Luca Bellucci^1*, Valentina Tozzini^1*, Zacharias Fthenakis¹, Mauro Francesco Sgroi², Francesco Delfino¹

1 Istituto Nanoscienze del Consiglio Nazionale delle Ricerche (CNR-NANO), NEST-SNS, Piazza San Silvestro, 12, Pisa, 56127, Italy

2 Department of Chemistry and NIS-INSTM, University of Turin, Via Pietro Giuria 7, Torino, 10125, Italy

* Corresponding authors emails: luca.bellucci@nano.cnr.it, valentina.tozzini@nano.cnr.it

DOI10.24435/materialscloud:y0-9z [version v1]

Publication date: Mar 27, 2025

How to cite this record

Luca Bellucci, Valentina Tozzini, Zacharias Fthenakis, Mauro Francesco Sgroi, Francesco Delfino, Reduced graphene oxide membrane models for hydrogen storage, Materials Cloud Archive 2025.47 (2025), https://doi.org/10.24435/materialscloud:y0-9z

Description

A database of 600 atomistic models of reduced graphene oxide (rGO) and hydrogenated rGO (H-rGO) was constructed, comprising 120 rGO and 480 H-rGO structures. The dataset spans a broad range of oxygen concentrations, –O–:–OH (epoxy/ether to hydroxyl) ratios, and hydrogenation levels. The database is designed for applications in computational modeling, machine learning, and structure–property analyses. The models were generated following a three-step simulation protocol: – Step 1 | Generation of Pseudo-GO Models: Graphene sheets were functionalized with oxygen groups (–O– or –OH), randomly distributed according to three –O–:–OH ratios (25:75, 50:50, and 75:25). Functionalization was applied symmetrically on both sides of the sheet, avoiding adjacent carbon atoms. – Step 2 | Thermal Reduction: Each pseudo-GO structure was subjected to annealing at four different temperatures (1000, 1500, 2000, and 2500 K). After initial relaxation at 300 K, the models were heated, equilibrated, annealed back to room temperature, and re-optimized. This step produced 120 rGO models exhibiting a range of oxygen contents, functional group distributions, and defect patterns. – Step 3 | Hydrogenation of rGO Models: rGO models were exposed to atomic hydrogen using a combined Grand Canonical Monte Carlo and molecular dynamics (GCMC/MD) scheme at 300 K and four hydrogen pressures (1, 2, 4, and 8 bar). Hydrogenation was performed with 50 GCMC exchange steps every 1 ps of MD, followed by relaxation and removal of unstable species. This step generated 480 H-rGO models with varying hydrogen coverage and bonding configurations. All simulations were performed using the LAMMPS software package with the ReaxFF reactive force field.

Materials Cloud sections using this data

Files

File name	Size	Description
README.txt MD5md5:bae7766fb407761b0cb5fa156e664ecb	674 Bytes	README
rGO.tgz MD5md5:a79921c8dd0e4768a084d9b0b9f23063	468.4 KiB	Reduced Graphene Oxide (rGO) models.
H1-rGO.tgz MD5md5:8a236017132aa8349013235879dccad5	489.1 KiB	Hydrogenated rGO (H-rGO) at 1 bar and 300 K
H2-rGO.tgz MD5md5:ea59499c280e6e1084ffd15bc955194a	488.4 KiB	Hydrogenated rGO (H-rGO) at 2 bar and 300 K
H4-rGO.tgz MD5md5:368343664e70c60e0eae85b1a6278e3a	489.1 KiB	Hydrogenated rGO (H-rGO) at 4 bar and 300 K
H8-rGO.tgz MD5md5:3336101eed97b6d87d941a9d80d8c411	491.9 KiB	Hydrogenated rGO (H-rGO) at 8 bar and 300 K

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Keywords

Reduced Graphene Oxide Hydrogenated graphene oxide Graphene oxide models Functionalized carbon nanostructures