CuNO2 and Cu(+)NO2 Revisited:  A Comparative ab Initio and DFT Study

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry

Background:

• Copper nitrite (CuNO2) and its ionic form (Cu(+)NO2) are important in various chemical processes.
• Understanding their structural isomers and energetic properties is crucial for predicting reactivity.

Purpose of the Study:

• To investigate the potential energy surfaces (PES) of CuNO2 and Cu(+)NO2.
• To compare the accuracy of different computational methods, including ab initio, pure DFT, and hybrid DFT, for these systems.

Main Methods:

• Full optimization of stationary points (minima and transition structures) using coupled cluster (CCSD(T), QCISD(T)) and density functional theory (DFT) methods (BPW91, PBE, PBE0, B3LYP).
• Employment of large atomic natural orbital (ANO) basis sets for high accuracy.
• Analysis of relative energies, structures, and bond dissociation energies.

Main Results:

• The C2v bidentate η(2)-O,O isomer is the most stable for CuNO2.
• For Cu(+)NO2, the Cs monodentate η(1)-O trans isomer is the most stable, followed by cis and η(1)-N isomers.
• Hybrid DFT methods (PBE0, B3LYP) show good performance for relative stabilities and structures, outperforming pure DFT methods.
• Pure DFT methods exhibit less reliability in predicting bond dissociation energies compared to ab initio methods.

Conclusions:

• Hybrid DFT methods offer a reasonable balance between accuracy and computational cost for studying CuNO2 and Cu(+)NO2 isomers.
• Careful selection of computational methods is essential for accurate predictions of energetic properties.
• The study provides valuable insights into the structural preferences and electronic properties of copper nitrite species.