Lanthanide nanoparticles offer potential in nanoscale photonics due to their high lifetime and quantum yield. However, surface quenching degrades these properties, requiring time-consuming experimental optimization. Here, we present a versatile Monte-Carlo approach that accurately predicts the lifetimes and quantum yields of lanthanide nanoparticles. Based on a Bayesian optimization algorithm, we optimize the geometry and doping concentration of nanocrystals resulting in simulated quantum yields of >60% and lifetimes of >30μs. This approach saves 95% time compared to experimental methods and holds promise for applications such as nanoparticle lasers or quantum memories.
Lensless endoscopy based on multicore fibres is a promising concept for 3D imaging deep inside tissue. In-depth design studies regarding novel aperiodic multicore fibre designs and their advantages in terms of endoscopy performance are presented.
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