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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

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Published on: April 12, 2019

Density functional theory for charged fluids.

Jian Jiang¹, Valeriy V Ginzburg, Zhen-Gang Wang

¹Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA. zgw@caltech.edu.

|June 29, 2018

Summary

A new density functional theory (DFT) improves modeling of charged systems like electrolytes. This approach simplifies calculations and avoids spurious phase predictions, making it more computationally efficient.

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Area of Science:

Physical Chemistry
Computational Chemistry
Soft Matter Physics

Background:

Density functional theory (DFT) is crucial for modeling complex fluids.
Existing DFT models for inhomogeneous charged systems face computational challenges.
Accurate modeling of electrolytes and polyelectrolytes is essential in various scientific fields.

Purpose of the Study:

To develop an improved density functional theory (DFT) for inhomogeneous charged systems.
To enhance the treatment of electrostatic correlations and chain connectivity.
To reduce computational cost and facilitate implementation of DFT models.

Main Methods:

Incorporating fundamental measure theory (FMT) for hard-sphere contributions.
Applying thermodynamic perturbation theory and mean-spherical approximation.
Utilizing a first-order Taylor expansion for electrostatic correlations and chain connectivity.

Main Results:

The first-order Taylor expansion provides results comparable to second-order expansions.
The new treatment successfully avoids spurious layer-by-layer phase predictions.
The improved DFT model offers significant simplifications and reduced computational expense.

Conclusions:

The proposed DFT offers a more efficient and accurate method for simulating charged systems.
This advancement facilitates the study of electrolytes and polyelectrolytes.
The simplified approach enhances the practical applicability of DFT in computational chemistry and physics.