Pt-Ni core-shell structure with Pt-skin and electronic effect on catalytic performance

In order to improve the catalytic performance of the nitrobenzene hydrogenation rearrangement to prepare p-aminophenol,a bimetallic Pt-Ni/C(PNC)catalyst was synthesized.Taking advantage of the synergistic effect of Ni and Pt to enhance product selectivity and catalytic performance stability,the electrons in Ni are moved to Pt by the electron effect,which affects the catalyst’s ability to activate H_(2)as well as the amount of hydrogen activated.Furthermore,due to the strong Pt(5d)-Ni(3d)coupling effect,Ni can effectively maintain Pt stability in the acidic system and reduce Pt dissolution.The stability of the PNC can be found to be greatly enhanced compared to the Pt/C(PC)catalyst,and p-aminophenol selectivity is greatly enhanced,showing excellent catalytic performance.

Sand flux estimation during a sand-dust storm at Tazhong area of Taklimakan Desert, China

In this paper, the sand transport during a sand-dust storm in the Tazhong area of the central Taklimakan Desert from 11：29 to 23：56 on July 19, 2008 was observed and measured in real time. The sand flux at Tazhong was estimated using sand transport empirical formulas. The critical friction velocity at Tazhong was 0.24 m/s and the functional relation between the wind speed and sediment discharge at the height of 2 m was established. It was also found that the calculated values by Lettau＇s sediment discharge formula were close to those of the instrument measurements. The horizontal sand flux and the vertical sand flux during this sand-dust storm at Tazhong were respectively 258.67×10-4 kg/（m·s） and 40.07×10-7 kg/（m2·s）.

Nano Ag-enhanced photoelectric conversion efficiency in all-inorganic,hole-transporting-layer-free CsPbIBr_(2) perovskite solar cells

All-inorganic,hole-transporting-layer-free CsPbIBr_(2)perovskite solar cells have great potential for development,but their device performance needs to be further improved.Recently,metal nanostructures have been successfully applied in the field of solar cells to improve their performance.Nano Ag-enhanced power conversion efficiency(PCE)in one CsPbIBr_(2)perovskite solar cell utilizing localized surface plasmons of Ag nanoparticles(NPs)on the surface has been researched experimentally and by simulation in this paper.The localized surface plasmon resonance of Ag NPs has a near-field enhancement effect,which is expected to improve the light absorption of CsPbIBr_(2)perovskite photovoltaic devices.In addition,Ag NPs have a forward-scattering effect on the incident light,which can also improve the performance of CsPbIBr_(2)-based perovskite photovoltaic devices.By directly assembling Ag NPs(with a size of about 150 nm)on the surface of fluorine-doped tin oxide it is found when the particle surface coverage is 10%,the CsPbIBr_(2)perovskite photovoltaic device achieves a best PCE of 2.7%,which is 9.76%higher than that of the control group.Without changing any existing structure in the ready-made solar cell,this facile and efficient method has huge applications.To the best of our knowledge,this paper is the first report on nano Ag-enhanced photoelectric conversion efficiency in this kind of CsPbIBr_(2)perovskite solar cell.

Numerical simulation of gap effect in supersonic flows

The gap effect is a key factor in the design of the heat sealing in super- sonic vehicles subjected to an aerodynamic heat load. Built on S-A turbulence model and Roe discrete format, the aerodynamic environment around a gap on the surface of a supersonic aircraft was simulated by the finite volume method. As the presented results indicate, the gap effect depends not only on the attack angle, but also on the Mach number.

Event Temporal Relation Extraction with Attention Mechanism and Graph Neural Network

Event temporal relation extraction is an important part of natural language processing.Many models are being used in this task with the development of deep learning.However,most of the existing methods cannot accurately obtain the degree of association between different tokens and events,and event-related information cannot be effectively integrated.In this paper,we propose an event information integration model that integrates event information through multilayer bidirectional long short-term memory(Bi-LSTM)and attention mechanism.Although the above scheme can improve the extraction performance,it can still be further optimized.To further improve the performance of the previous scheme,we propose a novel relational graph attention network that incorporates edge attributes.In this approach,we first build a semantic dependency graph through dependency parsing,model a semantic graph that considers the edges’attributes by using top-k attention mechanisms to learn hidden semantic contextual representations,and finally predict event temporal relations.We evaluate proposed models on the TimeBank-Dense dataset.Compared to previous baselines,the Micro-F1 scores obtained by our models improve by 3.9%and 14.5%,respectively.