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Orbital-free methods for plasmonics: Linear response.

Fabio Della Sala1

  • 1Institute for Microelectronics and Microsystems (CNR-IMM), Via Monteroni, Campus Unisalento, 73100 Lecce, Italy and Center for Biomolecular Nanotechnologies, Istituto Italiano di Tecnologia, Via Barsanti 14, 73010 Arnesano (LE), Italy.

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|September 15, 2022
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Summary
This summary is machine-generated.

Orbital-free methods accurately model quantum effects in large plasmonic systems by deriving from Time-Dependent Density Functional Theory. These methods offer a computationally efficient alternative to traditional approaches for designing advanced nanomaterials.

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Area of Science:

  • Computational Nanoscience
  • Quantum Chemistry
  • Materials Science

Background:

  • Plasmonic systems, like metal nanoparticles, are crucial in fields from biology to photovoltaics.
  • Accurate optical response modeling is vital for designing plasmonic nanomaterials.
  • Classical electrodynamics fails for nanoscale systems due to nonlocal and spill-out effects.

Purpose of the Study:

  • To review orbital-free (OF) methods derived from linear response Time-Dependent Density Functional Theory (TD-DFT).
  • To highlight approximations and properties of OF methods for modeling plasmonic systems.
  • To validate OF method accuracy for optical properties of jellium nanoparticles.

Main Methods:

  • Derivation of OF methods (semiclassical to Quantum Hydrodynamic Theory) from linear response TD-DFT.
  • Validation using jellium nanoparticles as a model plasmonic system.
  • Focus on methods scaling linearly with system size for computational efficiency.

Main Results:

  • OF methods accurately describe quantum effects in large plasmonic systems.
  • These methods provide accurate optical properties without system-specific parameters.
  • Accuracy is dependent on the quality of the kinetic energy functional for ground-state electronic density.

Conclusions:

  • Orbital-free TD-DFT methods are a powerful, computationally efficient tool for plasmonic systems.
  • They offer a viable alternative to computationally expensive full TD-DFT for large-scale applications.
  • Future developments should focus on improving universal kinetic energy functionals.