MoS2/g-C3N4复合催化剂的制备及CdSe量子点敏化产氢性能研究

太阳能光催化分解水制氢被认为是从根本上解决能源与环境问题较为理想的途径之一。在以尿素为原料制得石墨相氮化碳(g-C_3N_4)的基础之上,采用简单的低温溶液反应法将二硫化钼(MoS_2)与石墨相氮化碳(g-C_3N_4)复合得到复合催化剂MoS_2/g-C_3N_4,并利用透射电子显微镜(TEM)、X射线衍射(XRD)、紫外-可见漫反射(DRS)、傅里叶变换红外光谱(FT-IR)和荧光光谱等对该复合光催化剂的组成、形貌和光物理性能进行了表征;进而以CdSe量子点为光敏剂,三乙醇胺(TEOA)为牺牲剂,构建了不含贵金属的三组分光催化产氢体系,并对体系pH值、CdSe量子点浓度等对产氢性能的影响进行了研究。结果表明:将MoS_2纳米颗粒负载到g-C_3N_4上可使g-C_3N_4的光催化产氢性能得到显著提高。当MoS_2负载量为7%(质量比)时,在最佳的条件下(pH=9.0,CdSe量子点的体积为25mL),最大产氢速率达到了141.74μmol·h-1,6h的产氢总量达到了212.61μmol。最后,结合荧光猝灭实验,推测了该体系的产氢机理。     

Tensile Strength Evolution and Damage Mechanisms of Al–Si Piston Alloy at Different Temperatures

The Al–Si piston alloys always bear different temperatures because of its peculiar component structure and service condition. Therefore, the tensile strength, elongation to fracture, and corresponding damage mechanisms of Al12SiCuNiMg piston alloys (ASPA) have been investigated with in situ technique at different temperatures. The tensile properties show two‐stage tendencies: the former stage (25–280 °C) is determined by easily broken phases with inherent brittleness (such as primary Si), and the fracture behavior presents rapid brittle fracture after reaching the critical stress (about 430 MPa, based on in situ technique and the elastic stress field model). The later one (280–425 °C) is dominated by particles debonding and θphase coarsening. The plastic deformation behavior, dynamic recovery, and flow process become more significant on account of thermal activation. The Considère criterion h = K indicates that the transition of damage behaviors from insufficient local strength to insufficient matrix strength and the corresponding failure model shifts from brittle to ductile fracture. Based on the damage mechanisms, the elastic field model and thermal activation relation model have been established to characterize the strength of the ASPA at different temperature ranges.

     

The Influence of Carbon Nitride Nanosheets Doping on the Crystalline Formation of MIL‐88B(Fe) and the Photocatalytic Activities

In this research, bulk graphitic carbon nitride (g‐C₃N₄) is exfoliated and transferred to the carbon nitride nanosheets (CNNSs), which are then coupled with MIL‐88B(Fe) to form the hybrid. From the results of the powder X‐ray diffraction, scanning electronic microscopy and thermogravimetric analysis, it is found that the doping of CNNSs on the surface of MIL‐88(Fe) could maintain the basic structure of MIL‐88B(Fe), and the smaller dimension of CNNSs might influence the crystallization process of metal‐organic frameworks (MOFs) compared to bulk g‐C₃N₄. Besides, the effects of the CNNSs incorporation on photocatalysis are also investigated. Through the photoluminescence spectra, electrochemical measurements, and photocatalytic experiments, the hybrid containing 6% CNNSs is certified to possess the highest catalytic activity to degrade methylene blue and reduce Cr(VI) under visible light. The improvement of the photocatalytic performance can be attributed to the matched energy level which favors the formation of the heterojunctions. Besides, it promotes the charge migration such that the contact between MOFs and CNNSs is more intimate, which can be inferred from the electronic microscopy images. Finally, a possible photocatalytic mechanism is put forward by the relative calculation and the employment of the scavengers to trap the active species.     

Natural Plant Materials as Dielectric Layer for Highly Sensitive Flexible Electronic Skin

Nature has long offered human beings with useful materials. Herein, plant materials including flowers and leaves have been directly used as the dielectric material in flexible capacitive electronic skin (e‐skin), which simply consists of a dried flower petal or leaf sandwiched by two flexible electrodes. The plant material is a 3D cell wall network which plays like a compressible metamaterial that elastically collapses upon pressing plus some specific surface structures, and thus the device can sensitively respond to pressure. The device works over a broad‐pressure range from 0.6 Pa to 115 kPa with a maximum sensitivity of 1.54 kPa^?1, and shows high stability over 5000 cyclic pressings or bends. The natural‐material‐based e‐skin has been applied in touch sensing, motion monitoring, gas flow detection, and the spatial distribution of pressure. As the foam‐like structure is ubiquitous in plants, a general strategy for a green, cost‐effective, and scalable approach to make flexible e‐skins is offered here.     

Highly uniform ultrasound-sensitive nanospheres produced by a pH-induced micelle-to-vesicle transition for tumor-targeted drug delivery

Although gas-filled microbubbles with high echogenicity are widely applied inclinical ultrasonography, the micron scale particle size impedes their use in the treatment of solid tumors,which are accessible to objects less than several hundred nanometers. We herein propose an unusual approach involving apH-induced core–shell micelle-to-vesicle transition to prepare ultrasound-sensitive polymeric nanospheres (polymersomes in structure) possessing multiple features, including nanosize, monodispersity, and incorporation of a phase-transitional imaging agent into the aqueous lumen. These features are not achievable via the conventional double-emulsion method for polymersome preparation. The nanospheres were constructed based on a novel triblock copolymer with dual pH sensitivity. The liquid-to-gas phase transition of the imaging agent induced by external low-frequency ultrasound may destroy the nanospheres for a rapid drug release, with simultaneous tissue-penetrating drug delivery inside a tumor. These effects may provide new opportunities for the development of an effective cancer therapy with few adverse effects.

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航天器振动试验控制技术进展

航天器对恶劣动力学环境的适应能力直接关系到整个航天飞行任务的成败,振动试验控制技术是动力学环境试验的关键环节.本文分析了近年来国内外航天器振动试验设备和振动控制算法的研发动态、基本原理和关键技术达到的水平.提出了跟踪研究的基本思路,途径及建议.     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

Container-Based Internet of Vehicles Edge Application Migration Mechanism

Internet of Vehicles (IoV) applications integrating with edge computing will significantly drive the growth of IoV. However, the contradiction between the high-speed mobility of vehicles, the delay sensitivity of corresponding IoV applications and the limited coverage and resource capacity of distributed edge servers will pose challenges to the service continuity and stability of IoV applications. IoV application migration is a promising solution that can be supported by application containerization, a technology forseamless cross-edge-server application migration without user perception. Therefore, this paper proposes the container-based IoV edge application migration mechanism, consisting of three parts. The first is the migration trigger determination algorithm for cross-border migration and service degradation migration, respectively, based on trajectory prediction and traffic awareness to improve the determination accuracy. The second is the migration target decision calculation model for minimizing the average migration time and maximizing the average service time to reduce migration times and improve the stability and adaptability of migration decisions. The third is the migration decision algorithm based on the improved artificial bee colony algorithm to avoid local optimal migration decisions. Simulation results show that the proposed migration mechanism can reduce migration times, reduce average migration time, improve average service time and enhance the stability and adaptability of IoV application services.