Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 263

The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.

Screening of bio-compatible metal–organic frameworks as potential drug carriers using Monte Carlo simulations

Open access
Bernini, María C., Fairen-Jimenez, David, Pasinetti, Marcelo, Ramirez-Pastor, Antonio J., Snurr, Randall Q.·2014·J. Mater. Chem. B

Abstract

A series of bio-compatible metal-organic frameworks (MOFs) have been studied as potential carriers for drug delivery applications. Grand canonical Monte Carlo (GCMC) simulations were performed to study the adsorption of the model drug ibuprofen. Simulations were first validated with available experimental data for ibuprofen adsorption and release in MIL-53, MIL-100 and MIL-101. In the second stage, the study was extended to three additional MOFs with interesting properties in terms of bio-compatibility and porosity: CDMOF-1, based on edible precursors; MOF-74 containing a highly biocompatible metal (Mg); and BioMOF-100, a mesoporous MOF with extremely high pore volume. By comparing with experimental data, we show how GCMC simulation is able to predict the macroscopic performance of new porous MOFs in drug delivery applications, providing useful molecular-level insights and giving thermodynamic and structural details of the process. Adsorption isotherms, snapshots, energy of adsorption and radial distribution functions were used to analyse the drug delivery process.

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 · 10.1039/c3tb21328e

Cites

45 of 45 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 45 references

Cited by

See all 263

Metadata

Authors
Bernini, M. C., Fairen-Jimenez, D., Pasinetti, M., Ramirez-Pastor, A. J., & Snurr, R. Q.
Venue
J. Mater. Chem. B
Published
2014
Volume
2
Issue
7
Pages
766-774
ISSN
  • 2050-750X (ISSN-L)
  • 2050-7518
OpenAlex
W2094931871
Cited by
263
References
45
FWCI
9.11
Type
journal article
Language
en
Open access
bronze

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: Screening of bio-compatible metal–organic frameworks as potential drug carriers using Monte Carlo simulations. https://app.cochat.ai/papers/10.1039/c3tb21328e
The paper
Bernini, M. C., Fairen-Jimenez, D., Pasinetti, M., Ramirez-Pastor, A. J., & Snurr, R. Q. (2014). Screening of bio-compatible metal–organic frameworks as potential drug carriers using Monte Carlo simulations. J. Mater. Chem. B. https://doi.org/10.1039/c3tb21328e

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.