anisotropy (FA) value. Here, we propose an alternative way of determining the FA as a sample average for cases where spatially resolved methods are not needed or not applicable. It is based on a particular diffusion-diffusion correlation spectroscopy protocol, allowing for the extraction of the mean (i.e. sample averaged) FA value. We demonstrate that mean FA values obtained from three anisotropic biological tissues are consistent with those extracted using diffusion tensor imaging. Moreover, we show that differences of mean FA values in healthy and tumour-bearing mouse brains allow to distinguish these tissue types. We anticipate that the proposed method will be beneficial in the wider context of medical and material science. [ABSTRACT FROM AUTHOR]

Iron nanoparticles are highly-effective magnetic nanoparticles for T 2 magnetic resonance imaging (MRI). However, the stability of their magnetic properties is dependent on good protection of the iron core from oxidation in aqueous media. Here we report the synthesis of custom-synthesized phosphonate-grafted polyelectrolytes (PolyM3) of various chain lengths, for efficient coating of iron nanoparticles with a native iron oxide shell. The size of the nanoparticle-polyelectrolyte assemblies was investigated by transmission electron microscopy and dynamic light scattering, while surface attachment was confirmed by Fourier transform infrared spectroscopy. Low cytotoxicity was observed for each of the nanoparticle-polyelectrolyte (“Fe-PolyM3”) assemblies, with good cell viability (>80%) remaining up to 100 μg mL −1 Fe in HeLa cells. When applied in T 2 -weighted MRI, corresponding T 2 relaxivities ( r 2 ) of the Fe-PolyM3 assemblies were found to be dependent on the chain length of the polyelectrolyte. A significant increase in contrast was observed when polyelectrolyte chain length was increased from 6 to 65 repeating units, implying a critical chain length required for stabilization of the α-Fe nanoparticle core. [ABSTRACT FROM AUTHOR]