Nanofiltration membranes with narrowed pore size distribution via pore wall modification

2016 ◽  
Vol 52 (55) ◽  
pp. 8589-8592 ◽  
Author(s):  
Yong Du ◽  
Yan Lv ◽  
Wen-Ze Qiu ◽  
Jian Wu ◽  
Zhi-Kang Xu
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Pore Wall ◽  
Nanofiltration Membranes ◽  
Novel Method

A novel method has been proposed to modify the pore wall of nanofiltration membranes (NFMs) by filtrating molecules that are reactive to the NFMs, leading to narrowed pore size distribution.

Study of Structural Features of Porous TINI-Based Materials Produced by SHS and Sintering

2015 ◽  
Vol 1085 ◽  
pp. 430-435 ◽  
Author(s):  
Sergey G. Anikeev ◽  
Valentina N. Khodorenko ◽  
Oleg V. Kokorev ◽  
Timofey L. Chekalkin ◽  
Victor E. Gunter
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Pore Wall ◽  
Structural Features ◽  
Strength Properties ◽  
Material Strength ◽  
Powder Metallurgy Method ◽  
Sintered Alloy ◽  
Shs Method

Structural properties of porous TiNi-based materials produced by SHS method and sintering have been investigated. The material having different pore wall surface topography, porosity and pore size distribution was shown to be produced depending on the powder metallurgy method for porous TiNi-based alloy. All the materials having porosity of 55-70%, mean pore size 90-150 μm, as well as normal pore size distribution are most preferable. Ultimate strength and breaking point were determined to depend on porosity, pore size distribution, pore intersections and phase chemical composition of the material. Strength properties of the sintered alloy are twice as much compared to the SHS-produced ones due to homogeneity of its macrostructure, low chemical heterogeneity and TiNi3 precipitations strengthening the TiNi matrix.

A Novel Method for Analyzing Pore Size Distribution of Complex Geometry Shaped Porous Shale

2020 ◽  
Vol 1003 ◽  
pp. 134-143
Author(s):  
Yang Ming ◽  
Lin Mian
Keyword(s):  
Porous Media ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Complex Geometry ◽  
Capillary Condensation ◽  
Relative Pressure ◽  
Differential Function ◽  
Novel Method

This article proposes the differential BJH equation based on the principles of multilayer adsorption and capillary condensation, which was simplified by theoretical investigation and experiments. This work indicates that the differential function of isotherm and the differential function of pore size to relative pressure determine the pore size distribution of porous media. The differential BJH model can be used to explain the source of the false peak in pore size distribution and to calculate the pore size distribution of different shapes of pores in a porous media with a porous structure. It has an excellent application prospect in the characterization of complex pore structure represented by shale.

Fabrication of ultrahigh-molecular-weight polyethylene porous implant for bone application

2020 ◽  
Vol 40 (8) ◽  
pp. 685-692
Author(s):  
Beatriz Olalde ◽  
Ana Ayerdi-Izquierdo ◽  
Rubén Fernández ◽  
Nerea García-Urkia ◽  
Garbiñe Atorrasagasti ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Structural Integrity ◽  
Fibre Diameter ◽  
Pore Wall ◽  
Ultrahigh Molecular Weight Polyethylene ◽  
Salt Leaching ◽  
Ultrahigh Molecular Weight

AbstractPorous implants play a crucial role in allowing ingrowth of host connective tissue and thereby help in keeping the implant in its place. With the aim of mimicking the microstructure of natural extracellular matrix, ultrahigh-molecular-weight polyethylene (UHMWPE) porous samples with a desirable pore size distribution were developed by combining thermally induced phase separation and salt leaching techniques. The porous UHMWPE samples consisted of a nanofibrous UHMWPE matrix with a fibre diameter smaller than 500 nm, highly interconnected, with a controllable pore diameter from nanoscale to 300 µm. Moreover, a porous UHMWPE sample was also developed as a continuous and homogeneous coating onto the UHMWPE dense sample. The dense/porous UHMWPE sample supported human foetal osteoblast 1.19 cell line proliferation and differentiation, indicating the potential of porous UHMWPE with a desirable pore size distribution for bone application. An osseointegration model in the sheep revealed substantial bone formation within the pore layer at 12 weeks via SEM evaluation. Ingrown bone was more closely opposed to the pore wall when compared to the dense UHMWPE control. These results indicate that dense/porous UHMWPE could provide improved osseointegration while maintaining the structural integrity necessary for load-bearing orthopaedic application.

pyGAPS: A Python-Based Framework for Adsorption Isotherm Processing and Material Characterisation

2019 ◽  
Author(s):  
Paul Iacomi ◽  
Philip L. Llewellyn
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Surface Area ◽  
Isosteric Heat ◽  
Material Characterisation ◽  
Mixture Adsorption ◽  
Surface Energetics ◽  
Adsorption Processing ◽  
User Friendly

Material characterisation through adsorption is a widely-used laboratory technique. The isotherms obtained through volumetric or gravimetric experiments impart insight through their features but can also be analysed to determine material characteristics such as specific surface area, pore size distribution, surface energetics, or used for predicting mixture adsorption. The pyGAPS (python General Adsorption Processing Suite) framework was developed to address the need for high-throughput processing of such adsorption data, independent of the origin, while also being capable of presenting individual results in a user-friendly manner. It contains many common characterisation methods such as: BET and Langmuir surface area, t and α plots, pore size distribution calculations (BJH, Dollimore-Heal, Horvath-Kawazoe, DFT/NLDFT kernel fitting), isosteric heat calculations, IAST calculations, isotherm modelling and more, as well as the ability to import and store data from Excel, CSV, JSON and sqlite databases. In this work, a description of the capabilities of pyGAPS is presented. The code is then be used in two case studies: a routine characterisation of a UiO-66(Zr) sample and in the processing of an adsorption dataset of a commercial carbon (Takeda 5A) for applications in gas separation.

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