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The imprinted polymers were prepared to absorb dichlorophen (DCP) by using mesoporous silica with ordered pores and high specific surface area. Both scanning electron microscopy and transmission electron microscopy results suggested that the mesoporous silica nanosphere pores had a periodic distribution. The imprinted layer of polymers was thin and uniform. The adsorption experiments showed that the adsorption of imprinted polymers was obviously improved due to the presence of mesoporous structure. The maximum adsorption capacity of MSNs@MIPs at 318 K was 91.1 mg/g, and the adsorption process rapidly reached the equilibrium within 40 min. The adsorption isotherm was well fitted by the Freundlich isotherm model, indicating that multimolecular layer adsorption mechanism governs the adsorption of DCP by the polymers. The adsorption of MSNs@MIPs complied with pseudo-second-order kinetic model. Both selective and regenerative experiments demonstrated that MSNs@MIPs can be successfully applied for selective adsorption of DCP.

Although negative thermal expansion (NTE) materials provide a new strategy to overcome the thermal-quenching phenomenon among rare earth doped luminescent materials, the overall weak upconversion luminescence still restricts their application in the field of optical temperature sensing. Herein, giant enhancement of anti-quenching upconversion luminescence is achieved in the NTE Sc2W3O12:Er3+/Yb3+ phosphors by (KMg)3+ impurity doping, and the phosphors are used for the construction of an all-fiber temperature sensing (AFTS) system. Compared to the upconversion luminescence of the Sc2W3O12:Er3+/Yb3+ phosphors at room temperature, the synergistic effect of impurity doping and NTE characterstics results in a 6000-fold enhancement of the upconversion luminescence of the (KMg)3+ doped Sc2W3O12:Er3+/Yb3+ phosphors at 573 K. A single-point tip temperature sensor was constructed based on the fluorescence luminescence intensity ratio (FIR) technology and the corresponding self-calibrated curves were obtained with a regression coefficient of 0.9996. The potential application of the constructed AFTS system was demonstrated in the real-time temperature monitoring of a CPU chip and a thermostat bath. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) has good potential to promote technology-enhanced learning. Students can benefit from immersive visualization and intuitive interaction in their learning of abstract concepts, complex structures, and dynamic processes. This paper is interested in evaluating the effects of VR learning games in a Virtual and Augmented Reality Technology-Enhanced Learning (VARTeL) environment within an engineering education setting. A VARTeL flipped classroom is established in the HIVE learning hub at Nanyang Technological University (NTU) Singapore for the immersive and interactive learning. Experiments are designed for the university students conducting the learning, with three interactive and immersive VR games related to science, technology, engineering and mathematics (STEM), i.e., virtual cells, a virtual F1 racing car, and vector geometry. These VR games are a part of the VARTeL apps designed in-house at NTU for STEM education. Quantitative and qualitative analyses are performed. A total of 156 students from Mechanical Engineering participated in the experiment. There are 15 participants selected for an interview after the experiment. Pre-tests and post-tests are performed using two different models, the developed VARTeL and the modified Technology-Rich Outcome-Focused Learning Environment Inventory (TROFLEI), in order to measure the efficiency of the VARTeL environment in Higher Education. Significant improvements of about 24.8% are observed for the post-tests over the pre-tests, which illustrate the effectiveness of the VARTeL for Engineering education. Details of the VR simulation games, methods of data collection, data analyses, as well as the experiment results are discussed. It is observed from the results that all the underlying scales of the modified TROFLEI are above the threshold for the 'Good' category, indicating that a very reliable questionnaire is designed in this research. The mean 'Ideal' values are about 0.7–2.6% higher than the mean 'Actual' values. The limitations of the experiment and future works with recommendations are also presented in this paper. [ABSTRACT FROM AUTHOR]