Analog and digital detection of plasmon-enhanced upconverting nanoparticles

Upconverting nanoparticles (UCNPs) offer significant potential for highly sensitive biosensing due to their background-free detection and excellent photostability. However, their intrinsically low upconversion efficiency limits their usage in practical applications. To reach ultra-high sensitivity with a simplified readout system, the excitation field, and consequently the upconversion luminescence, can be strengthened by using plasmon-based mechanisms. For qualitative detection, the optical field inhomogeneities in plasmon-enhanced upconversion do not generally cause practical limitations, but in quantitative detection, a homogeneous signal across the biosensor surface is required. With UCNPs this is particularly challenging since the upconversion efficiency is highly non-linear depending on the excitation field intensity. The motivation for this work is to compare the digital and analog readouts for quantitative biosensing applications. UCNPs are imaged via diverging surface plasmon polaritons, and the images are analyzed using both methods: digital detection counts individual UCNPs, whereas analog detection quantifies upconversion luminescence by integrating the pixel intensity across the image. Our results show that analog detection exhibits greater variability than digital detection. This indicates that digital detection is likely to provide better repeatability when employing plasmon-enhanced UCNPs for quantitative biosensing.