Isoflavonoids from Astragalus membranaceus Hairy Roots

Chemistry of Natural Compounds -     

Electro-assisted Molecular Assembly Giving Atomic-Scale Catalytic Active-Site Detection

The artificially accurate design of nonmetal electrocatalysts’ active site has been a huge challenge because no pure active species with the specific structure could be strictly controlled by traditional synthetic methods. Species with a multiconfiguration in the catalyst hinder identification of the active site and the subsequent comprehension of the reaction mechanism. We have developed a novel electro-assisted molecular assembly strategy to obtain a pure pentagon ring on perfect graphene avoiding other reconstructed structures. More importantly, the active atom was confirmed by the subtle passivation process as the topmost carbon atom. Recognition of the carbon-defect electrocatalysis reaction mechanism was first downsized to the single-atom scale from the experimental perspective. It is expected that this innovative electro-assisted molecular assembly strategy could be extensively applied in the active structure-controlled synthesis of nonmetal electrocatalysts and verification of the exact active atom.     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.     

动力学模态分解方法重构及预测流场误差分析

利用动力学模态分解(dynamic mode decomposition,DMD)方法可以实现非定常流场的分解、重构和预测,但该方法重构和预测流场的误差需要给出定量分析.鉴于此,提出了定量描述动力学模态分解重构和预测流场的误差分析方法,以雷诺数Re=80的圆柱绕流二维流场数值模拟结果为例,研究了非线性流动和周期性流场重构和预测误差的动态变化情况.结果表明:依据能量大小确定的模态反映了流场的主要相干结构;低频、低增长/衰减率和大尺度的相干结构能量占比大,对流场的影响较大;DMD方法可以准确重构非线性和周期性变化流场,重构的误差小于10-10,预测流场的误差较重构流场出现跳跃增大现象;DMD方法预测非线性变化流场的误差在样本时间区间内较小(小于10-3),超出样本区间误差的发展急剧增大,变化情况依赖于数据样本;预测周期性流场的误差稳定在10-4左右.     

模具结构对连续纤维增强热塑性复合材料性能的影响

采用自行设计的两种不同结构的熔融浸渍模具制备了连续玻璃纤维增强聚丙烯预浸带，测试了模具结构对预浸带的孔隙率、纤维断裂率、界面形貌、纤维分散均匀度和拉伸强度的影响，建立了纤维浸渍模型和纤维断裂模型，并通过理论模型对预浸带的孔隙率和断裂率进行理论预测。结果表明，本文建立的数学模型能够有效预测预浸带的浸渍程度和纤维断裂率，可用于浸渍模具结构的优化设计；在本文范围内，与波浪形模具相比，斜齿形模具的多楔形区结构可以有效地降低预浸带孔隙率和提升纤维分散程度；波浪形模具的流道圆角半径较大，楔形区个数较少，与斜齿形模具相比，可有效降低纤维断裂率并提升拉伸性能。     

实验动物行业兽医现状分析

实验动物行业中,兽医体现在实验动物相关工作中的每一个环节,包括实验动物的日常管理、动物实验的设计、实验过程中动物健康保障和护理、实验动物福利的监督和管理、动物实验技术的应用、实验动物取材、施行安死术等。通过参阅相关文献资料,结合自身工作总结,就目前实验动物兽医现状进行分析,供各位同仁以参考。     

创新文化竞争力国际比较研究

提升中国创新文化国际竞争力,是全面塑造发展新优势的关键着力点,对我国建设创新型国家具有基础性、长期性、决定性影响.通过构建创新文化竞争力指标体系,选取GII创新指数排名和GDP总量排名均为前20的国家作为研究对象,运用主成分分析法对创新文化国际竞争力进行评价,研究发现:①从综合竞争力水平来看,英国、荷兰、美国、瑞士处于第一梯队,德国、加拿大、法国处于第二梯队,中国、韩国、日本为第三梯队;②从竞争力构成要素来看,中国创新文化可持续发展能力和国家创新驱动力具有相对竞争优势,发展基础力和创新型产业支撑力亟待提升,创新文化吸引力也存在进步空间.为此,提出完善创新文化发展的基础条件、讲好中国故事、加大要素投入等管理启示,以期为提升中国创新文化国际竞争力,建设创新型国家提供针对性建议.     

Space-Confined Atomic Clusters Catalyze Superassembly of Silicon Nanodots within Carbon Frameworks for Use in Lithium-Ion Batteries

Incorporating nanoscale Si into a carbon matrix with high dispersity is desirable for the preparation of lithium-ion batteries (LIBs) but remains challenging. A space-confined catalytic strategy is proposed for direct superassembly of Si nanodots within a carbon (Si NDs⊂C) framework by copyrolysis of triphenyltin hydride (TPT) and diphenylsilane (DPS), where Sn atomic clusters created from TPT pyrolysis serve as the catalyst for DPS pyrolysis and Si catalytic growth. The use of Sn atomic cluster catalysts alters the reaction pathway to avoid SiC generation and enable formation of Si NDs with reduced dimensions. A typical Si NDs⊂C framework demonstrates a remarkable comprehensive performance comparable to other Si-based high-performance half LIBs, and higher energy densities compared to commercial full LIBs, as a consequence of the high dispersity of Si NDs with low lithiation stress. Supported by mechanic simulations, this study paves the way for construction of Si/C composites suitable for applications in future energy technologies.