碳化二亚胺类抗水解稳定剂Bio-SW100的合成与应用

以硫脲法工艺路线合成了单体型碳化二亚胺抗水解稳定剂SW-100,通过红外光谱、元素分析以及液相色谱考察了产物的结构、纯度。红外光谱和元素分析确定了合成产物结构正确,液相色谱确定产物纯度达到99%以上。在结构和纯度确定的基础上,将合成产物添加到聚乳酸中进行水解性能测试。结果表明,在1%添加量下聚乳酸拉伸强度保持率较纯树脂提高了80%。     

Simultaneous improvement of thermal conductivity and mechanical properties for mechanically mixed ABS/h-BN composites by using small amounts of hyperbranched polymer additives

Recently, thermal interface materials (TIMs) are in great demands for modern electronics. For mechanically mixed polymer composite TIMs, the thermal conductivity and the mechanical properties are generally lower than expected values due to the sharply increased viscosity and poor filler dispersion. This work shows that addition of a small amount of polyester-based hyperbranched polymer (HBP) avoided the trade-off in mechanically mixed ABS/hexagonal boron nitride (h-BN) composites. After adding 0.5 wt% HBP, the maximum h-BN content in the composites increased from 50 to 60 wt%. The out-of-plane, in-plane thermal conductivity, and tensile strength of ABS/h-BN with 50 wt% h-BN were 0.408, 0.517 W/mK, and 18 MPa, respectively, and were increased to 0.729, 0.847 W/mK, and 32 MPa by adding 0.5 wt% HBP, while 0.972, 1.12 W/mK, and 29.5 MPa were achieved for ABS/h-BN/HBP with 60 wt% h-BN. The morphological and rheological results proved that these enhancements are due to the improved h-BN dispersion by decreasing viscosity of composites during mixing. Theoretical modeling based on the modified effective medium theory confirmed such results and showed that the interfacial thermal resistance also decreased slightly. Thus, this work demonstrates a facile and scalable method for simultaneously improving the thermal conductivity and mechanical properties of thermoplastic-based TIMs.     

改进Elman神经网络在短期热负荷预测中的应用

热电厂的短期热负荷预测在城市集中供暖中起着至关重要的作用,直接影响热电厂的经济效益和热能利用率。电厂的短期热负荷一般采用神经网络预测模型进行预测,而BP神经网络应用最为广泛。Elman神经网络算法在BP神经网络基础上加入了承接层,作为一步延时算子,实现记忆能力,使系统具备适应时变能力,增强系统全局稳定性。但Elman神经网络算法模型的构造依然需要大量样本的支撑,而且输入层的变量多,导致预测时间依然很长,收敛速度慢。该文在Elman神经网络预测前,进行了相关系数预处理和对样本中异常值的平均化预处理,通过数据归一化运算,使Elman神经网络输入层变量大幅减少。仿真实验表明,改进的Elman神经网络算法使预测模型快速寻优,减少预测时间的同时明显提高预测精度。     

Feedforward control of the transverse strip profile in hot-dip galvanizing lines

Hot-dip galvanizing is a standard technology to produce coated steel strips. The primary objective of the galvanizing process is to establish a homogeneous zinc layer with a defined thickness. One condition to achieve this objective is a uniform transverse distance between the strip and the gas wiping dies, which blow off excessive liquid zinc. Therefore, a flat strip profile at the gas wiping dies is required. However, strips processed in such plants often exhibit residual curvatures which entail unknown flatness defects of the strip. Such flatness defects cause non-uniform air gaps and hence an inhomogeneous zinc coating thickness. Modern hot-dip galvanizing lines often use electromagnets to control the transverse strip profile near the gas wiping dies. Typically, the control algorithms ensure a flat strip profile at the electromagnets because the sensors for the transverse strip displacement are also located at this position and it is unfeasible to mount displacement sensors directly at the gas wiping dies. This brings along that in general a flatness defect remains at the gas wiping dies, which in turn entails a suboptimal coating.In this paper, a model-based method for a feedforward control of the strip profile at the position of the gas wiping dies is developed. This method is based on a plate model of the axially moving strip that takes into account the flatness defects in the strip. First, an estimator of the flatness defects is developed and validated for various test strips and settings of the plant. Using the validated mathematical model, a simulation study is performed to compare the state-of-the-art control approach (flat strip profile at the electromagnets) with the optimization-based feedforward controller (flat strip profile at the gas wiping dies) proposed in this paper. Moreover, the influence of the distance between the gas wiping dies and the electromagnets is investigated in detail.     

