水泥沥青胶凝材料的硬化机理研究

分析了一种特殊胶凝材料-水泥沥青胶凝材料的水化硬化机理.采用等温量热法、X射线衍射分析和环境扫描电镜对用阴离子沥青乳液和硅酸盐水泥配制的水泥沥青胶凝材料的水化进程、水化产物组成和微观形貌进行了观察.水泥沥青胶凝材料的水化过程仍然可以分为快速反应期,诱导期、加速期、减速期和衰退期.沥青与水泥之间没有化学反应,没有新的矿物相生成.水泥沥青胶凝材料的水化硬化过程起始于水泥的水化,当水泥的水化反应进入加速期,水化放热速率接近最大时,沥青开始破乳成膜.在水泥沥青胶凝材料硬化体中,水泥的水化产物形成骨架,沥青膜包覆其上,是连续相;两者形成互穿体系.乳化沥青中的乳化剂会延缓水泥的水化过程.     

软水溶蚀作用下水泥粉煤灰硬化浆体微观结构变化

利用MIP,XRD,TG,SEM等试验方法对软水溶蚀作用下水泥粉煤灰硬化浆体的微观结构进行了研究.结果显示水泥粉煤灰硬化浆体遭受软水溶蚀后,表现出一定程度的质量损失和微观结构劣化.180d溶蚀龄期内掺有粉煤灰的硬化浆体劣化程度稍高于纯水泥浆体,但粉煤灰的适量掺入可以延缓硬化浆体微结构出现劣化的趋势.水泥粉煤灰硬化浆体的微观结构稳定性在经受180d的软水溶蚀后并未遭到严重破坏.     

养护温度对微膨胀复合胶凝材料性能的影响

研究了养护温度对微膨胀复合胶凝材料膨胀效能、强度、水化程度及微观构影响.果表明：标准养护条件下（20℃）,晶状钙矾石基本都生长在孔缝中,对膨胀贡献较小,凝胶颗粒状钙矾石对膨胀贡献更大;提高养护温度（40℃）能够促进膨胀剂水化,但发展更快强度限制了膨胀发展,凝胶或微晶状钙矾石对孔隙填充使中等养护温度硬化胶凝材料浆体最为密实;更高养护温度时（60℃）,硬化浆体内部生成了大量粗棒状钙矾石晶体,导致其在水化早期即产生过大膨胀,持续高温高湿环境使少量钙矾石发生分,致使后期限制膨胀率有所降低.适度膨胀对硬化浆体孔构是有益,能够使大孔明显减少,但过大膨胀会对孔构造成不利影响,大孔数量偏多.     

X型超轻点阵结构芯体（I）：概念的提出、材料制备及实验

提出一种新型的超轻点阵芯体结构,在此简称为X型芯体.针对该结构提出一种钢板网冲压-钎焊技术,制备出周期性的X型点阵芯体夹层板.通过压缩和剪切性能测试表明,与具有相同密度的金字塔结构比较,X型点阵芯体结构的压缩和剪切峰值强度均提高约30%,以及更高的幅度的plateau平台.研究表明金字塔点阵中的四根杆通过俩俩交错形成X型芯体结构,杆交错形成的二维结点能有效地提高单元体在压缩和剪切变形中的非弹性屈曲抗力.     

C+Ti双注入钢中纳米抗腐蚀相的形成和抗腐蚀特性

C+Ti注入样品经过腐蚀和点蚀后用透射电子显微镜发现了抗腐蚀的丝状纳米相. 多重电位扫描法研究表明这种相具有抗腐蚀和抗点蚀特性,其腐蚀电流密度下降10～26倍. X射线分析表明这种相为直径10～30 nm的FeTi和FeTi₂相,这种相密集的镶嵌在注入层中,其长度大约为150～320 nm. 腐蚀后用扫描电子显微镜观察到密集的丝状的抗腐蚀和抗点蚀的纳米结构. 这种丝状纳米相是金属碳化物,这些相构成了具有优异抗腐蚀特性的钝化层.     

