Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 220

The DOI matches its Crossref record.

Analysis of the Relationship between H2S Removal Capacity and Surface Properties of Unimpregnated Activated Carbons

Adib, Foad, Bagreev, Andrey, Bandosz, Teresa J.·2000·Environmental Science & Technology

Abstract

The H 2 S breakthrough capacity was measured on two series of activated carbons of a coconut shell and a bituminous coal origins. To broaden the spectrum of surface features the samples were oxidized using nitric acid or ammonium persulfate under conditions chosen to preserve their pore structures. Then the carbons were characterized using Boehm titration, potentiometric titration, thermal analysis, temperature programmed desorption, sorption of nitrogen, and sorption of water. It was found that the choice of unimpregnated carbon for application as H 2 S adsorbent should be made based on parameters of its acidity such as number of acidic groups, pH of surface, amount of surface groups oxygen, or weight loss associated to decomposition of surface oxygen species. The results obtained from the analyses of six unimpregnated carbon samples suggest that there are certain threshold values of these quantities which, when exceeded, have a dramatic effect on the H 2 S breakthrough capacity.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/es990341g

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Metadata

Authors
Adib, F., Bagreev, A., & Bandosz, T. J.
Venue
Environmental Science & Technology
Published
2000-01-12
Volume
34
Issue
4
Pages
686-692
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W1972737400
Cited by
220
References
0
FWCI
41.36
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Analysis of the Relationship between H2S Removal Capacity and Surface Properties of Unimpregnated Activated Carbons. https://app.cochat.ai/papers/10.1021/es990341g
The paper
Adib, F., Bagreev, A., & Bandosz, T. J. (2000). Analysis of the Relationship between H2S Removal Capacity and Surface Properties of Unimpregnated Activated Carbons. Environmental Science & Technology. https://doi.org/10.1021/es990341g

Data sources

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.