Highly sensitive detection of nanoparticles with a self-referenced and self-heterodyned whispering-gallery Raman microlaser.

Abstract

Optical whispering-gallery-mode resonators (WGMRs) have emerged as promising platforms for label-free detection of nano-objects. The ultimate sensitivity of WGMRs is determined by the strength of the light-matter interaction quantified by quality factor/mode volume, Q/V, and the resolution is determined by Q. To date, to improve sensitivity and precision of detection either WGMRs have been doped with rare-earth ions to compensate losses and increase Q or plasmonic resonances have been exploited for their superior field confinement and lower V. Here, we demonstrate, for the first time to our knowledge, enhanced detection of single-nanoparticle-induced mode splitting in a silica WGMR via Raman gain-assisted loss compensation and WGM Raman microlaser. In particular, the use of the Raman microlaser provides a dopant-free, self-referenced, and self-heterodyned scheme with a detection limit ultimately determined by the thermorefractive noise. Notably, we detected and counted individual nanoparticles with polarizabilities down to 3.82 × 10(-6) μm(3) by monitoring a heterodyne beatnote signal. This level of sensitivity is achieved without exploiting plasmonic effects, external references, or active stabilization and frequency locking. Single nanoparticles are detected one at a time; however, their characterization by size or polarizability requires ensemble measurements and statistical averaging. This dopant-free scheme retains the inherited biocompatibility of silica and could find widespread use for sensing in biological media. The Raman laser and operation band of the sensor can be tailored for the specific sensing environment and the properties of the targeted materials by changing the pump laser wavelength. This scheme also opens the possibility of using intrinsic Raman or parametric gain for loss compensation in other systems where dissipation hinders progress and limits applications.