CuPd催化剂调节中间反应能垒提高电催化CO_(2)生成二碳产物的选择性

过度的碳排放已造成了严重的全球环境问题,电催化CO_(2)还原是一种利用间歇性过剩电能将CO_(2)转化为有价值的化学物质的有效策略.在多种CO_(2)还原产物中,二碳(C2)产物(如乙烯、乙醇)因其比一碳产物(如甲酸、甲烷、甲醇)具有更高的能量密度而备受关注.Cu是唯一能用电化学方法将CO_(2)转化为多碳产物的单金属催化剂.如何提高Cu基催化剂上CO_(2)还原为C2产物的效率已引起了极大关注.电催化还原CO_(2)生成C2产物有两个重要步骤:一是参与碳碳偶联反应的CO*中间体的量(*代表中间体吸附在基底表面),二是碳碳偶联步骤的能垒.对于Cu单金属催化剂,虽然其表面碳碳偶联步骤的能垒相对较低,但是Cu对CO_(2)的吸附能力和CO_(2)*加氢能力并不高,导致在Cu表面不能生成足量的CO*中间体参与碳碳偶联反应,因而对C2产物的选择性和活性并不理想.与Cu单金属催化剂相反,在Pd单金属催化剂表面,CO*中间体的形成具有超快的反应动力学,但是CO*易在Pd表面中毒且后续碳碳偶联步骤的能垒极高,使其表面不能生成C2产物.为了充分发挥Cu(碳碳偶联步骤能垒较低)和Pd(CO*形成具有超快反应动力学)的双重优势,本文构建了一种紧密的CuPd(100)界面,以调节中间反应能垒,从而提高C2产率.密度泛函理论(DFT)计算表明,CuPd(100)界面增强了CO_(2)的吸附,且降低了CO_(2)*加氢步骤的能垒,从而能够催化生成更多的CO*中间体参与碳碳偶联反应.且CuPd(100)界面上CO_(2)还原为C2产物的电位决定步骤能垒为0.61 eV,低于Cu(100)表面的(0.72 eV).本文采用了一种简便的湿化学法制备了CuPd(100)界面催化剂.X射线衍射和X射线光电子能谱测试以及扩展X射线吸收精细结构光谱结果表明,合成的是相分离的CuPd双金属催化剂,而非CuPd合金催化剂.同时高分辨透射电镜可以观察到清晰的CuPd(100)界面.由此可见,本文成功合成了CuPd(100)界面催化剂.程序升温脱附实验结果表明,CuPd(100)界面对CO_(2)和CO*的吸附比Cu强,结果与理论预测一致.气体传感实验结果表明,CuPd(100)界面CO_(2)*加氢能力比Cu强.为评估CuPd(100)界面催化剂的催化活性,进行了CO_(2)电化学还原实验.结果表明,在0.1 mol/L的KHCO3电解液中,CuPd(100)界面催化剂在‒1.4 VRHE下,C2产物的法拉第效率为50.3%±1.2%,是同电位下Cu催化剂的(23.6%±1.5%)的2.1倍,C2产物的选择性是Cu催化剂的2.4倍,且具有更高的电流密度和更大的电化学活性面积.本文通过调控中间反应能垒以合理设计铜基CO_(2)还原电催化剂提供了参考.

结构化学课程中基于网络的点群演示教学平台PGLite的开发与实践

介绍了基于网络的分子点群教学演示系统PGLite的开发及应用,分子点群演示系统PGLite具有展示分子结构模型和对称元素的功能,并实现了直接访问网页来操作分子模型的友好界面,构建了结构化学课程分子点群教学平台,帮助学生更好地理解掌握结构化学课程中的分子对称性,切实提高分子点群的教学效果。

Evolutionary Dynamics Modeling of Symbolic Social Network Structure Equilibrium

The use of symbol attributes on the side of symbolic social networks to analyze,understand,and predict the topology,function,and dynamic behaviour of complex networks,and has important theoretical significance for personalized recommendations,attitude prediction,user feature analysis,and clustering and application value.However,due to the huge scale of online social networks,this poses a challenge to traditional symbolic social network analysis methods.Based on the theory of structural equilibrium,this paper studies the evolutionary dynamics of symbolic social networks,proposes the energy function of weak structural equilibrium theory,and uses the evolution of evolutionary algorithms to obtain the weak imbalance of the network.The simulation experiment results show that the calculation method in this paper can get the optimal solution faster.It provides an idea for the study of real and complex social networks.

Vasopressin decreases neuronal apoptosis during cardiopulmonary resuscitation

The American Heart Association and the European Resuscitation Council recently recommend- ed that vasopressin can be used for cardiopulmonary resuscitation, instead of epinephrine. However, the guidelines do not discuss the effects of vasopressin during cerebral resuscitation. In this study, we intraperitoneally injected epinephrine and/or vasopressin during cardiopul- monary resuscitation in a rat model of asphyxial cardiac arrest. The results demonstrated that, compared with epinephrine alone, the pathological damage to nerve cells was lessened, and the levels of c-Iun N-terminal kinase and p38 expression were significantly decreased in the hippo- campus after treatment with vasopressin alone or the vasopressin and epinephrine combination. No significant difference in resuscitation effects was detected between vasopressin alone and the vasopressin and epinephrine combination. These results suggest that vasopressin alone or the vasopressin and epinephrine combination suppress the activation of mitogen-activated protein kinase and c-Iun N-terminal kinase signaling pathways and reduce neuronal apoptosis during cardiopulmonary resuscitation.

