Dynamic light scattering (DLS) is a popular method of particle size measurement, but at ultra-low particle concentrations, the occurrence of number concentration fluctuations limits the use of the technique. Number fluctuations add a non-Gaussian term to the scattered light intensity autocorrelation function (ACF). This leads to an inaccurate particle size distribution (PSD) being recovered if the normal DLS analysis model is used. We propose two methods for inverting the DLS data and recovering the PSDs when number fluctuations are apparent. One is to directly establish the relationship between the non-Gaussian ACF and the PSD by the kernel function reconstruction (KFR) method while including the non-Gaussian term to recover the PSD. The other is to remove the effect of the non-Gaussian term in the ACF by the baseline reset (BR) method. By including the number fluctuation term, the ideal recovered PSD can be obtained from the simulated data, but this will not happen in the experimental measurement data. This is because the measured intensity ACF contains more noise than the simulated ACF at ultra-low concentration. In particular, the baseline noise at the tail of long delay time of ACF overwhelms the number fluctuation term, making it difficult to recover reliable PSD data. Resetting the baseline can effectively remove the digital fluctuation term in ACF, which is also a feasible method to improve PSD recovery under ultra-low concentration. However, increasing noise at ultra-low concentrations can lead to errors in determining an effective baseline. This greatly reduces the accuracy of inversion results. Results from simulated and measured ACF data show that, for both methods, noise on the ACF limits reliable PSD recovery.

Surface plasmon resonance (SPR) detection technology is playing an important role in various fields such as food safety and environmental monitoring due to its excellent stability and reliability. However, there is also a growing demand for higher sensitivity in SPR sensors. Therefore, this work developed an SPR sensor based on the synergistic effect of electric-field enhancement and adsorption enhancement by using amino acid-derived carbon dots (CDs). The results showed that the incorporation of amino acid CDs can generate a maximum electric-field enhancement of up to 6.44 × 10⁵ V/m in the near-field region, which is 312% of that achieved by a bare gold film. And the adsorption kinetics results indicate that the active groups on the surface of amino acid CDs exhibit a notable adsorption enhancement effect for the target molecule (NaCl), with an adsorption capacity 335% higher than that of the bare gold film. This designed SPR sensor demonstrates a detection sensitivity of 167.28 a.u./RIU for NaCl solution, representing a 247.8% improvement compared to an SPR sensor without amino acid CDs under the same conditions. This SPR sensor shows promising potential for applications in biomedical and environmental detection fields.