图案化SiC和SiCN陶瓷微结构的制备

采用毛细管微模塑技术和转移微模塑技术, 以硅片为栽片, 以图案化聚二甲基硅氧烷(PDMS)弹性体为模板, 以聚碳硅烷(PCS)和聚硅氮烷(PSZ)为先驱体, 经过先驱体的渗入、先驱体的交联固化、弹性模板的去除以及图案化先驱体的无机化, 制备了图案化SiC和SiCN陶瓷微结构. 研究结果表明, 所制备的陶瓷微结构的尺寸和形状受模板的图案化尺寸和形状控制. 由于SiC和SiCN非氧化物陶瓷自身的优良性能将使得所制备的图案化SiC和SiCN陶瓷微结构在高温、高压等环境下具有非常广泛的应用前景.     

微波等离子体增强化学气相沉积方法制备碳氮纳米管及其结构表征

利用微波等离子体增强化学气相沉积方法 ,在多孔二氧化硅基底上制备了大面积取向一致的碳氮纳米管薄膜 .采用扫描电子显微镜、透射电子显微镜和能量散射X射线能谱仪分别进行了纳米管的形貌、结构和成分的研究 .结果表明这种纳米管的直径一般为 10 0nm ,长度可达 2 0 μm ,为纳米钟的线性聚合物 .纳米管的成分中同时均匀含有C ,N两种元素 .进一步的X射线光电子能谱结果证明了C与N之间以成键结合 .这预示着一种新的C1-xNx(x =0 .16± 0 .0 1)相出现在纳米管结构中 .     

CRTSⅡ型水泥乳化沥青砂浆静态力学性能发展的微观分析

测试了沪昆高铁江西段现场成型CRTS II型CA砂浆长期力学性能的发展变化,并通过沥青抽滤,水泥热重分析,压汞法和核磁共振等试验方法分析了沥青组分、砂浆内部微观孔隙结构变化,水泥水化程度对砂浆长期力学性能的影响.结果发现:砂浆28 d抗压强度与弹性模量均达到了规范要求,随着龄期延长,砂浆力学性能持续升高,但42 d以后砂浆力学性能增长放缓,水泥的持续水化使得砂浆内部孔隙不断细化,强度上升;养护7 d后,砂浆内沥青含量已经固定,成膜固化过程完成.     

基于SHPB试验的高速铁路CRTSⅡ型CA砂浆动态性能

采用分离式霍普金森压杆(Split Hopkinson Pressure Bar,SHPB)试验研究了高速铁路CRTS II型水泥乳化沥青砂浆(CA砂浆)的动态力学性能,并建立了CRTS II型CA砂浆的动态本构关系模型.结果表明:随着应变率的增大,CRTS II型CA砂浆峰值强度逐渐增加,但增加速率随应变率的增大而减小,当应变率从44.17增加至54.79 s-1和从54.79增加至108.47 s-1时,峰值强度分别增加了初始峰值强度的52.28%和7.5%,弹性模量随应变率的变化规律性较差;应变率越大,破坏时的贯通裂纹越多,碎裂程度越大;CRTS II型CA砂浆的比能量吸收随着应变率的增大而增大.所建立的动态本构模型拟合曲线与试验曲线具有较好的一致性.     

人体颈椎黄韧带中二羟焦磷酸钙和碳羟磷灰石的矿物学成因探讨

从晶体形貌、矿物物相和化学成分等角度表征颈椎黄韧带钙化,并结合病理学探讨其病因、形成机制和钙化进程.研究对2例颈椎黄韧带钙化样品进行了显微红外、拉曼、透射电子显微镜(TEM)、扫描电子显微镜(SEM)和同步辐射X射线衍射(XRD)测试,结果表明,钙化物有柱状、粒状、絮状和球状4种形态;柱状和粒状钙化呈单晶体,晶形较好、边界明显,为三斜晶系二羟焦磷酸钙;絮状和球状钙化呈纳米多晶集合体,主要由B型取代的碳羟磷灰石组成.显微红外和拉曼测试显示在钙化集合体中,二羟焦磷酸钙和碳羟磷灰石2种物相分布不均匀,由中央到外围呈现碳羟磷灰石不断减少,二羟焦磷酸钙不断增多的含量变化趋势.通过对钙化物晶体、集合体形貌、物相及不同物相分布关系的分析,本文认为,颈椎黄韧带的钙化初期,首先形成柱状和粒状二羟焦磷酸钙晶体;钙化后期,钙化集合体发生二羟焦磷酸钙的分解和碳羟磷灰石晶体的沉积,前者为后者提供物质来源;碳羟磷灰石沉积过程中,先由纳米级钙化物形成絮状钙化,后形成球状钙化.     

