Measurement of pore sized microporous-mesoporous materials by time-domain nuclear magnetic resonance

Abstract

Time-domain nuclear magnetic resonance (TD NMR) technology has been used for pore detection in porous materials for a long time, but there are few pore detection methods for microporous-mesoporous materials. The surface of different materials is obtained by pore detection of known pore materials. Relaxation rate, which obtains aperture information, has an important practical significance for the application of time-domain NMR technology in the characterization of porous materials. In this study, the T2 peaks of pores of known pore size materials, namely zeolite molecular sieves (0.3 nm and 1 nm) and anodized aluminum porous membranes (30 nm and 90 nm), were used to calculate the pore surface relaxation of zeolite molecular sieve with 0.3 nm pore size and 1 nm pore size. The ratio of the rate of the surface is 3.379; the ratio of the pore surface relaxation ratio of the 30 nm and 90 nm apertures of the anodized aluminum porous film is 3.031. This result is very close to the pore size ratio, indicating that the surface relaxation rate of the same material is directly related to the pore size, while the T2 peak can qualitatively measure the pore size.

Advances in Characterizing Gas Hydrate Formation in Sediments with NMR Transverse Relaxation Time

“…where S V is the surface-to-volume ratio of the pore, ρ is the transverse surface relaxivity, F S stands for the geometric shape factor of pores (3 for spherical, 2 for cylindrical, and 1 for grooved), and r is the pore radius [90,91].…”

Characterization of Macroporous Materials

“…Although MRI is able to quantify the internal space of the measured substance, its applicability is limited by two aspects. First, the resolution of MRI imaging cannot achieve the standard that can be effectively utilized by image analysis software at this stage (Zhao et al 2020). But for imaging of foam structure, 3D image processing algorithm and an image processing software package called FoamView were developed specifically to extract structural information from 3D foam images (Hertel et al 2013).…”

“…But for imaging of foam structure, 3D image processing algorithm and an image processing software package called FoamView were developed specifically to extract structural information from 3D foam images (Hertel et al 2013). Second, the water content of the substance to be tested has certain requirements and there are limitations in dynamically monitoring the change of material moisture (Zhao et al 2020). These drawbacks limit the application of this technique in the characterization of porous materials.…”

“…Consequently, the last few decades saw emergence of more accurate pore characterization methods better known as three-dimensional (3D) imagining techniques. These include computerized X-ray tomography, 3D electron tomography (3DET), dualbeam electron microscopy and magnetic resonance imaging (Zhao et al 2020). Their outstanding advantages for characterization of macroporous materials are outlined in Fig.…”