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A Simple Method for the Size Controlled Synthesis of Stable Oligomeric Clusters of Gold Nanoparticles under Ambient Conditions
Published on: February 5, 2016
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Towards structural optimization of gold nanoclusters with quantum Monte Carlo
Juha Tiihonen1, Hannu Häkkinen1,2
1Department of Physics, Nanoscience Center, University of Jyväskylä, Jyväskylä, Finland.
The Journal of Chemical Physics
|November 1, 2023
Summary
Quantum Monte Carlo (QMC) methods improve accuracy and consistency for simulating gold compounds compared to density functional theory (DFT). QMC also enables robust structural optimization of gold nanoclusters for biochemical applications.
Area of Science:
- Computational chemistry
- Quantum mechanics
- Materials science
Background:
- Gold nanoclusters are crucial for biochemical applications.
- Simulating gold compounds is challenging due to dynamic correlation and relativistic effects.
- Density functional theory (DFT) relies on approximations for exchange-correlation (XC) functionals.
Purpose of the Study:
- To evaluate quantum Monte Carlo (QMC) techniques for optimizing gold compounds.
- To compare QMC accuracy and consistency against DFT.
- To demonstrate QMC's capability for structural optimization of gold nanoclusters.
Main Methods:
- Variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) simulations.
- Density functional theory (DFT) calculations with various XC functionals.
- Structural optimization using VMC forces for thiolated gold clusters.
Main Results:
- QMC methods provide more accurate and consistent results than DFT.
- QMC mitigates the limitations of XC approximations in DFT.
- A robust and scalable QMC-based structural optimization workflow was demonstrated.
Conclusions:
- QMC techniques are promising for accurate simulations of gold compounds.
- QMC offers a reliable alternative to DFT for gold nanocluster research.
- Further development of QMC methods will enhance their applicability in nanoscience.
