Southwest University of Science and Technology

About: Southwest University of Science and Technology is a education organization based out in Mianyang, China. It is known for research contribution in the topics: Adsorption & Graphene. The organization has 10017 authors who have published 8923 publications receiving 94850 citations. The organization is also known as: Xīnán Kējìdàxué.

Experimental Study on Basic Mechanical Properties of Basalt Fiber Reinforced Concrete.

Abstract: Blending a certain proportion of basalt fiber into concrete improves the toughness of concrete, which prevents cracking and avoids the brittle behaviors. In this paper, the compressive, tensile, and flexural tests of concrete with different basalt fiber contents were carried out. Then the test phenomena, failure modes, and mechanical properties were compared and analyzed to derive the relationship between the basalt fiber contents and mechanical properties. The toughness and crack resistance performance of basalt fiber reinforced concrete were evaluated by the fracture energy, advanced toughness parameters, and characteristic length proposed by Hillerborg. The correlation coefficient of basalt fiber was introduced to establish the calculation formula for mechanical properties of basalt fiber reinforced concrete. The results indicated that basalt fiber significantly improved the toughness and crack resistance performance of concrete. The enhancing effect of the basalt fiber on the compressive strength of concrete is lower than that of tensile strength and flexural strength. Moreover, the improvement effect was the highest with the basalt fiber content was 0.3% and 0.4%.

Colossal permittivity in TiO2 co‐doped by donor Nb and isovalent Zr

Abstract: Effect of isovalent Zr dopant on the colossal permittivity (CP) properties was investigated in (Zr+Nb) co-doped rutile TiO2 ceramics, i.e., Nb0.5%ZrxTi1-xO2. Compared with those of only Nb-doped TiO2, the CP properties of co-doped samples showed better frequency-stability with a lower dielectric loss. Especially, a CP up to 6.4 × 104 and a relatively low dielectric loss (0.029) of x = 2% sample were measured at 1 kHz and room temperature. Moreover, both dielectric permittivity and loss were nearly independent of direct current bias, and measuring temperature from room temperature to around 100 °C. Based on the XPS, the formation of oxygen vacancies was suppressed due to the incorporation of Zr. Furthermore, it induced the enhancement of the conduction activation energy according to the impedance spectroscopy. The results will provide a new routine to achieve a low dielectric loss in the CP materials. This article is protected by copyright. All rights reserved.

The Dynamic Brain Networks of Motor Imagery: Time-Varying Causality Analysis of Scalp EEG.

Abstract: Motor imagery (MI) requires subjects to visualize the requested motor behaviors, which involves a large-scale network that spans multiple brain areas. The corresponding cortical activity reflected on the scalp is characterized by event-related desynchronization (ERD) and then by event-related synchronization (ERS). However, the network mechanisms that account for the dynamic information processing of MI during the ERD and ERS periods remain unknown. Here, we combined ERD/ERS analysis with the dynamic networks in different MI stages (i.e. motor preparation, ERD and ERS) to probe the dynamic processing of MI information. Our results show that specific dynamic network structures correspond to the ERD/ERS evolution patterns. Specifically, ERD mainly shows the contralateral networks, while ERS has the symmetric networks. Moreover, different dynamic network patterns are also revealed between the two types of MIs, in which the left-hand MIs exhibit a relatively less sustained contralateral network, which may be the network mechanism that accounts for the bilateral ERD/ERS observed for the left-hand MIs. Similar to the network topologies, the three MI stages also appear to be characterized by different network properties. The above findings all demonstrate that different MI stages that involve specific brain networks for dynamically processing the MI information.