Xi'an Jiaotong University

About: Xi'an Jiaotong University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Heat transfer & Dielectric. The organization has 85440 authors who have published 99682 publications receiving 1579683 citations. The organization is also known as: '''Xi'an Jiaotong University''' & Xi'an Jiao Tong University.

A high dielectric constant non-fullerene acceptor for efficient bulk-heterojunction organic solar cells

Abstract: The majority of organic semiconductors have a low relative dielectric constant (er 6) has attracted a very limited attention. Moreover, high performance OSCs based on high dielectric constant photovoltaic materials are still in their infancy. Herein, we report an oligoethylene oxide side chain-containing non-fullerene acceptor (ITIC-OE) with a high relative dielectric constant of er ≈ 9.4, which is two times larger than that of its alkyl chain-containing counterpart ITIC. Encouragingly, the OSCs based on ITIC-OE show a high power conversion efficiency of 8.5%, which is the highest value for OSCs that employ high dielectric constant materials. Nevertheless, this value is lower than those of ITIC-based control devices. The less phase-separated morphology in blend films due to the reduced crystallinity of ITIC-OE and the too good miscibility between PBDB-T and ITIC-OE are responsible for the lower device performance. This work suggests additional prerequisites to make high dielectric constants play a significant role in OSCs.

Does wireless sensor network scale? A measurement study on GreenOrbs

Abstract: In spite of the remarkable efforts the community put to build the sensor systems, an essential question still remains unclear at the system level, motivating us to explore the answer from a point of real-world deployment view. Does the wireless sensor network really scale? We present findings from a large scale operating sensor network system, GreenOrbs, with up to 330 nodes deployed in the forest. We instrument such an operating network throughout the protocol stack and present observations across layers in the network. Based on our findings from the system measurement, we propose and make initial efforts to validate three conjectures that give potential guidelines for future designs of large scale sensor networks. (1) A small portion of nodes bottlenecks the entire network, and most of the existing network indicators may not accurately capture them. (2) The network dynamics mainly come from the inherent concurrency of network operations instead of environment changes. (3) The environment, although the dynamics are not as significant as we assumed, has an unpredictable impact on the sensor network. We suggest that an event-based routing structure can be trained optimal and thus better adapt to the wild environment when building a large scale sensor network.

Boosted binary Harris hawks optimizer and feature selection

Abstract: Feature selection is a required preprocess stage in most of the data mining tasks. This paper presents an improved Harris hawks optimization (HHO) to find high-quality solutions for global optimization and feature selection tasks. This method is an efficient optimizer inspired by the behaviors of Harris' hawks, which try to catch the rabbits. In some cases, the original version tends to stagnate to the local optimum solutions. Hence, a novel HHO called IHHO is proposed by embedding the salp swarm algorithm (SSA) into the original HHO to improve the search ability of the optimizer and expand the application fields. The update stage in the HHO optimizer, which is performed to update each hawk, is divided into three phases: adjusting population based on SSA to generate SSA-based population, generating hybrid individuals according to SSA-based individual and HHO-based individual, and updating search agent in the light of greedy selection and HHO’s mechanisms. A large group of experiments on many functions is carried out to investigate the efficacy of the proposed optimizer. Based on the overall results, the proposed IHHO can provide a faster convergence speed and maintain a better balance between exploration and exploitation. Moreover, according to the proposed continuous IHHO, a more stable binary IHHO is also constructed as a wrapper-based feature selection (FS) approach. We compare the resulting binary IHHO with other FS methods using well-known benchmark datasets provided by UCI. The experimental results reveal that the proposed IHHO has better accuracy rates over other compared wrapper FS methods. Overall research and analysis confirm the improvement in IHHO because of the suitable exploration capability of SSA.

Direct observation of chemical short-range order in a medium-entropy alloy

Abstract: Complex concentrated solutions of multiple principal elements are being widely investigated as high- or medium-entropy alloys (HEAs or MEAs)1–11, often assuming that these materials have the high configurational entropy of an ideal solution. However, enthalpic interactions among constituent elements are also expected at normal temperatures, resulting in various degrees of local chemical order12–22. Of the local chemical orders that can develop, chemical short-range order (CSRO) is arguably the most difficult to decipher and firm evidence of CSRO in these materials has been missing thus far16,22. Here we discover that, using an appropriate zone axis, micro/nanobeam diffraction, together with atomic-resolution imaging and chemical mapping via transmission electron microscopy, can explicitly reveal CSRO in a face-centred-cubic VCoNi concentrated solution. Our complementary suite of tools provides concrete information about the degree/extent of CSRO, atomic packing configuration and preferential occupancy of neighbouring lattice planes/sites by chemical species. Modelling of the CSRO order parameters and pair correlations over the nearest atomic shells indicates that the CSRO originates from the nearest-neighbour preference towards unlike (V−Co and V−Ni) pairs and avoidance of V−V pairs. Our findings offer a way of identifying CSRO in concentrated solution alloys. We also use atomic strain mapping to demonstrate the dislocation interactions enhanced by the CSROs, clarifying the effects of these CSROs on plasticity mechanisms and mechanical properties upon deformation. Direct experimental evidence of chemical short-range atomic-scale ordering (CSRO) in a VCoNi medium-entropy alloy is provided via diffraction and electron microscopy, analysed from specific crystallographic directions.