High intrinsic phase stability of ultrathin 2M WS2.

Metallic 2M or 1T'-phase transition metal dichalcogenides (TMDs) attract increasing interests owing to their fascinating physicochemical properties, such as superconductivity, optical nonlinearity, and enhanced electrochemical activity. However, these TMDs are metastable and tend to transform to the thermodynamically stable 2H phase. In this study, through systematic investigation and theoretical simulation of phase change of 2M WS2, we demonstrate that ultrathin 2M WS2 has significantly higher intrinsic thermal stabilities than the bulk counterparts. The 2M-to-2H phase transition temperature increases from 120 °C to 210 °C in the air as thickness of WS2 is reduced from bulk to bilayer. Monolayered 1T' WS2 can withstand temperatures up to 350 °C in the air before being oxidized, and up to 450 °C in argon atmosphere before transforming to 1H phase. The higher stability of thinner 2M WS2 is attributed to stiffened intralayer bonds, enhanced thermal conductivity and higher average barrier per layer during the layer(s)-by-layer(s) phase transition process. The observed high intrinsic phase stability can expand the practical applications of ultrathin 2M TMDs.

Physical Education Teaching Strategy under Internet of Things Data Computing Intelligence Analysis.

Racket sports such as tennis are amongst the most popular recreational sports activities. Optimizing tennis teaching methods and improving teaching modes can effectively improve the teaching quality of tennis. In this study, a video and image action recognition system based on image processing techniques and Internet of things is developed to overcome the shortcomings of the traditional tennis teaching methods. To validate its performance, the students of tennis courses are divided into experimental group and control group, respectively. The control group is taught by using the traditional tennis teaching method whereas the experimental group is taught by using the IoT video and image recognition teaching system. Three factors of students including service throwing height, arm elbow angle, and knee bending angles of both groups are measured and compared with those of world elite tennis players. The results show that the students' serving abilities in the experimental group are significantly improved using the video and image recognition system based on IoT, and they are better than those of the students in the control group. The proposed video and image processing technique can be applied in students' physical education and can be employed to provide the basis for the innovation of tennis teaching strategies in physical education.