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Real-Space Methods for Ab Initio Modeling of Surfaces and Interfaces under External Potential Bias.

Kartick Ramakrishnan1, Gopalakrishnan Sai Gautam2, Phani Motamarri1

  • 1Department of Computational and Data Sciences, Indian Institute of Science, Bengaluru 560012, India.

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We present two novel real-space density functional theory (DFT) methods for applying external potential bias to model surfaces and interfaces. These methods overcome limitations of plane-wave DFT, enabling more accurate simulations of electronic and catalytic devices.

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Area of Science:

  • Computational Materials Science
  • Surface Science
  • Computational Chemistry

Background:

  • Accurate modeling of surfaces and interfaces under external potential bias is crucial for electronic, catalytic, and energy storage devices.
  • Existing plane-wave density functional theory (DFT) methods face limitations due to periodic boundary conditions and scalability issues.
  • Real-space DFT offers flexibility for generic boundary conditions, making it suitable for surface and interface studies.

Purpose of the Study:

  • To introduce and validate two new real-space DFT methods for applying external potential bias to surfaces and interfaces.
  • To provide an alternative to plane-wave DFT methods, overcoming their inherent restrictions.
  • To enable more accurate and scalable simulations of surface and interface phenomena.

Main Methods:

  • Developed two real-space finite-element DFT (DFT-FE) methods for applying external potential bias.
  • Method 1: Applied a constant electric field by modifying the DFT Hamiltonian with an auxiliary linear potential.
  • Method 2: Directly enforced external potential bias by imposing constraints on the electrostatic potential.

Main Results:

  • Validated the constant electric field method against plane-wave DFT on benchmark systems (Li7La3Zr2O12, GaAs, Al).
  • Evaluated both methods for ground-state properties like surface and adsorption energies.
  • Demonstrated the ability to constrain electrostatic potential in localized regions, a challenge for periodic codes.

Conclusions:

  • The developed real-space DFT methods offer a robust alternative to plane-wave approaches for modeling surfaces and interfaces under potential bias.
  • These methods overcome periodic boundary condition limitations and offer better scalability for larger systems.
  • The framework facilitates accurate investigation of surface and interface phenomena without assumptions or correction schemes.