RESUMEN
Dynamic luminescence behavior by external stimuli, such as light, thermal field, electricity, mechanical force, etc., endows the materials with great promise in optoelectronic applications. Upon thermal stimulus, the emission is inevitably quenched due to intensive non-radiative transition, especially for phosphorescence at high temperature. Herein, we report an abnormal thermally-stimulated phosphorescence behavior in a series of organic phosphors. As temperature changes from 198 to 343 K, the phosphorescence at around 479 nm gradually enhances for the model phosphor, of which the phosphorescent colors are tuned from yellow to cyan-blue. Furthermore, we demonstrate the potential applications of such dynamic emission for smart dyes and colorful afterglow displays. Our results would initiate the exploration of dynamic high-temperature phosphorescence for applications in smart optoelectronics. This finding not only contributes to an in-depth understanding of the thermally-stimulated phosphorescence, but also paves the way toward the development of smart materials for applications in optoelectronics.
RESUMEN
Clustering is considered one of the most powerful tools for analyzing gene expression data. Although clustering has been extensively studied, a problem remains significant: iterative techniques like k-means clustering are especially sensitive to initial starting conditions. An unreasonable selection of initial points leads to problems including local minima and massive computation. In this paper, a spatial contiguity analysis-based approach is proposed, aiming to solve this problem. It employs principal component analysis (PCA) to identify data points that are likely extracted from different clusters as initial points. This helps to avoid local minima, and accelerates the computation. The effectiveness of the proposed approach was validated on several benchmark datasets.