Research on Crowdsourcing Price Game Model in Crowd Sensing

Crowd-Sensing is an innovative data acquisition method that combines the perception of mobile devices with the idea of crowdsourcing.It is a new application mode under the development of the Internet of Things.The perceptual data that mobile users can provide is limited.Multiple crowdsourcing parties will share this limited data,but the cost that the crowdsourcing party can pay is limited,and enough mobile users are needed to complete the perceptual task,making the group wisdom is really played.In this process,there is bound to be a game between the crowds and the mobile users.Most of the existing researches consider a group-aware system.A group of mobile users will directly share or compete for the opportunity of the crowd-holders to do tasks and get paid,the behavior of multiple crowd-source parties,and their bilateral interaction with mobile users.The research is not clear enough and there is no targeted research.This paper will model and analyze the dynamic evolution process of crowd sensing perception.Based on the unique characteristics of crowd-source non-cooperative game and crowd-sourced Nash equilibrium,we will develop a perceptual plan for mobile users and use the stability analysis of iterative algorithms to explore a way to better match the capabilities of mobile users and the needs of crowdsourced parties.Our theoretical analysis and simulation results verify the dynamic evolution model of crowdsourcing in group perception and propose a method to improve the efficiency of crowdsourcing.

A New Behavior-Assisted Semantic Recognition Method for Smart Home

In the recent Smart Home(SH)research work,intelligent service recommendation technique based on behavior recognition,it has been extensively preferred by researchers.However,most current research uses the Semantic recognition to construct the user’s basic behavior model.This method is usually restricted by environmental factors,the way these models are built makes it impossible for them to dynamically match the services that might be provided in the user environment.To solve this problem,this paper proposes a Semantic behavior assistance(Semantic behavior assistance,SBA).By joining the semantic model on the intelligent gateway,building an SA model,in this way,a logical Internet networks for smart home is established.At the same time,a behavior assistant method based on SBA model is proposed,among them,the user environment-related entities,sensors,devices,and user-related knowledge models exist in the logical interconnection network of the SH system through the semantic model.In this paper,the data simulation experiment is carried out on the method.The experimental results show that the SBA model is better than the knowledge-based pre-defined model.

Research on Vehicle Routing Problem with Soft Time Windows Based on Hybrid Tabu Search and Scatter Search Algorithm

With the expansion of the application scope of social computing problems,many path problems in real life have evolved from pure path optimization problems to social computing problems that take into account various social attributes,cultures,and the emotional needs of customers.The actual soft time window vehicle routing problem,speeding up the response of customer needs,improving distribution efficiency,and reducing operating costs is the focus of current social computing problems.Therefore,designing fast and effective algorithms to solve this problem has certain theoretical and practical significance.In this paper,considering the time delay problem of customer demand,the compensation problem is given,and the mathematical model of vehicle path problem with soft time window is given.This paper proposes a hybrid tabu search(TS)&scatter search(SS)algorithm for vehicle routing problem with soft time windows(VRPSTW),which mainly embeds the TS dynamic tabu mechanism into the SS algorithm framework.TS uses the scattering of SS to avoid the dependence on the quality of the initial solution,and SS uses the climbing ability of TS improves the ability of optimizing,so that the quality of search for the optimal solution can be significantly improved.The hybrid algorithm is still based on the basic framework of SS.In particular,TS is mainly used for solution improvement and combination to generate new solutions.In the solution process,both the quality and the dispersion of the solution are considered.A simulation experiments verify the influence of the number of vehicles and maximum value of tabu length on solution,parameters’control over the degree of convergence,and the influence of the number of diverse solutions on algorithm performance.Based on the determined parameters,simulation experiment is carried out in this paper to further prove the algorithm feasibility and effectiveness.The results of this paper provide further ideas for solving vehicle routing problems with time windows and improving the efficiency of vehicle routing problems and have strong applicability.

Optimization of Load Balancing Algorithm for Virtual Machine Dynamic Migration under Mobile Cloud Computing

As one of the key technologies of cloud computing,the virtualization technology can virtualize all kinds of resources and integrate them into the unified planning of the cloud computing management platform.The migration of virtual machines is one of the important technologies of virtual machine applications.However,there are still many deficiencies in the implementation of load balancing by virtual machine dynamic migration in cloud computing.Traditional triggering strategy thresholds are mostly fixed.If there is an instantaneous peak,it will cause migration,which will cause a waste of resources.In order to solve this problem,based on improving the dynamic migration framework,this paper proposes node selection optimization algorithm and node load balancing strategy and designs a prediction module,which uses a one-time smooth prediction to avoid the shortcoming of peak load moment.The simulation experiments and conclusions analysis results show that the fusion algorithm has performance advantages obvious.