红外热成像在乳腺疾病检测的应用研究

乳腺疾病已严重危害女性身心健康,其中乳腺癌更位居全球范围内女性癌症发病率和死亡率首位,因此乳腺癌的早期发现意义重大。传统结构影像学早期检测疾病具有一定局限性,而红外热成像作为功能成像技术可为乳腺癌的早期筛查提供有效线索。因此本文主要就红外热成像在乳腺疾病的早期检测及预后评估的应用价值进行综述。     

Fabrication of Cu/graphite film/Cu sandwich composites with ultrahigh thermal conductivity for thermal management applications

Effective thermal management of electronic integrated devices with high powder density has become a serious issue, which requires materials with high thermal conductivity (TC). In order to solve the problem of weak bonding between graphite and Cu, a novel Cu/graphite film/Cu sandwich composite (Cu/GF/Cu composite) with ultrahigh TC was fabricated by electro-deposition. The micro-riveting structure was introduced to enhance the bonding strength between graphite film and deposited Cu layers by preparing a rectangular array of micro-holes on the graphite film before electro-deposition. TC and mechanical properties of the composites with different graphite volume fractions and current densities were investigated. The results showed that the TC enhancement generated by the micro-riveting structure for Cu/GF/Cu composites at low graphite content was more effective than that at high graphite content, and the strong texture orientation of deposited Cu resulted in high TC. Under the optimizing preparing condition, the highest in-plane TC reached 824.3 W·m⁻¹·K⁻¹, while the ultimate tensile strength of this composite was about four times higher than that of the graphite film.     

内燃机活塞环表面处理技术

活塞环在内燃机中有着支撑、密闭、储油、导热的作用,内燃机活塞环制备材料应该具备优良的加工性能、耐高温、耐腐蚀、导热性好且具有良好的强韧性,较好的与气缸材料表面的磨合性能。球墨铸铁和专用钢材已经成为制备内燃机活塞环的基础材料,目前国内外采用多种表面处理技术比如:镀铬、氮化、PVD与CVD镀膜、喷钼、喷涂陶瓷层等表面处理工艺进行表面改性,提高内燃机活塞环的使用寿命和使用性能。需要不断研究和开发新的内燃机活塞环的表面处理技术来满足实际生产和应用中内燃机越来越高的要求。     

高温氢工质热物理性质计算分析

氢工质在新能源与动力、航天推进、化工材料等领域有着广泛应用。通过开展高温氢工质热力学与输运性质研究，建立了原子态氢、分子态氢、热解平衡态氢的热物理性质计算模型，开发了热物性计算程序Prop_H_H2，适用范围为温度100~3 500 K、压力104~5×107 Pa 。验证表明，Prop_H_H2在适用范围内计算氢工质的物性参数合理可靠，在温度200~3 000 K、压力104~107 Pa范围内，程序预测值更加准确，相对偏差在±5%左右。本研究可为氢工质相关的航天推进、应用物理学、能源动力等行业的科研和应用提供支持借鉴。     

回转窑煅烧段烟气最高温度的间接测量

通过对球团回转窑内的热平衡分析,得到回转窑稳定工作时,煅烧段烟气最高温度与窑尾烟气温度之间的理论关系式。该公式表明回转窑在稳定工作时,窑尾烟气温度与煅烧段烟气最高温度存在线性关系。通过三维建模,运用有限元技术对窑尾烟气温度与煅烧段烟气最高温度进行了数值模拟。研究结果可为回转窑煅烧段温度在线监测和自动化调节火焰温度提供理论指导。     

多晶硅锭中硬质点分析及控制研究

以多晶硅锭中硬质点为研究对象,通过实验研究和数值模拟的方法,对多晶硅锭中硬质点进行形貌和成分分析,并提出改善控制方法。研究结果表明硅锭中部的硬质点较细小,主要由SiC组成;硅锭头部的硬质点较粗大,主要由SiC和Si3N4组成,还有少量O的存在。进一步研究发现多晶硅定向凝固铸锭炉的热场结构对于多晶硅锭硬质点形成有直接影响,通过改进热场结构,优化晶体生长界面,显著减少了铸锭中硬质点的数量。