Efficiently accounting for ion correlations in electrokinetic nanofluidic devices using density functional theory

Area of Science:

• Physical Chemistry
• Nanotechnology
• Computational Science

Background:

• Electrokinetic phenomena in nanofluidics are governed by electrical double layers (EDLs) at device walls.
• Accurate EDL modeling is critical for designing and optimizing nanofluidic devices.
• Classical theories like Poisson-Boltzmann often neglect finite ion size and ion-ion correlations.

Purpose of the Study:

• To demonstrate density functional theory (DFT) as an accurate and efficient method for modeling EDLs in nanofluidics.
• To investigate the impact of finite ion size and ion-ion correlations on EDL behavior.
• To explore DFT's capability in predicting nonlinear EDL phenomena.

Main Methods:

• Applying density functional theory (DFT) derived from liquid-theory thermodynamic principles.
• Computing finite ion size effects and ion-ion correlations.
• Comparing DFT predictions with classical theories for nanofluidic systems.

Main Results:

• DFT accurately computes finite ion size effects and ion-ion correlations, improving EDL models.
• DFT successfully predicts nonlinear phenomena such as charge inversion, which classical theories miss.
• Predicted charge inversion leads to distinct current densities and ion velocities in pressure-driven and electro-osmotic flows.

Conclusions:

• Density functional theory (DFT) is a valuable tool for modeling nanofluidic systems, especially those with small dimensions, high surface charges, high ion concentrations, or large ions.
• DFT's ability to capture ion-ion correlations provides a more accurate understanding of EDL behavior and nonlinear effects.
• DFT offers a promising approach for the design and optimization of next-generation nanofluidic devices.