The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Computational structure characterisation tools in application to ordered and disordered porous materials
Abstract
In this article, we present a set of computational tools for systematic characterisation of ordered and disordered porous materials. These tools include calculation of the accessible surface area and geometric pore size distribution, analysis of the structure connectivity and percolation analysis of the porous space. We briefly discuss the algorithms behind these calculations. To demonstrate the capabilities of the tools and the type of insights that can be gained from their application, we consider a series of case studies. These case studies include small molecular fragments, several crystalline metal-organic materials, and variants of these materials with induced defects and disorder in their structure. The simulation package is available upon request.
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.
Integrity signals
Registry
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.
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
Phase Transitions and Critical Phenomena
(2016) · Statistical and Thermal Physics · doi:10.1201/9781439850541-13 · Cited by 11,176
Eddaoudi, M., Kim, J., Rosi, N., Vodak, D., Wachter, J., O'Keeffe, M., & Yaghi, O. M. (2002) · Science · doi:10.1126/science.1067208 · Cited by 8,132
DREIDING: a generic force field for molecular simulations
Mayo, S. L., Olafson, B. D., & Goddard, W. A. (1990) · The Journal of Physical Chemistry · doi:10.1021/j100389a010 · Cited by 6,585
Ultrahigh Porosity in Metal-Organic Frameworks
Furukawa, H., Ko, N., Go, Y. B., Aratani, N., Choi, S. B., Choi, E., Yazaydin, A. Ö., Snurr, R. Q., O’Keeffe, M., Kim, J., et al. (2010) · Science · doi:10.1126/science.1192160 · Cited by 3,904
Metal–organic frameworks: a new class of porous materials
Rowsell, J. L. C., & Yaghi, O. M. (2004) · Microporous and Mesoporous Materials · doi:10.1016/j.micromeso.2004.03.034 · Cited by 2,963
A route to high surface area, porosity and inclusion of large molecules in crystals
Materials Design and Discovery Group, Chae, H. K., Siberio-Pérez, D. Y., Kim, J., Go, Y., Eddaoudi, M., Matzger, A. J., O'Keeffe, M., & Yaghi, O. M. (2004) · Nature · doi:10.1038/nature02311 · Cited by 2,816
Reticular Chemistry: Occurrence and Taxonomy of Nets and Grammar for the Design of Frameworks
Ockwig, N. W., Delgado-Friedrichs, O., O'Keeffe, M., & Yaghi, O. M. (2005) · Accounts of Chemical Research · doi:10.1021/ar020022l · Cited by 2,197
Hoshen, J., & Kopelman, R. (1976) · Physical Review B · doi:10.1103/physrevb.14.3438 · Cited by 1,928
Metal‐Organic Frameworks: A Rapidly Growing Class of Versatile Nanoporous Materials
Meek, S. T., Greathouse, J. A., & Allendorf, M. D. (2011) · Advanced Materials · doi:10.1002/adma.201002854 · Cited by 1,407
Postsynthetic modification of metal–organic frameworks—a progress report
Tanabe, K. K., & Cohen, S. M. (2011) · Chem. Soc. Rev. · doi:10.1039/c0cs00031k · Cited by 1,173
Cited by
Wu, H., Chua, Y. S., Krungleviciute, V., Tyagi, M., Chen, P., Yildirim, T., & Zhou, W. (2013) · Journal of the American Chemical Society · doi:10.1021/ja404514r · Cited by 1,457
New Stories of Zeolite Structures: Their Descriptions, Determinations, Predictions, and Evaluations
Li, Y., & Yu, J. (2014) · Chemical Reviews · doi:10.1021/cr500010r · Cited by 603
High-throughput computational screening of metal–organic frameworks
Colón, Y. J., & Snurr, R. Q. (2014) · Chem. Soc. Rev. · doi:10.1039/c4cs00070f · Cited by 470
Zhao, Y., Liu, H., Wu, C., Zhang, Z., Pan, Q., Hu, F., Wang, R., Li, P., Huang, X., & Li, Z. (2019) · Angewandte Chemie International Edition · doi:10.1002/anie.201901194 · Cited by 328
Large language models for reticular chemistry
Zheng, Z., Rampal, N., Inizan, T. J., Borgs, C., Chayes, J. T., & Yaghi, O. M. (2025) · Nature Reviews Materials · doi:10.1038/s41578-025-00772-8 · Cited by 134
Metadata
- Authors
- Sarkisov, L., & Harrison, A.
- Venue
- Molecular Simulation
- Publisher
- Informa UK Limited
- Published
- 2011-12
- Volume
- 37
- Issue
- 15
- Pages
- 1248-1257
- ISSN
- 0892-7022 (ISSN-L)
- 1029-0435
- OpenAlex
- W1968598487
- Cited by
- 658
- References
- 23
- FWCI
- 14.28
- 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: Computational structure characterisation tools in application to ordered and disordered porous materials. https://app.cochat.ai/papers/10.1080/08927022.2011.592832
- The paper
- Sarkisov, L., & Harrison, A. (2011). Computational structure characterisation tools in application to ordered and disordered porous materials. Molecular Simulation. https://doi.org/10.1080/08927022.2011.592832
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.
