China Jiliang University

About: China Jiliang University is a education organization based out in Hangzhou, China. It is known for research contribution in the topics: Fiber optic sensor & Optical fiber. The organization has 9291 authors who have published 8932 publications receiving 95279 citations. The organization is also known as: China Institute of Metrology.

Frequency comparative study of coal-fired fly ash acoustic agglomeration.

Abstract: Particulate pollution is main kind of atmospheric pollution. The fine particles are seriously harmful to human health and environment. Acoustic agglomeration is considered as a promising pretreatment technology for fine particle agglomeration. The mechanisms of acoustic agglomeration are very complex and the agglomeration efficiency is affected by many factors. The most important and controversial factor is frequency. Comparative studies between high-frequency and low-frequency sound source to agglomerate coalfired fly ash were carried out to investigate the influence of frequency on agglomeration efficiency. Acoustic agglomeration theoretical analysis, experimental particle size distributions (PSDs) and orthogonal design were examined. The results showed that the 20 kHz high-frequency sound source was not suitable to agglomerate coal-fired fly ash. Only within the size ranging from 0.2 to 0.25 μm the particles agglomerated to adhere together, and the agglomerated particles were smaller than 2.5 μm. The application of low-frequency (1000–1800 Hz) sound source was proved as an advisable pretreatment with the highest agglomeration efficiency of 75.3%, and all the number concentrations within the measuring range decreased. Orthogonal design L16 (4)3 was introduced to determine the optimum frequency and optimize acoustic agglomeration condition. According to the results of orthogonal analysis, frequency was the dominant factor of coal-fired fly ash acoustic agglomeration and the optimum frequency was 1400 Hz.

Improved stability of CsPbBr3 perovskite quantum dots achieved by suppressing interligand proton transfer and applying a polystyrene coating.

Abstract: All-inorganic lead halide perovskite quantum dots (PQDs) have shown great promise for optoelectronic applications due to their unique optical and electrical properties. However, their poor stability against moisture, UV light or thermal attacks greatly hinders their practical applications. One of the reasons for this instability is the proton transfer between oleic acid (OA) and oleylamine (OLA), which induces serious ligand loss. The idea of this work is to prevent the interligand proton transfer by replacing OLA with cetyl trimethylammonium bromide (CTAB) that cannot be protonated. The synthesized CsPbBr3 PQDs in solution show high photoluminescence quantum yields up to 71% and also exhibit higher stability against acetone than the counterparts synthesized using oleylammonium bromide (OLABr). Subsequently, CsPbBr3 PQDs with a peak wavelength of 515 nm (g-CsPbBr3) synthesized using CTAB are further composited with a polymer of carboxyl-functionalized polystyrene (cPS). The composite shows enhanced thermal and moisture stability. It is demonstrated that this green-emitting composite can produce high color gamut (130%) white light-emitting diodes when combined with the K2SiF6:Mn4+ phosphor and a blue InGaN chip, enabling its use in display backlights.

Novel Just-In-Time Learning-Based Soft Sensor Utilizing Non-Gaussian Information

Abstract: This brief develops a novel just-in-time (JIT) learning-based soft sensor for modeling of industrial processes. The recorded data is assumed to exhibit non-Gaussian signal components, which are extracted by a non-Gaussian regression (NGR) technique. Unlike previous work on JIT modeling which uses distance-based similarity measure for local modeling, this brief introduces a new similarity measure for the extracted non-Gaussian components using support vector data description. Based on the similarity measure, a JIT modeling procedure called NGR_JIT is proposed. Application studies on a numerical example as well as an industrial process demonstrate the proposed soft sensor can give better predictive accuracy when the predictor and response sets are non-Gaussian distributed.

∼2 µm Luminescence and energy transfer characteristics in Tm3+/Ho3+co-doped silicate glass

Abstract: A Tm3+/Ho3+ co-doped silicate glass with good thermal stability is prepared by the melt-quenching method. Efficient ∼2 μm emission is observed under 808 nm laser excitation. The infrared emission characteristics and energy transfer mechanism are investigated. To obtain efficient ∼2 μm emission, the optimized concentration ratio of Tm3+ to Ho3+ is found to be 0.75:0.4 in the present silicate glass system. Additionally, the energy transfer between Tm3+ and Ho3+ plays an important role in the luminescence mechanism and energy transfer efficiency from Tm3+ to Ho3+ reaches 88%. The emission property together with good thermal property indicates that Tm3+/Ho3+ co-doped silicate glass is a potential kind of laser glass for efficient 2 μm laser.