An electrochemical and microstructural characterization of steel-mortar admixed with corrosion inhibitors

The present research brings new insights on the role of admixed corrosion inhibitors in the processes of cement hydration and rebar corrosion.The admixing of NaCl and the corrosion inhibitors in fresh mortar was found to alter the morphology and microstructure of the hardened mortar at the steel-mortar interfacial region.The admixing of the inhibitors increased the risk of carbonation of cement hydrates at the steel-mortar interfacial region,but partially displaced chloride ions. Chloride and the admixed in...     

Adipocyte extracellular matrix composition, dynamics and role in obesity

The central role of the adipose tissue in lipid metabolism places specific demands on the cell structure of adipocytes. The protein composition and dynamics of the extracellular matrix (ECM) is of crucial importance for the functioning of those cells. Adipogenesis is a bi-phasic process in which the ECM develops from a fibrillar to a laminar structure as cells move from the commitment phase to the growth phase characterized by storage of vast amounts of triglycerides. Mature adipocytes appear to spend a lot of energy on the maintenance of the ECM. ECM remodeling is mediated by a balanced complement of constructive and destructive enzymes together with their enhancers and inhibitors. ECM remodeling is an energy costing process regulated by insulin, by the energy metabolism, and by mechanical forces. In the obese, overgrowth of adipocytes may lead to instability of the ECM, possibly mediated by hypoxia.     

Multivariate Time Series Model with Hierarchical Structure for Over‐Dispersed Discrete Outcomes

In this paper, we propose a multivariate time series model for over‐dispersed discrete data to explore the market structure based on sales count dynamics. We first discuss the microstructure to show that over‐dispersion is inherent in the modeling of market structure based on sales count data. The model is built on the likelihood function induced by decomposing sales count response variables according to products' competitiveness and conditioning on their sum of variables, and it augments them to higher levels by using the Poisson–multinomial relationship in a hierarchical way, represented as a tree structure for the market definition. State space priors are applied to the structured likelihood to develop dynamic generalized linear models for discrete outcomes. For the over‐dispersion problem, gamma compound Poisson variables for product sales counts and Dirichlet compound multinomial variables for their shares are connected in a hierarchical fashion. Instead of the density function of compound distributions, we propose a data augmentation approach for more efficient posterior computations in terms of the generated augmented variables, particularly for generating forecasts and predictive density. We present the empirical application using weekly product sales time series in a store to compare the proposed models accommodating over‐dispersion with alternative no over‐dispersed models by several model selection criteria, including in‐sample fit, out‐of‐sample forecasting errors and information criterion. The empirical results show that the proposed modeling works well for the over‐dispersed models based on compound Poisson variables and they provide improved results compared with models with no consideration of over‐dispersion. Copyright © 2014 John Wiley & Sons, Ltd.     

Model instability in predictive exchange rate regressions

In this paper we aim to improve existing empirical exchange rate models by accounting for uncertainty with respect to the underlying structural representation. Within a flexible Bayesian framework, our modeling approach assumes that different regimes are characterized by commonly used structural exchange rate models, with transitions across regimes being driven by a Markov process. We assume a time-varying transition probability matrix with transition probabilities depending on a measure of the monetary policy stance of the central bank at home and in the USA. We apply this model to a set of eight exchange rates against the US dollar. In a forecasting exercise, we show that model evidence varies over time, and a model approach that takes this empirical evidence seriously yields more accurate density forecasts for most currency pairs considered.     

