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TiCr2 with adding different amount of Mn (0, 2, 4 and 8 wt.%) alloys have been investigated. All alloys have C14-type main phase (gray color in SEM) and Ti minor phase (dark gray color in SEM). Rietveld fitting results proved that the lattice parameter a and cell volume of C14-type phase decreased with increasing Mn content. The first hydrogenation measurement manifest that all alloys have best activation properties and could be activated without any prior heat treatment and hydrogen exposure. However, introducing Mn led to the decrease of the first hydrogen absorption rate of TiCr2 alloy, which may be due to the decrease of cell volume of C14-type main phase. The first hydrogenation properties at low temperature and effect of air exposure of the alloy were discussed. The results showed that the maximum hydrogen absorption capacity at 0 °C was obviously higher than that at room temperature. In addition, TiCr2 alloy doped with minor amounts of Mn after long-time air exposure showed better hydrogenation performance. This may be due to the Mn additive acting as a deoxidizer. Finally, the first hydrogenation kinetic mechanisms of all alloys at different temperature were also studied by using the rate limiting step.

To solve the problems of traditional flame temperature accurate measurement that requires complex equipment, high cost, and difficulty in popularization, it proposes a method of rapid flame temperature monitoring and estimation based on deep learning. To establish a data training set based on RGB estimation of flame temperature, firstly, ordinary RGB and high-speed infrared cameras were used to capture the combustion process at the same time to obtain RGB images and corresponding temperature fields. Secondly, an adjustable modular network structure is established, which includes a video interpolation network, a flame detection network, and a flame temperature estimation network, and the switch training method is used to train the network. To prevent overfitting, a network training algorithm based on genetic algorithm is proposed, so that the training of the flame temperature estimation network is completed efficiently. Finally, the reliability of the calculation model is verified by a typical high-temperature combustion test of the solid propellant. The results show that the error between the calculated value and the measured temperature is only ±5.73%.

Pedagogical Content Knowledge (PCK) and Professional Learning Community (PLC) are key notions to help understand teacher development for the benefit of student learning. Less understood is the contribution of PLC to PCK. This paper considers the Teaching and Research System in China to be a nationally institutionalised PLC for in-service teacher education. Building on quantitative analysis of a sample of 10,202 teachers, the paper concludes that participation in teaching and research activities within PLCs benefits teachers' PCK. The paper also concludes that building PCK through the Teaching and Research System has potential to counteract regional education inequality. Refereed/Peer-reviewed