Diffusive modeling and Monte Carlo analysis of random-laser-base optical sensors for dual refractive index and temperature detection

Accurate temperature measurements and thermal property measurements in the micro- and nanoscopes are crucial to thermal management and energy harvesting, and biomedical diagnostics. The traditional optical methods of optical temperature sensors, like interferometry, fluorescence or photonic resonators, tend to be challenging to be integrated into disordered or miniaturized systems and have limited operational bandwidths or are complex to fabricate. To overcome these shortcomings, we suggested a new case study of a random-laser-based optical sensor that is specially intended to be used in detection of temperature and refractive index of high sensitivity of a thermally dynamic setup. The suggested one exploits several scattering and diffusive light transport, which is modeled following a modified photon diffusion framework and an additional gain-threshold model. The effect of geometry, thermal gradients and noise levels on spectral response is captured through Monte Carlo simulations. The model explicitly gives connections between thermal sensitivity and physical parameters like group delay, effective scattering length and lasing threshold gain. These findings indicate temperature sensitivities of over 50 pm/K and changes in the refractive index of up to 2.6 nm/RIU over optimized geometries. With high-SNR, spectral uncertainty of less than 0.1 pm is attained, and spectral limits of thermal detection of 0.02 K are possible. The suggested scheme offers scalable and solid base to the next-generation random-laser sensors of biochemical, thermal and environmental diagnostics.