Structural studies of a phosphatidyl serine-amorphous calcium phosphate complex

A phosphatidyl serine-amorphous calcium phosphate complex has been synthesized as a model of the matrix vesicle system that is associated with the induction of mineral deposition in bone, cartilage and dentine. The complex has been studied using a novel technique of subtractive extended X-ray absorption fine structure (EXAFS). This enables spectra of the components of the molecules to be subtracted from the complex so as to identify the sites of interaction. The results suggest there is a movement in the nitrogen atom of the phosphatidyl serine which approaches the calcium atom in the mineral phase. This interpretation would link the membrane structure of the vesicle to the structure of the mineral in a way that could explain some of its roles in biomineralization. Received 14 November 1997; accepted 23 December 1997     

Thrombospondins: from structure to therapeutics

Cartilage oligomeric matrix protein, also known as thrombospondin-5 (TSP-5), is an extracellular matrix protein found primarily in cartilage and musculoskeletal tissues. TSP-5 is of interest because mutations in the gene cause two skeletal dysplasias, pseudoachondroplasia (PSACH) and multiple epiphyseal dysplasia (MED/EDM1). Both PSACH and EDM1 have a characteristic chondrocyte phenotype distinguished by giant rough endoplasmic reticulum (rER) cisternae containing TSP-5 and other extracellular matrix proteins such as type IX collagen and matrilin-3. The accumulation of proteinaceous material in the rER compromises cellular function and leads to premature chondrocyte death. Both in vitro and in vivo models have been generated with varying degrees of success to study the cellular mechanisms of the disease process. Here we review and discuss in vitro and in vivo PSACH and MED model systems and describe two transgenic mouse lines expressing human mutant TSP-5 protein. These model systems have revealed several important features of the PSACH cellular pathology: unfolded protein response activation, upregulation of apoptosis and inappropriate assembly of matrix network in the rER. Some of these models are valuable reagents that may be of use in testing therapeutic interventions. (Part of a Multiauthor Review).     

Term Structure Forecasting of Government Bond Yields with Latent and Macroeconomic Factors: Do Macroeconomic Factors Imply Better Out‐of‐Sample Forecasts?

This study empirically examines the role of macroeconomic and stock market variables in the dynamic Nelson–Siegel framework with the purpose of fitting and forecasting the term structure of interest rate on the Japanese government bond market. The Nelson–Siegel type models in state‐space framework considerably outperform the benchmark simple time series forecast models such as an AR(1) and a random walk. The yields‐macro model incorporating macroeconomic factors leads to a better in‐sample fit of the term structure than the yields‐only model. The out‐of‐sample predictability of the former for short‐horizon forecasts is superior to the latter for all maturities examined in this study, and for longer horizons the former is still compatible to the latter. Inclusion of macroeconomic factors can dramatically reduce the autocorrelation of forecast errors, which has been a common phenomenon of statistical analysis in previous term structure models. Copyright © 2013 John Wiley & Sons, Ltd.     

Affine Term Structure Model with Macroeconomic Factors: Do No‐Arbitrage Restriction and Macroeconomic Factors Imply Better Out‐of‐Sample Forecasts?

This study extends the affine dynamic Nelson–Siegel model for the inclusion of macroeconomic variables. Five macroeconomic variables are included in affine term structure model, derived under the arbitrage‐free restriction, to evaluate their role in the in‐sample fitting and out‐of‐sample forecasting of the term structure. We show that the relationship between the macroeconomic factors and yield data has an intuitive interpretation, and that there is interdependence between the yield and macroeconomic factors. Moreover, the macroeconomic factors significantly improve the forecast performance of the model. The affine Nelson–Siegel type models outperform the benchmark simple time series forecast models. The out‐of‐sample predictability of the affine Nelson–Siegel model with macroeconomic factors for the short horizon is superior to the simple affine yield model for all maturities, and for longer horizons the former is still compatible to the latter, particularly for medium and long maturities. Copyright © 2015 John Wiley & Sons, Ltd.