生物矿化法制备氧化镓颗粒及其性能表征

以蚕丝蛋白为模板,在相对温和的条件下通过生物矿化的手段形成具有特殊形貌的α-GaOOH颗粒,并通过在不同温度下煅烧α-GaOOH得到α-Ga2O3和β-Ga2O3.采用扫描电镜(SEM)、透射电镜(TEM)、X射线衍射仪(XRD)和荧光分光光度计(PL)等手段研究了丝素蛋白多肽和矿化时间对颗粒的影响,对其生物矿化机理进行了初步探讨.结果表明,所制备的β-Ga2O3具有优良的发光特性,丝素蛋白多肽模板以无定形的结构与产物结合在一起,并且经过高温烧结后仍以碳膜的形式包覆在材料的表面.这种碳膜结构对于提高材料的生物学性能起着重要的作用.     

Effects of (Li0.5Sm0.5)/W co-substitution and sintering temperature on the structure and electrical properties of ultrahigh Curie temperature piezoceramics,Ca0.92(Li0.5Sm0.5)0.08Bi2Nb2-xWxO9

With co-substitution of (Li_0.5Sm_0.5) at A site and W at B site, the electrical properties of modified Ca_0.92(Li_0.5Sm_0.5)_0.08Bi₂Nb_2-xW_xO₉ [(CLS)BN-xW, x = 0, 0.015 and 0.03] piezoceramics with ultrahigh Curie temperature (T_C) of > 930 °C were enhanced dramatically. The increased resistivity induced by the co-substitution ensure them to be polarized under an enough high field. Combined with the increase of spontaneous ferroelectric polarization (P_S), the significant enhancements in the piezoelectric, dielectric and ferroelectric properties can be obtained in the composition x = 0.015. Furthermore, the piezoelectric activity (d₃₃) and bulk resistivity (ρ_b) of (CLS)BN-0.015 W can be further enhanced at an appropriate sintering temperature. This optimum composition sintered at 1170 °C shows ultrahigh T_C of ～948 °C, d₃₃ of ～17.3 pC/N and ρ_b of ～6.9 MΩ cm at 600 °C, which are comparable to those of the reported high-temperature Aurivillius piezoceramics with T_C > 850 °C.     

基于发展科学探究能力的高中化学教学实践 ——以"元素周期律"章节为例

基于学生在学习元素周期律时存在的普遍问题改进了教学实践,分析了元素周期律发展学生科学探究能力的价值,设计了四个教学环节——趣味导入,成果展示;分析规律,做出猜想;设计方案,收集证据;梳理模型,迁移应用,并提出了三点针对学生探究能力发展的教学建议.     

负极添加NMP对电池性能的影响

锂离子电池负极浆料中添加N-甲基吡咯烷酮(NMP),在极片加热干燥时不能完全除去.残留的NMP吸附在石墨表面,使得SEI膜与石墨结合不牢固.研究了其对电池性能的影响,结果显示,在电池的循环过程中,SEI膜逐渐脱落,导致电池循环寿命缩短,但对电池的容量、内阻、倍率、存储等初期性能不影响.     

Scanning tunneling spectroscopic study of monolayer 1T-TaS2 and 1T-TaSe2

Nano Research - The isostructural and isoelectronic transition-metal-dichalcogenides 1T-TaS2 and 1T-TaSe2 are layered materials with intricate electronic structures. Combining the molecular beam...     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.