A remarkable increase in the adsorbed H2 amount: Influence of pore size distribution on the H2 adsorption capacity of Fe-BTC

2020 ◽  
Vol 45 (22) ◽  
pp. 12394-12407
Author(s):  
Aysu Yurduşen ◽  
Alp Yürüm ◽  
Yuda Yürüm
2016 ◽  
Vol 16 (5) ◽  
pp. 1297-1312 ◽  
Author(s):  
P. Dhanasekaran ◽  
P. M. Satya Sai ◽  
C. Anandbabu ◽  
K. K. Rajan

Sawdust of Artocarpus hirsutus impregnated with ferric hydroxide and activated alumina (SFAA) has been studied for defluoridation of water. This paper presents a detailed surface characterization of the adsorbent by studying pore size distribution and surface morphology. By combining the constituents in the right proportion, an adsorbent with a well-developed pore size distribution could be synthesized. The effects of various parameters on fluoride adsorption by SFAA are investigated. The adsorption capacity of SFAA is considerably higher than that of many adsorbents including activated alumina. More importantly, the adsorption capacity remains unchanged for the pH range of 1 to 9, which also makes it attractive for wastewater treatment. Besides a higher efficiency supported by the results of column studies, this adsorbent is economic as the sawdust constitutes 40% by weight of the total adsorbent. Kinetic studies indicate that fluoride adsorption on SFAA follows pseudo second-order model. Breakthrough adsorption capacity of SFAA is 1.21 mg/g, as compared with 0.41 mg/g for activated alumina.


2021 ◽  
Vol 21 (1) ◽  
pp. 515-528
Author(s):  
Baoxin Zhang ◽  
Xuehai Fu ◽  
Ze Deng ◽  
Ming Hao

A number of studies have used the nuclear magnetic resonance (NMR) technique to analyse pore characteristics and to discuss the influencing mechanisms of pore structure on methane adsorption. However, there are few studies on the dynamic characteristics of methane adsorption over time under the same temperature and pressure conditions, especially by using the cylindrical coal samples. In this study, scanning electron microscopy (SEM), mercury injection porosimetry (MIP), isothermal adsorption and NMR techniques were carried out on the four medium-high volatile bituminous coal samples from Shanxi Province, China. The simulation of methane adsorption was carried out with the custom adsorption instruments. Based on the experimental results and the Hodot pore size classification standard, the pore size distribution of the samples was analysed. In addition, the influence of nanopore structure and water content on methane adsorption was discussed. The results show that the T2 relaxation diagram of the four coal samples has a bimodal-triple peak, which reflects the complexity of the pore structure. Due to the clay minerals filling microfractures in the sample HX, the connectivity of the nanopores is reduced, in addition there is an obvious gap between the peaks in the relaxation diagram. After calculation of the T2 relaxation diagrams of the coals, the results can be converted into the pore size distribution map. The pores in the four samples are mainly composed of the macropores, followed by the mesopores, and the ratio of micropores and transition pores is relatively small. At Sw (saturated in 5% brine for 24 h) and Sir (dried at 333 K for 3 h) conditions, the adsorption capacity of the four samples presented a positive correlation with the effective porosity and the ratio of micropores, and presented a negative correlation with the ratio of mesopores, while the macropores contribute less to the adsorption. Compared with samples at Sw conditions, the adsorption capacity of the samples at Sir conditions shows an overall increasing trend, which is approximately 1.6 times that of the samples at Sw conditions on average. When a large amount of liquid water invades the nanopores and fractures, the water occupies the adsorption space of the methane due to the wettability effects and capillary pressure, which reduces the adsorption capacity.


2019 ◽  
Vol 358 ◽  
pp. 160-169 ◽  
Author(s):  
Prashanth Suresh Kumar ◽  
Leon Korving ◽  
Karel J. Keesman ◽  
Mark C.M. van Loosdrecht ◽  
Geert-Jan Witkamp

2019 ◽  
Author(s):  
Paul Iacomi ◽  
Philip L. Llewellyn

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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