Combined Determination of Specific Surface Area and Surface Charge Properties of Charged Particles from a Single Experiment

2011 ◽  
Vol 75 (6) ◽  
pp. 2128-2135 ◽  
Author(s):  
Hang Li ◽  
Jie Hou ◽  
Xinmin Liu ◽  
Rui Li ◽  
Hualin Zhu ◽  
...  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Asif Hussain ◽  
Jiebing Li ◽  
Jun Wang ◽  
Fei Xue ◽  
Yundan Chen ◽  
...  

Herein we demonstrate first report on fabrication, characterization, and adsorptive appraisal of graphene/cellulose nanofibers (GO/CNFs) monolith for methylene blue (MB) dye. Series of hybrid monolith (GO/CNFs) were assembled via urea assisted self-assembly method. Hybrid materials were characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction patterns, Raman spectroscopy, elemental analysis, thermogravimetric curve analysis, specific surface area, surface charge density measurement, and compressional mechanical analysis. It was proposed that strong chemical interaction (mainly hydrogen bonding) was responsible for the formation of hybrid assembly. GO/CNFs monolith showed mechanically robust architecture with tunable pore structure and surface properties. GO/CNFs adsorbent could completely remove trace to moderate concentrations of MB dye and follow pseudo-second-order kinetics model. Adsorption isotherm behaviors were found in the following order: Langmuir isotherm > Freundlich isotherm > Temkin isotherm model. Maximum adsorption capacity of 227.27 mg g−1 was achieved which is much higher than reported graphene based monoliths and magnetic adsorbent. Incorporation of nanocellulose follows exponential relationship with dye uptake capacities. High surface charge density and specific surface area were main dye adsorptive mechanism. Regeneration and recycling efficiency was achieved up to four consecutive cycles with cost-effective recollection and zero recontamination of treated water.


2006 ◽  
Vol 52 (179) ◽  
pp. 558-564 ◽  
Author(s):  
Margret Matzl ◽  
Martin Schneebeli

AbstractThe specific surface area (SSA) is considered an essential microstructural parameter for the characterization of snow. Photography in the near-infrared (NIR) spectrum is sensitive to the SSA. We calculated the snow reflectance from calibrated NIR images of snow-pit walls and measured the SSA of samples obtained at the same locations. This new method is used to map the snow stratigraphy. The correlation between reflectance and SSA was found to be 90%. Calibrated NIR photography allows quantitative determination of SSA and its spatial variation in a snow profile in two dimensions within an uncertainty of 15%. In an image covering 0.5–1.0 m2, even layers of 1mm thickness can be documented and measured. Spatial maps of SSA are an important tool in initializing and validating physical and chemical models of the snowpack.


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