2022
DOI: 10.1039/d1ra08042c
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High-permeability vacuum membrane distillation utilizing mechanically compressed carbon nanotube membranes

Abstract: High-permeable vacuum membrane distillation by applying vertically aligned carbon nanotube for the first time.

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Cited by 8 publications
(5 citation statements)
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“…However, other models such as the Hertz model cannot be used as we have observed adhesion (∼15 nN) between the probe and the sample, and the JKR model is applicable to soft samples with high adhesion, where significant deformation occurs at the contact zone during pull-off which is not the case in our samples. Moreover, there are other parameters such as areal density of VACNTs in the range of 200−400 CNT/μm 2 , 29 and we assume that the VACNTs have uniform structure in the microscale, and the gap between the CNTs can be ignored as it is nearly 5−10 nm.…”
Section: Resultsmentioning
confidence: 99%
“…However, other models such as the Hertz model cannot be used as we have observed adhesion (∼15 nN) between the probe and the sample, and the JKR model is applicable to soft samples with high adhesion, where significant deformation occurs at the contact zone during pull-off which is not the case in our samples. Moreover, there are other parameters such as areal density of VACNTs in the range of 200−400 CNT/μm 2 , 29 and we assume that the VACNTs have uniform structure in the microscale, and the gap between the CNTs can be ignored as it is nearly 5−10 nm.…”
Section: Resultsmentioning
confidence: 99%
“…However, these membranes often encounter issues such as pore wetting and scaling during a prolonged operation. Consequently, intensive efforts have been made on the construction of biomimetically rough surfaces with nanomaterials (e.g., micro/nanoscale nanotubes/silica, SiC@graphene), aiming to improve the wetting and scaling resistance of the membrane. However, low-surface-energy substrates such as polydimethylsiloxane (PDMS), hexadecyltrimethoxysilane (HDTMS), and fluoroalkylsilane , are commonly utilized to modify the surface or as binders to immobilize nanomaterials. In this case, the micro/nanostructure of the membrane could be partially obscured, potentially reducing surface roughness, increasing mass transfer resistance, and consequently leading to a decrease in water vapor flux. Reported membranes made of nanomaterials without polymers, such as alumina-supported metal–organic framework (MOF) membranes and carbon nanotube membranes, can exhibit a good water flux. Inspired by the above, it is urgent to develop simple approaches using low-cost materials that can be combined with nanomaterials to prepare antiwetting membranes. …”
Section: Introductionmentioning
confidence: 99%
“…In this case, the micro/nanostructure of the membrane could be partially obscured, potentially reducing surface roughness, increasing mass transfer resistance, and consequently leading to a decrease in water vapor flux. 21−23 Reported membranes made of nanomaterials without polymers, such as aluminasupported metal−organic framework (MOF) membranes 24 and carbon nanotube membranes, 25 can exhibit a good water flux. Inspired by the above, it is urgent to develop simple approaches using low-cost materials that can be combined with nanomaterials to prepare antiwetting membranes.…”
Section: Introductionmentioning
confidence: 99%
“…Depending on the approach for vapor condensation, MD can be classified into four major configurations [ 13 ], including air gap membrane distillation (AGMD) [ 14 , 15 , 16 , 17 ], sweeping-gas membrane distillation (SGMD) [ 12 , 18 , 19 , 20 , 21 , 22 ], direct contact membrane distillation (DCMD) [ 12 , 23 , 24 , 25 , 26 , 27 ], and vacuum membrane distillation (VMD) [ 12 , 28 , 29 , 30 , 31 , 32 ]. Recently, a new MD configuration that combined the features of AGMD and DCMD processes was introduced and named water gap membrane distillation (WGMD) [ 33 , 34 , 35 ] or permeate gap membrane distillation (PGMD) [ 36 , 37 , 38 , 39 ], or liquid gap membrane distillation (LGMD) [ 40 , 41 , 42 , 43 ].…”
Section: Introductionmentioning
confidence: 99%