Two-dimensional transition metal dichalcogenides (TMDs) have very potential properties for sensing applications. Hence, a lossy-mode resonance (LMR) refractive index (RI) sensor based on TMDs- indium-tin-oxide (ITO) configuration is proposed for high imaging sensitivity. A significant advantage of the proposed LMR sensor is that can achieve sharp resonance curves for both the transverse electric (TE) and transverse magnetic (TM) polarizations while the traditional surface plasmon resonance (SPR) sensor can only support TM polarizations. Through theoretical analysis, we found that the imaging sensitivity can be improved to 6438 RIU-1 (ns=1.330) and 6695 RIU-1 (ns=1.340) for TE and TM polarizations, respectively. It is an existing improvement of about 85.84 times and 11.5 times correspond to the single ITO-based LMR sensor without TMDs, respectively. This article reveals the design rules of the LMR sensor after system research, which provides guidance for further research and applied in environmental monitoring, biomolecules inspection, and so on.

Human health and ecological environment are badly affected due to oil pollution. A novel strategy for identifying oil pollutants has been proposed based on generic modular design. A total of three modules are included in the oil identification strategy and each module is consisted of a series of steps. The different steps of each module were experimented and evaluated by excitation-emission matrix fluorescence spectroscopy data set of oil. The experimental results show that the average accuracy with 13.6% was improved by using the histogram equalization than using thresholding in module 1. The average accuracy with 5% was improved by using the low-order Zernike moments than using high-order Zernike moments in module 2. The average accuracy with 28.9% was improved by using angle similarity measure in the nearest-neighbor classifier compared to the other six in module 3. The optimal accuracy with 95% was obtained by combining the margin features of excitation-emission matrix fluorescence spectroscopy extracted by low-order Zernike moments with the nearest-neighbor classifier applied to angle similarity measure. The combination also has a good specificity and sensitivity. The results provide references for identifying oil pollutants.