Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 256

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Hydrophobic amino acids as a new class of kinetic inhibitors for gas hydrate formation

Open access
Sa, Jeong-Hoon, Kwak, Gye-Hoon, Lee, Bo Ram, Park, Da-Hye, Han, Kunwoo, Lee, Kun-Hong·2013·Scientific Reports

Abstract

As the foundation of energy industry moves towards gas, flow assurance technology preventing pipelines from hydrate blockages becomes increasingly significant. However, the principle of hydrate inhibition is still poorly understood. Here, we examined natural hydrophobic amino acids as novel kinetic hydrate inhibitors (KHIs) and investigated hydrate inhibition phenomena by using them as a model system. Amino acids with lower hydrophobicity were found to be better KHIs to delay nucleation and retard growth, working by disrupting the water hydrogen bond network, while those with higher hydrophobicity strengthened the local water structure. It was found that perturbation of the water structure around KHIs plays a critical role in hydrate inhibition. This suggestion of a new class of KHIs will aid development of KHIs with enhanced biodegradability and the present findings will accelerate the improved control of hydrate formation for natural gas exploitation and the utilization of hydrates as next-generation gas capture media.

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 · 10.1038/srep02428

Cites

17 of 17 references verified0 citation errors · 0 not checkable

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

Cites

Show all 17 references

Metadata

Authors
Sa, J.-H., Kwak, G.-H., Lee, B. R., Park, D.-H., Han, K., & Lee, K.-H.
Venue
Scientific Reports
Published
2013-08-13
Volume
3
Issue
1
Pages
2428-2428
ISSN
2045-2322 (ISSN-L)
OpenAlex
W2083156977
Cited by
256
References
17
FWCI
7.91
Type
journal article
Language
en
Open access
gold

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: Hydrophobic amino acids as a new class of kinetic inhibitors for gas hydrate formation. https://app.cochat.ai/papers/10.1038/srep02428
The paper
Sa, J.-H., Kwak, G.-H., Lee, B. R., Park, D.-H., Han, K., & Lee, K.-H. (2013). Hydrophobic amino acids as a new class of kinetic inhibitors for gas hydrate formation. Scientific Reports. https://doi.org/10.1038/srep02428

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.