Universal pipeline combines Bayesian optimization and electrodynamics simulations to maximize plasmonic performance, indicating a new standard in nanoparticle design.
Finding the optimal dimensions of metal nanoparticles to maximize their plasmonic performance in targeted applications is a complex and time-consuming process that typically requires a trial-and-error approach. Here, we propose a universal pipeline that integrates Bayesian optimization with electrodynamics simulations to find dimensions of gold bipyramids with superior plasmonic performance in photothermal efficiency, enhancement of Raman scattering and photoluminescence, strong coupling between plasmon and exciton, and aggregation-induced color difference. Our workflow is a straightforward tool for plasmonic nanoparticle design, setting their optimal dimensions for targeted applications.
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Montaño‐Priede et al. (2025) studied this question.
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