Corrosion behavior and magnetocaloric effect of FeNi(1J85) coated LaFe_(11.6)Si_(1.4)/Sn composites

The FeNi coated LaFe_(11.6)Si_(1.4)/Sn composites were prepared by hot pressing(HP). The microstructure,corrosion behavior and magnetocaloric effect(MCE) of FeNi coated LaFe_(11.6)Si_(1.4)/Sn composites were investigated systematically. The results show that the corrosion resistance of FeNi coated LaFe_(11.6)Si_(1.4)Sn composites is better than that of LaFe_(11.6)Si_(1.4)/Sn composites in deionized water. The maximum magnetic entropy change((-△S_M)~(max)) and relative cooling power(RCP) of FeNi coated LaFe_(11.6)Si_(1.4)/Sn composites are 13.30 J/(kg-K) and 146.25 J/kg, respectively, which are larger than that((-△S_M)~(max), 10.65 J/(kg·K) and RCP, 106.53 J/kg) of LaFe_(11.6)Si_(1.4)/Sn composites in a low magnetic field change of 2 T. FeNi coated LaFe_(11.6)Si_(1.4)/Sn composites possess a more negative slope. The improvement of magnetic properties is due to high permeability FeNi permalloy(1 J85) which improves the itinerant-electron metamagnetic(IEM) transition. So, the method of coating FeNi can provide a new idea for enhancing the corrosion resistance and magnetocaloric effect of La(Fe_xSi_(1-x))_(13)-based materials.     

Thermal Behavior During the Selective Laser Melting Process of Ti-6Al-4V Powder in the Point Exposure Scan Pattern

Metallurgical and Materials Transactions B - Currently, there are two main scan patterns, including the continuous exposure scan pattern and the point exposure scan pattern, during the selective...     

基于双树复小波分解的Boosting集成学习土地覆被分类研究

近年来,集成学习（Ensemble Learning,EL）分类方法成为土地覆被分类的研究热点,尤其是Boosting集成分类方法具有分类精度高、泛化能力强,在土地覆被分类中得到了显著的应用。但是,Boosting集成分类方法对噪声很敏感,如果训练样本含有噪声时,Boosting算法可能会失效,这是该方法的局限性。为了解决Boosting集成方法在土地覆被分类中存在的问题,有效克服噪声的影响,减少分类结果中的“椒盐”现象和提高分类精度,提出了基于双树复小波分解的Boosting集成学习分类方法。该方法对影像的光谱波段进行一层双树复小波分解,降低图像的噪声,将分解后的各波段作为Boosting集成学习的输入,得到最终的分类结果。实验先后比较了GBDT、XGBoost、LightGBM 3种Boosting集成学习算法在SPOT 6和Sentinel-2A影像上的分类效果。结果表明：(1)在SPOT 6影像上,3种Boosting集成算法总体分类精度均高于90%;DTCWTLightGBM分类总体精度最高,达到94.73%,Kappa系数为0.93,比LightGBM总体精度提高了1.1%...     

江西长力转炉开发60Si2Mn弹簧钢工艺研制

介绍了江西长力转炉研发60Si2Mn弹簧扁钢的过程,以及60Si2Mn弹簧钢的转炉生产工艺及研制结果.     

4522合成冷冻机油在丙烷压缩机上的应用

介绍了4522合成冷冻机油在丙烷压缩机上的应用,使用周期超过4 000 h.     

丙烯腈-氯化聚乙烯-三丙烯基异氰尿酸酯-苯乙烯树脂的制备和研究

以苯乙烯、氯化聚乙烯、丙烯腈、三丙烯基异氰尿酸酯(TAIC)为主要原料,采取悬浮聚合法聚合得到了物理机械性能优良、耐候、耐老化性能优良,巴勒斯效应和热收缩率小,加工性能好的四元共聚树脂.初步探讨了三丙烯基异氰尿酸酯量对树脂性能的影响.     

纳米氧化物粒子改善PP-R树脂性能的规律

以粒度相当、分散性能相似的纳米SiO2、纳米TiO2、纳米Al2O3和纳米ZnO等4种纳米氧化物粒子为填料,采用相同工艺来改善PP-R树脂各项性能,尤其是耐热性能和力学性能.研究结果表明,纳米粒子对PP-R树脂的改性效果顺序是:纳米ZnO＞纳米TiO2＞纳米Al2O3＞纳米SiO2;纳米氧化物粒子的极性对PP-R树脂的性能有显著影响,在排除纳米粒子的粒度、分散性和复合材料制备工艺等因素的影响前提下,纳米粒子的极性越强,改性效果越好.     

沉积压力对Parylene C膜性能的影响

采用X射线衍射(XRD),MOCON透湿仪等研究了不同沉积压力下制备ParyleneC膜的结晶度、水蒸汽透过性、拉伸强度、雾度、透明度随沉积压力的变化规律.结果表明,随着沉积室压力升高,Parylee C膜相对结晶度、透湿性能、拉伸强度、透明度下降,雾度增大.     

Physicochemical Properties and Functionality of Rice Bran Protein Hydrolyzate Prepared from Heat-stabilized Defatted Rice Bran with the Aid of Enzymes

ABSTRACT: Molecular size, thermal properties, hydrophobicity, nitrogen solubility, and emulsifying and foaming properties were determined for protein products from heat‐stabilized defatted rice bran. The freeze‐dried and spray‐dried proteins had molecular sizes between 6.5 to 66.2 kDa; denaturation temperatures of 84.1 and 84.6 °C, enthalpies of 2.5 and 2.37 J/g, hydrophobicities of 20677 and 22611, maximum solubilities of 66.3% and 66.1% at pH 12.0, emulsifying capacities of 0.19 and 0.18, emulsion stabilities of 16.5 and 17.3 min, foam capacities of 4.0 mL and 4.2 mL, and negligible foam stabilities. These results demonstrated that the extracted rice bran protein has potential as a nutraceutical ingredient in food applications.     

对杨木BCTMP配抄的手抄片性能的影响研究

该文主要在实验室条件下考察了分别用高剪切纤维离解机处理前后的杨木BCTMP按不同比例与部分阔叶木浆、针叶木浆配抄手抄片物理性能的变化。结果表明,配抄后的浆张松厚度提高、粗糙度降低、不透明度提高,尤其在配抄比例为30%时,配抄BCTMP离解二段纸浆后的浆张不透明度提高率达81%;并对配抄前后总体效果进行比较,结果得出,配抄15%的BCTMP离解二段纸浆后,浆张松厚度与空白样相比提高了3.4%,表面粗糙度降低了3.8%,不透明度提高了2.9%,抗张指数增加了4.4%,耐破指数几乎不变,但撕裂指数有所下降,这表明高剪切纤维离解机处理后的杨木BCTMP有助于改善纸或纸板的质量。