Computational Design of Durable Spherical Nanoparticles with Optimal Material, Shape, and Size for Ultrafast Plasmon-Enhanced Nanocavitation

Photons interaction with metallic nanoparticles can excite a resonant plasmon that concentrates energy at the nanoscale. At high intensity, this quasi-particle decays into a photoexcited nanoplasma that triggers the generation of nanobubbles, which can be used for imaging and therapeutic purposes. This highly nonlinear wavelength-dependent process is controlled by the nanoparticle material, shape, and size in intricate ways, which justifies the need for a systematic design approach that currently lacks in the field. To palliate to this, we developed in this work a computational framework that enables the efficient in silico screening of large libraries of spherically symmetric structures and metallic materials. Using this framework, we have investigated the nanocavitation performance of spherical nanoparticles with more than 14 million combinations of materials, shapes, sizes, and irradiation conditions, from which we could distill general principles for the design of durable nanoantennas. In the near-infrared, our work suggests that Cu, TiN, Ag, and Au nanoparticles offer similar performance, with optimal diameters of ∼λ/5. In contrast, only Ag and Al are appropriate for irradiation in the UV–visible, cavitation being associated with structural damage for all other tested materials at these wavelengths. We also demonstrate that silica-metal nanoshell structures have the potential to reduce the cavitation threshold at all wavelengths compared to homogeneous nanoparticles due to their extensive spectral tunability. However, designing more complex layered systems seems to bring no benefit. Our work provides important physical insight on the influence of materials on nanocavitation and simulation-based design guidelines that should be broadly useful for the engineering of nonlinear nanoplasmonic materials for biological applications