Electronic structures of 3d-metal mononitrides

Area of Science:

• Computational chemistry
• Quantum chemistry
• Materials science

Background:

• Accurate prediction of molecular properties is crucial for understanding chemical behavior.
• Density functional theory (DFT) is a widely used computational method for electronic structure calculations.
• Different DFT functionals can yield varying results, necessitating careful selection.

Purpose of the Study:

• To evaluate the performance of various density functional methods (B3LYP, BLYP, BHLYP, BPW91, B3PW91) for predicting molecular properties.
• To compare calculated properties of neutral and charged molecules with experimental data and previous theoretical studies.
• To identify the most suitable functionals for specific molecular properties and charge states.

Main Methods:

• Utilized density functional theory (DFT) with five different functionals: B3LYP, BLYP, BHLYP, BPW91, and B3PW91.
• Calculated key molecular properties including bond distances, vibrational frequencies, electron affinities, ionization potentials, and dissociation energies.
• Performed calculations on neutral, positively charged (cations), and negatively charged (anions) molecular species.

Main Results:

• Calculated molecular properties showed significant dependence on the chosen DFT functional.
• Pure density functional methods (BLYP, BPW91) demonstrated good agreement with experimental data for bond distances and vibrational frequencies of neutral species.
• Hybrid exchange functional methods (B3LYP, B3PW91) showed better accuracy in predicting dissociation energies for cations.
• The BHLYP functional consistently yielded lower dissociation energies for both neutral and charged species.

Conclusions:

• The choice of DFT functional critically impacts the accuracy of calculated molecular properties.
• BLYP and BPW91 are recommended for neutral species, while B3LYP and B3PW91 are preferred for cation dissociation energies.
• Further investigation may be needed to refine functional selection for specific applications in computational chemistry.