Nano-microscale porosity and pore size distribution in aggregates of paddy soil as affected by long-term mineral and organic fertilization under rice-wheat cropping system

In this study, operation and maintenance performance in two long-term operating Membrane Bioreactor (MBR) wastewater treatment facilities were investigated. One facility in Japan started its operation in 1999 showed that both effluent BOD and n-hexane extracts were less than 5 mg/L, and a cumulative replacement percentage (CR%) of membrane cartridges was 7.8% as of 2008. Another facility in the United Kingdom (UK) started its operation in 1998 showed that average effluent BOD was less than 5 mg/L and more than 5-log removal of faecal coliforms was maintained. The CR% was 6.4% as of 2008. Amongst 95 facilities in Europe, the CR% was 6.4% after 5-year operation. In order to inspect product quality of membrane cartridges after 10-year operation in the UK facility, clean water flow (CWF) rate and pore size distribution were measured. The CWF rate was approximately 100% of that of new membrane cartridge's, and the pore size distribution was well maintained at less than 0.46 μm. A microscopic observation showed some scratches on the membrane surface. However, they did not lead to deteriorate permeate quality. These data suggested that the membrane cartridges can be used as long as 10 years.

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

10.26434/chemrxiv.7970402.v1 ◽

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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