Achieving Predictive Description of Molecular Conductance by Using a Range-Separated Hybrid Functional

Area of Science:

• Computational chemistry
• Molecular electronics
• Condensed matter physics

Background:

• Computational studies frequently overestimate molecular bridge conductance compared to experimental data.
• This discrepancy may stem from challenges in creating stable molecular junctions or limitations in computational methods.
• Traditional density functionals can introduce inaccuracies in predicting electronic properties.

Purpose of the Study:

• To investigate the impact of different computational functionals on the accuracy of molecular conductance calculations.
• To compare the performance of range-separated hybrid (RSH) functionals against traditional functionals for molecular conductance.
• To identify computational schemes that better reproduce experimentally measured conductance values.

Main Methods:

• First-principles calculations were performed on molecular bridges.
• Calculations utilized both traditional functionals and a range-separated hybrid (RSH) functional.
• Computed conductance values were compared against experimentally measured data for four different molecular systems.

Main Results:

• The RSH functional yielded calculated conductance values within the same order of magnitude as experimental measurements across all tested cases.
• The widely used B3LYP functional significantly overestimated conductance, by approximately 1-2 orders of magnitude.
• The improved accuracy with the RSH functional is attributed to a more physically realistic description of frontier orbital quasi-particles.

Conclusions:

• Range-separated hybrid functionals offer a more accurate approach for calculating molecular bridge conductance than traditional functionals.
• Accurate prediction of molecular conductance is crucial for advancing molecular electronics.
• The choice of computational functional significantly impacts the reliability of theoretical predictions in molecular electronics.