Alumina ceramics are widely used in many fields such as cutting tools,laser shock materials,roadbed board and refractory.Herein,Al_(2)O_(3)ceramics are prepared by a low-cost pressureless sintering technology,using th...Alumina ceramics are widely used in many fields such as cutting tools,laser shock materials,roadbed board and refractory.Herein,Al_(2)O_(3)ceramics are prepared by a low-cost pressureless sintering technology,using the binary sintering aids of MgO and SiO_(2).The effects of sintering temperature and the ratio of binary sintering aids on the mechanical properties and microstructure of Al_(2)O_(3)ceramics are investigated.A spinel second phase(MgAl_(2)O_(4))is found out by the analysis of the results of XRD and EDS when MgO and SiO_(2)are introduced in the samples.The optimum properties are found when MgO content is 20 wt.%based on the total sintering aids and the sintering temperature is 1550℃.The bending strength and the bulk density reach a maximum value of 314 MPa and 3.73 g/cm^(3),respectively.The addition of appropriate amount of SiO_(2)makes the formation of liquid phase sintering and the removal of large pores.Meanwhile,a small amount of magnesium oxide doping has an effect on the grain refinement from the microstructure of the sample.Therefore,it is believed that MgO and SiO_(2)are the ideal sintering aids for promoting the densification and property of alumina ceramics.展开更多
Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology,the computer-aided drug design techniques have been successfully applied in almost every stage...Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology,the computer-aided drug design techniques have been successfully applied in almost every stage of the drug discovery and development pipeline to speed up the process of research and reduce the cost and risk related to preclinical and clinical trials.Owing to the development of machine learning theory and the accumulation of pharmacological data, the artificial intelligence(AI) technology, as a powerful data mining tool, has cut a figure in various fields of the drug design, such as virtual screening,activity scoring, quantitative structure-activity relationship(QSAR) analysis, de novo drug design, and in silico evaluation of absorption, distribution, metabolism, excretion and toxicity(ADME/T) properties. Although it is still challenging to provide a physical explanation of the AI-based models, it indeed has been acting as a great power to help manipulating the drug discovery through the versatile frameworks. Recently, due to the strong generalization ability and powerful feature extraction capability,deep learning methods have been employed in predicting the molecular properties as well as generating the desired molecules,which will further promote the application of AI technologies in the field of drug design.展开更多
Based on the supercritical ＂wingl＂ which was released in the DPW-III conference, multi-objective optimization has been done to increase the lift-drag ratio at cruise condition and improve transonic buffet boundary a...Based on the supercritical ＂wingl＂ which was released in the DPW-III conference, multi-objective optimization has been done to increase the lift-drag ratio at cruise condition and improve transonic buffet boundary and drag-rise performance. Hicks-Henne shape functions are used to represent the bump shape. In the design optimization to increase lift-drag ratio, the objectives involve the cruise point and three other off-design points nearby. In the other optimization process to improve buffet and drag-rise performance, three buffet onset points near the cruise point and one drag-rise point are selected as the design points. Non-dominating sort genetic algorithm II （NSGA-II） is used in both processes. Additionally, individual analysis for every selected point on the Pareto frontier is conducted in order to avoid local convergence and achieve global optimum. Re- sults of optimization for aerodynamic efficiency show a decrease of 11 counts in drag at the cruise point. Drag at nearby off-design points are also reduced to some extent. Similar approaches are made to improve buffet and drag-rise characteristics, resulting in significant improvements in both ways.展开更多
基金Projects(11772207,U2130128)supported by the National Natural Science Foundation of ChinaProjects(E2019210042,E2017210065)supported by the Natural Science Foundation of Hebei Province,China+3 种基金Project(QN2019137)supported by the Natural Science Foundation of the Hebei Education Department,ChinaProject(A2019210204)supported by the Natural Science Foundation of Hebei Province for Distinguished Young Scholars,ChinaProject(216Z4302G)supported by Central Government Guiding Local Science and Technology Development,ChinaProject supported by Youth Top-notch Talents Supporting Plan of Hebei Province,China。
文摘Alumina ceramics are widely used in many fields such as cutting tools,laser shock materials,roadbed board and refractory.Herein,Al_(2)O_(3)ceramics are prepared by a low-cost pressureless sintering technology,using the binary sintering aids of MgO and SiO_(2).The effects of sintering temperature and the ratio of binary sintering aids on the mechanical properties and microstructure of Al_(2)O_(3)ceramics are investigated.A spinel second phase(MgAl_(2)O_(4))is found out by the analysis of the results of XRD and EDS when MgO and SiO_(2)are introduced in the samples.The optimum properties are found when MgO content is 20 wt.%based on the total sintering aids and the sintering temperature is 1550℃.The bending strength and the bulk density reach a maximum value of 314 MPa and 3.73 g/cm^(3),respectively.The addition of appropriate amount of SiO_(2)makes the formation of liquid phase sintering and the removal of large pores.Meanwhile,a small amount of magnesium oxide doping has an effect on the grain refinement from the microstructure of the sample.Therefore,it is believed that MgO and SiO_(2)are the ideal sintering aids for promoting the densification and property of alumina ceramics.
基金supported by the National Natural Science Foundation of China (21210003 and 81230076 to H.J., 81773634 to M.Z. and 81430084 to K.C.)the “Personalized Medicines-Molecular Signature-based Drug Discovery and Development”, Strategic Priority Research Program of the Chinese Academy of Sciences (XDA12050201 to M.Z.)+1 种基金National Key Research & Development Plan (2016YFC1201003 to M.Z.)the National Basic Research Program (2015CB910304 to X.L.)
文摘Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology,the computer-aided drug design techniques have been successfully applied in almost every stage of the drug discovery and development pipeline to speed up the process of research and reduce the cost and risk related to preclinical and clinical trials.Owing to the development of machine learning theory and the accumulation of pharmacological data, the artificial intelligence(AI) technology, as a powerful data mining tool, has cut a figure in various fields of the drug design, such as virtual screening,activity scoring, quantitative structure-activity relationship(QSAR) analysis, de novo drug design, and in silico evaluation of absorption, distribution, metabolism, excretion and toxicity(ADME/T) properties. Although it is still challenging to provide a physical explanation of the AI-based models, it indeed has been acting as a great power to help manipulating the drug discovery through the versatile frameworks. Recently, due to the strong generalization ability and powerful feature extraction capability,deep learning methods have been employed in predicting the molecular properties as well as generating the desired molecules,which will further promote the application of AI technologies in the field of drug design.
文摘Based on the supercritical ＂wingl＂ which was released in the DPW-III conference, multi-objective optimization has been done to increase the lift-drag ratio at cruise condition and improve transonic buffet boundary and drag-rise performance. Hicks-Henne shape functions are used to represent the bump shape. In the design optimization to increase lift-drag ratio, the objectives involve the cruise point and three other off-design points nearby. In the other optimization process to improve buffet and drag-rise performance, three buffet onset points near the cruise point and one drag-rise point are selected as the design points. Non-dominating sort genetic algorithm II （NSGA-II） is used in both processes. Additionally, individual analysis for every selected point on the Pareto frontier is conducted in order to avoid local convergence and achieve global optimum. Re- sults of optimization for aerodynamic efficiency show a decrease of 11 counts in drag at the cruise point. Drag at nearby off-design points are also reduced to some extent. Similar approaches are made to improve buffet and drag-rise characteristics, resulting in significant improvements in both ways.
