The influence of the concentration and adsorption sites of different chemical groups on graphene through first principles simulations.

Carbon nanomaterials are one of the most promising nanostructures for adsorption of chemical species due to their high superficial area and possible interesting applications. A systematic study of chemical groups attached on graphene surfaces is necessary in order to evaluate the influence of the type and number of functionalizations on the resulting properties of a derived system. In this work, first principles simulations were used to evaluate the physical effects of different concentrations of chemical groups -COOH, -COH, -OH, -O- or -NH2 adsorbed on the graphene surface. The functionalizations occur from one up to three chemical groups and either in the same or different carbon rings. It is observed that significant changes occur in the adsorption and electronic properties due to the hybridization and symmetry points of interaction of the chemical groups. Then, the results indicate that it is possible to control the properties of the desired system through the type, concentration and binding site of the functional groups attached to the graphene monolayer.

Adsorption of anti-inflammatory nimesulide by graphene materials: a combined theoretical and experimental study.

Interactions of anti-inflammatory nimesulide (NM) with different graphene material species were explored employing both ab initio calculations, based on Density Functional Theory (DFT), and a batch adsorption process. The adsorption of NM onto graphene, with and without a vacancy, reduced graphene oxide (rGO) and functionalized graphene nanoribbons was simulated, providing a good understanding of the adsorption process of the NM molecule onto graphene material surfaces. The theoretical results indicate a physisorption interaction between NM and all of the evaluated adsorbents. Based on batch adsorption experiments, it was found that rGO, obtained via a modified Hummers method, is a good nanoadsorbent for the removal of the anti-inflammatory NM from aqueous solutions. The general-order kinetic equation displays the best fit to the experimental data compared with pseudo-first order and pseudo-second order kinetics. The equilibrium data fitted well into the Liu isotherm equation, and the maximum sorption capacity for the adsorption of NM by rGO was 82.4 mg g-1 at 25 °C. Our results of the first principle calculations and the batch adsorption experiments point out that graphene materials are promising nanomaterials for extracting NM from aqueous solutions.

Adsorption of sodium diclofenac on graphene: a combined experimental and theoretical study.

The interactions of sodium diclofenac drug (s-DCF) with different graphene species were investigated using both first principles calculations based on Density Functional Theory (DFT) and adsorption experiments. Through batch adsorption experiments, it was found that rGO was a good adsorbent for removing the s-DCF drug from aqueous solutions. The general-order kinetic model shows the best fit to the experimental data compared with pseudo-first order and pseudo-second order kinetic adsorption models. The equilibrium data (at 25 °C) were fitted to the Liu isotherm model. The maximum sorption capacity for adsorption of the s-DCF drug was 59.67 mg g(-1) for rGO. The s-DCF adsorption onto pristine graphene, graphene with a vacancy, reduced oxide graphene (rGO) and functionalized graphene nanoribbons were simulated providing a good understanding of the adsorption process of this molecule on graphene-family surfaces. The results predict a physisorption regime in all cases. Based on these results, the ab initio calculations and the adsorption experiments point out that the graphene-family are promising materials for extracting s-DCF from wastewater effluents.