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.

This study evaluated the feasibility of removing Alizarin Red S dye (ARS) from aqueous solutions, using nanoadsorbents such as single and multiwalled carbon nanotubes (SWCNT and MWCNT, respectively). The effect of pH, shaking time, and temperature on adsorption was studied. The pH 2.0 was observed to show optimum removal for both of the carbon nanotubes. The equilibrium time (298–318 K) was fixed at 65 and 100 min for SWCNT and MWCNT, respectively. The kinetics of adsorption was calculated using pseudo-first-order, pseudo-second-order, and general-order equations. The calculations revealed that the general-order kinetic equation best-fit the adsorption data. The Liu isotherm model best fit the equilibrium data (298–318 K). The maximum sorption capacity at 318 K for ARS dye was 312.5 and 135.2 mg g^–1 for SWCNT and MWCNT, respectively. Change in entropy (ΔS°), Gibb’s free energy change (ΔG°), and enthalpy (ΔH°) were calculated for the adsorption of ARS dye. The electrostatic interaction between nanoadsorbent–adsorbate was conveyed using the magnitude of change in enthalpy. Ab initio simulation was used to study the interaction of ARS with (5,5) and (8,0) SWCNTs, and (16,0) and (25,0) SWCNTs with and without vacancy. The theoretical calculations showed that the binding energies between ARS dye and SWCNTs are enhanced as the nanotube diameter gets bigger; however, the distance of binding remains unchanged. Therefore, the results from first principle calculations indicated that electrostatic interaction may be responsible for the adsorption of ARS dye onto SWCNT. The theoretical outcomes were found to be in coordination with the experimental estimates.

The structural and electronic properties of $\mathrm{Cr}{\mathrm{O}}_3$ interacting with graphene layer are calculated using ab initio methods based on the density functional theory. The $\mathrm{Cr}{\mathrm{O}}_3$ acts as an electron acceptor modifying the original electronic and magnetic properties of the graphene surface through an adsorption process. The changes induced in the electronic properties are strongly dependent on the $\mathrm{Cr}{\mathrm{O}}_3$ adsorption site, and for some sites, it is possible to open a gap in the electronic band structure. Spin polarization effects are also predicted for some adsorption configurations for which the binding energy is lower and charge transfer is higher.

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.