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Cited by 207

The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

Advanced Sorption Process Applications

Open access
·2019·IntechOpen eBooks

Abstract

At the beginning of the twenty-firstst century, separation processes presented a comprehensive application of the major operations performed by various industries, such as chemical, food, environmental, and biotechnology. Sorption, one of the preferred separation processes because of its effectiveness at different interfaces, has caught the attention of many scientists. This book is aimed at gaining a general knowledge of sorption and a number of extremely important applications, as well as recognizing its functions and paramount importance in chemical and biochemical plants, including environmental treatment. Moreover, progress in the phenomenon is highlighted in this book. To help provide instruction in the important sorption processes, we have chosen authors who have extensive industrial and academic experience in closing the gap between theory and practice. Crucial progress in the theoretical information section of sorption has been achieved, mainly through the development of new techniques that examine the usage of various sorbents, including nanomaterials for the removal of various pollutants. We have subdivided the book into several sections, one of which is focused on applications of the sorption process, which presents real results of the recent studies and gives a source of up-to-date literature. The relationship between the sorption process and isotherm and kinetics modeling is analyzed in another chapter. This book will be a reference book for those who are interested in sorption techniques from various industries.

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Crossref · 10.5772/intechopen.75857

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Metadata

Venue
IntechOpen eBooks
Publisher
IntechOpen
Published
2019-02-20
OpenAlex
W2916091117
Cited by
207
References
18
FWCI
17.59
Type
book
Language
en
Open access
gold

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.