Controllable atomistic graphene oxide model and its application in hydrogen sulfide removal

Area of Science:

• Computational Materials Science
• Surface Chemistry
• Nanomaterials

Background:

• Accurate atomistic models of graphene oxide (GO) are crucial for understanding its properties but are challenging to generate due to synthesis-dependent structures.
• Existing models often lack the detail to predict chemical interactions accurately.

Purpose of the Study:

• To develop a reliable method for generating atomistic graphene oxide models.
• To investigate the reactive adsorption of H2S and H2O/H2S mixtures on graphene oxide surfaces.
• To provide insights into the surface chemistry of graphene oxide for potential applications.

Main Methods:

• Utilized temperature-programmed molecular dynamics simulations combined with the ReaxFF reactive force field.
• Generated controllable atomistic GO structures by grafting epoxy and hydroxyl groups onto graphene surfaces.
• Performed reactive adsorption calculations for H2S and H2O/H2S mixtures on the generated GO models.

Main Results:

• Successfully generated realistic atomistic GO models that align with experimental data and ab initio calculations.
• Observed H2S dissociation on carbonyl groups, releasing H2O, CO2, and CO.
• Found that H2O preferentially adsorbs to carbonyl sites in H2O/H2S mixtures, hindering H2S decomposition.

Conclusions:

• The developed simulation methodology enables controllable generation of atomistic GO models.
• The study elucidates the reaction mechanisms of H2S and H2O/H2S on GO surfaces.
• This approach offers a new pathway for theoretical studies of graphene oxide and other amorphous materials.