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Combining Embedded Mean-Field Theory with Linear-Scaling Density-Functional Theory.

Joseph C A Prentice1, Robert J Charlton1, Arash A Mostofi1

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We integrated embedded mean-field theory (EMFT) into ONETEP, enabling accurate quantum embedding calculations for large systems efficiently. This breakthrough allows studying complex nanostructures previously out of reach.

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Area of Science:

  • Computational Chemistry
  • Quantum Mechanics
  • Materials Science

Background:

  • Quantum embedding methods are crucial for accurate electronic structure calculations.
  • Large-scale systems pose significant computational challenges for traditional methods.
  • Existing implementations limit the application of quantum embedding to smaller systems.

Purpose of the Study:

  • To integrate embedded mean-field theory (EMFT) into the ONETEP code.
  • To enable efficient and accurate DFT-in-DFT quantum embedding calculations.
  • To demonstrate the capability of this approach for large-scale systems.

Main Methods:

  • Implementation of EMFT within the ONETEP linear-scaling density-functional-theory code.
  • Performing simulations on diverse systems, from molecules to nanostructures.
  • Assessing the accuracy and efficiency of the developed quantum embedding method.

Main Results:

  • Successful integration of EMFT into ONETEP.
  • Demonstrated capability for accurate quantum embedding on systems with thousands of atoms.
  • Achieved significant computational cost reduction compared to full calculations.
  • Validated performance across a range of molecular and nanostructure systems.

Conclusions:

  • The EMFT-ONETEP implementation offers a powerful tool for large-scale quantum embedding.
  • This approach significantly reduces computational cost while maintaining accuracy.
  • Opens new possibilities for studying complex systems in chemistry and materials science.