2013
DOI: 10.1016/j.memsci.2012.11.049
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Effect of temperature-dependent microstructure evolution on pore wetting in PTFE membranes under membrane distillation conditions

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Cited by 165 publications
(75 citation statements)
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References 26 publications
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“…The increase in the average pore size may be due to the further decrease in the membrane thickness from 39 µm to 37 µm, which might be caused by the release of internal stress generated during heat-pressing; the other possible cause could be the supplementary merging of the crystalline phase of the PVDF which was converted from the amorphous phase during annealing [30]. The results were consistent with the study of Saffarini et al, as it was found that an increase in the annealing temperature would lead to an increase in the average pore size of the membranes [35]. Further annealing for another day led to a greater decrease in the range of the pore diameter and a sharp peak appeared, although the average mean pore size was further slightly increased to 1.3 µm (which was same as that of the neat membrane).…”
Section: Improvement Of Membrane Propertiessupporting
confidence: 89%
See 1 more Smart Citation
“…The increase in the average pore size may be due to the further decrease in the membrane thickness from 39 µm to 37 µm, which might be caused by the release of internal stress generated during heat-pressing; the other possible cause could be the supplementary merging of the crystalline phase of the PVDF which was converted from the amorphous phase during annealing [30]. The results were consistent with the study of Saffarini et al, as it was found that an increase in the annealing temperature would lead to an increase in the average pore size of the membranes [35]. Further annealing for another day led to a greater decrease in the range of the pore diameter and a sharp peak appeared, although the average mean pore size was further slightly increased to 1.3 µm (which was same as that of the neat membrane).…”
Section: Improvement Of Membrane Propertiessupporting
confidence: 89%
“…The existence of the α phase PVDF can increase the liquid entry pressure and, hence, the wetting resistance, contributing to better long-term MD performance. Saffarini et al stated that annealing could also affect the microstructure evolution [35], which benefits the long-term MD operation as well. By increasing the crystallinity and releasing the internal stresses caused by the heat-pressing, the thermal stability of the membrane could be improved, preventing the LEP from dropping rapidly owing to distortion at a high feed temperature.…”
Section: Increased Crystallinity and Appearance Of α Phase After Annementioning
confidence: 99%
“…Although wetting prevention in MD is the main process requirement, it has not been comprehensively studied and relatively few investigations have attempted to solve the wetting problems in MD membranes [12][13][14][15][16][17][18][19][20]. Some authors have investigated the improvement of hydrophobic properties of membranes employing novel materials or applying surface modification through manipulating surface chemistry and surface geometry by nanoparticle coating and surface fluorination [21][22][23][24][25][26][27].…”
Section: Introductionmentioning
confidence: 99%
“…Traditionally, stretched membranes (e.g., PTFE) with small curvature radius were assigned B values of 0.5-0.6 or even smaller (0.4-0.46) [12]. According to this model, two membranes, X and Y, with similar CA and r max , but with X having round pores and Y having stretched (i.e., more elliptically shaped) pores, will have different LEP values.…”
Section: Introductionmentioning
confidence: 99%
“…There is also lack of information as to how to evaluate the membrane characteristics in order to apply the models and, in general, how the different pore structures may affect the LEP. There is also the common notion that LEP should be determined experimentally for each particular membrane rather than trusting the predicted values, as several researchers reported wetting to occur at lower pressures than the LEP values predicted by these models [12].…”
Section: Introductionmentioning
confidence: 99%