Lewis Acid Catalyzed Amide Bond Formation in Covalent Graphene-MOF Hybrids.
Rabindranath LoMartin PykalAndreas SchneemannRadek ZbořilRoland A FischerKolleboyina JayaramuluMichal OtyepkaPublished in: The journal of physical chemistry. C, Nanomaterials and interfaces (2023)
Covalent hybrids of graphene and metal-organic frameworks (MOFs) hold immense potential in various technologies, particularly catalysis and energy applications, due to the advantageous combination of conductivity and porosity. The formation of an amide bond between carboxylate-functionalized graphene acid (GA) and amine-functionalized UiO-66-NH 2 MOF (Zr 6 O 4 (OH) 4 (NH 2 -bdc) 6 , with NH 2 -bdc 2- = 2-amino-1,4-benzenedicarboxylate and UiO = Universitetet i Oslo) is a highly efficient strategy for creating such covalent hybrids. Previous experimental studies have demonstrated exceptional properties of these conductive networks, including significant surface area and functionalized hierarchical pores, showing promise as a chemiresistive CO 2 sensor and electrode materials for asymmetric supercapacitors. However, the molecular-level origin of the covalent linkages between pristine MOF and GA layers remains unclear. In this study, density functional theory (DFT) calculations were conducted to elucidate the mechanism of amide bond formation between GA and UiO-66-NH 2 . The theoretical calculations emphasize the crucial role of zirconium within UiO-66, which acts as a catalyst in the reaction cycle. Both commonly observed hexa-coordinated and less common hepta-coordinated zirconium complexes are considered as intermediates. By gaining detailed insights into the binding interactions between graphene derivatives and MOFs, strategies for tailored syntheses of such nanocomposite materials can be developed.
Keyphrases
- metal organic framework
- density functional theory
- room temperature
- pet ct
- highly efficient
- molecular dynamics
- carbon nanotubes
- quantum dots
- reduced graphene oxide
- ionic liquid
- walled carbon nanotubes
- molecularly imprinted
- solid state
- perovskite solar cells
- climate change
- risk assessment
- gold nanoparticles
- deep learning
- smoking cessation
- machine learning
- positron emission tomography
- tandem mass spectrometry
- dna binding