Publication:
Understanding CO adsorption in MOFs combining atomic simulations and machine learning

Placeholder

School / College / Institute

Program

KU Authors

Co-Authors

Publication Date

Language

Type

Embargo Status

Journal Title

Journal ISSN

Volume Title

Alternative Title

Abstract

Correction to: Scientific Reportshttps://doi.org/10.1038/s41598-024-76491-x, published online 22 October 2024 In the original version of this article, one reference was omitted from the Reference list. Reference 25 “Naderlou, S., Vahedpour, M., and Franz, D. M. Exploring the Role of Functional Groups in Modulating NO and CO Adsorption and Diffusion in 2D (Zn)MOF-470: A Multiscale Computational Study. The Journal of Physical Chemistry C 2023 127 (38), 19301-19323 DOI: 10.1021/acs.jpcc.3c05371.” As a result, the Introduction “Franz and coworkers focused on CO adsorption in Zn-MOF-470 and its functionalized versions using GCMC simulations https://pubs.acs.org/doi/10.1021/acs.jpcc.3c05371. Results revealed that hydroxyl (-OH) functionalized Zn-MOF-470 achieves the highest uptake 116.2 cm3/g (~ 5.18 mol/kg) outperforming others at 1 bar, 298 K.” now reads, “Franz and coworkers focused on CO adsorption in Zn-MOF-470 and its functionalized versions using GCMC simulations25. Results revealed that hydroxyl (-OH) functionalized Zn-MOF-470 achieves the highest uptake at 116.2 cm3/g (~ 5.18 mol/kg) outperforming others at 1 bar, 298 K.” The original Article has been corrected.

Source

Publisher

Nature Portfolio

Subject

Multidisciplinary sciences

Citation

Has Part

Source

Scientific Reports

Book Series Title

Edition

DOI

10.1038/s41598-024-79664-w

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

0

Views

0

Downloads

View PlumX Details