504例体部恶性实体瘤患者金标植入的探讨(英文)

Objective:The purpose of the study is to investigate the technical points,effects and complications of fiducial marker implantation within target areas before the CyberKnife treatment on body malignant solid tumors.Methods:Five hundred and four cases of patients with body malignant solid tumors accepted fiducial implantation within target areas under CT guidance before the treatment of CyberKnife.Observe the complications and effect.Results:Among the 504 cases,500 cases successfully accepted the implantation(a success rate of 99.2%).158 patients felt pain at the punctured sites and 3 patients had tachycardia.33 patients had abdominal pain after the surgery due to a small amount of bleeding in the needle passage during liver puncturing process.Among the 19 lung cancer patients who accepted lung paracentesis,1 case had light pneumothorax and 1 case got light haemothorax.Among the 453 patients who accepted liver paracentesis,6 had fiducial migration.Conclusion:The method of fiducial implantation within target areas before treating body malignant solid tumor with CyberKnife is minimally invasive and comparatively secure.

Research on Prediction Methods of Prevalence Perception under Information Exposure

With the rapid development of information technology,the explosive growth of data information has become a common challenge and opportunity.Social network services represented by WeChat,Weibo and Twitter,drive a large amount of information due to the continuous spread,evolution and emergence of users through these platforms.The dynamic modeling,analysis,and network information prediction,has very important research and application value,and plays a very important role in the discovery of popular events,personalized information recommendation,and early warning of bad information.For these reasons,this paper proposes an adaptive prediction algorithm for network information transmission.A popularity prediction algorithm is designed to control the transmission trend based on the gray Verhulst model to analyze the law of development and capture popular trends.Experimental simulations show that the proposed perceptual prediction model in this paper has a better fitting effect than the existing models.

Comparison of the dose to lung volume between supine and prone position during treatment planning

Objective The aim of the study was to compare the dose to lung volume in the supine and prone position while designing Cyber Knife treatment plans to treat metastatic tumors in the spinous processes of the thoracic vertebrae, and offer a reference for reducing damage to normal tissues. Methods Nine cases of metastatic tumors in the spinous processes of the thoracic vertebrae were selected, and then we designed treatment plans based on the supine and prone positions and compared the results. Results In contrast with the treatment plan based on the prone position, the one for the supine position required 14862–36337 MU more; the lung D5% was 5.20–7.90 Gy higher; and the lung D20% was 2.61–5.73 Gy higher. The difference of dose to spine volume between the two plans was –2.21–2.67 Gy; to the skin volume was –3.93–7.85 Gy; and to the esophagus was 0.28–6.39 Gy. Conclusion The treatment plan based on the prone position of patients can better protect lung tissues than the one based on the supine position, and can also improve the availability of beams.

The roles of microstructural anisotropy in tribo-corrosion performance of one certain laser cladding Fe-based alloy

Because of the microstructural anisotropy for laser cladding materials,the tribo-corrosion performance can vary significantly with different directions.In this study,one certain Fe-based coating was fabricated by laser cladding.To study the effects of anisotropy,three working surfaces(0°,45°,and 90°to the building direction)were machined from the laser cladding samples;as-cast samples with an approximately homogeneous structure were prepared as controls.The tribo-corrosion tests were conducted in a 3.5 wt%NaCl solution with varying normal loads(5,10,and 15 N).The results demonstrated that the 45°surface has superior friction stability,corrosion resistance,and wear resistance.This was directly related to the crystal orientation and grain boundary density.In addition,a refined microstructure may enhance tribo-corrosion properties by increasing deformation resistance and decreasing surface activity.

Mapping China’s offshore mariculture based on dense time-series optical and radar data

Due to the weak information about cultural targets in the complex marine environment,an omission problem exists in large-scale mariculture extraction using single-view and single-source images.To overcome this problem,we developed a mariculture extraction method that combines dense time-series Sentinel-2 and Sentinel-1 data.A high-precision Chinese mariculture distribution map for 2020 was produced with an overall accuracy of 94.00%and a kappa coefficient of 0.91.The results show that(1)the total area of mariculture was 1173249.22 ha on the national scale,which was significantly larger than the previous studies(459595.70 and 205920.28 ha,respectively),with Shandong Province(39.09%)having the largest proportion;(2)China’s mariculture presented a spatial distribution characteristic of‘Denser North and Sparser South’,and mariculture was centralized in the coastal zones of the northern provinces(60.76%)rather than the southern provinces;(3)the official production statistics and remote sensing-derived mariculture area revealed a highly corresponding trend at the provincial level,with an R2 reaching 0.78,which is much higher than the 0.07 and 0.41 values of the comparison data.The results directly provide data reference for mariculture production estimation and site selection or ideas for mariculture extraction in other regions and globally.