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Cited by 600

The DOI matches its Crossref record; 232 of the 232 references it cites were found in a registry or an index.

Hydrogen Sulfide Capture: From Absorption in Polar Liquids to Oxide, Zeolite, and Metal–Organic Framework Adsorbents and Membranes

Open access
Shah, Mansi S., Tsapatsis, Michael, Siepmann, J. Ilja·2017·Chemical Reviews

Abstract

Hydrogen sulfide removal is a long-standing economic and environmental challenge faced by the oil and gas industries. H 2 S separation processes using reactive and non-reactive absorption and adsorption, membranes, and cryogenic distillation are reviewed. A detailed discussion is presented on new developments in adsorbents, such as ionic liquids, metal oxides, metals, metal–organic frameworks, zeolites, carbon-based materials, and composite materials; and membrane technologies for H 2 S removal. This Review attempts to exhaustively compile the existing literature on sour gas sweetening and to identify promising areas for future developments in the field.

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Registry

Crossref · 10.1021/acs.chemrev.7b00095

Cites

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Metadata

Authors
Shah, M. S., Tsapatsis, M., & Siepmann, J. I.
Venue
Chemical Reviews
Published
2017-07-05
Volume
117
Issue
14
Pages
9755-9803
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W2726413144
Cited by
600
References
232
FWCI
7.01
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Hydrogen Sulfide Capture: From Absorption in Polar Liquids to Oxide, Zeolite, and Metal–Organic Framework Adsorbents and Membranes. https://app.cochat.ai/papers/10.1021/acs.chemrev.7b00095
The paper
Shah, M. S., Tsapatsis, M., & Siepmann, J. I. (2017). Hydrogen Sulfide Capture: From Absorption in Polar Liquids to Oxide, Zeolite, and Metal–Organic Framework Adsorbents and Membranes. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.7b00095

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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.