触觉式机器人焊缝跟踪方法

对机器人在焊缝自动跟踪方面进行了研究，介绍了机器人触觉的力传感器结构和使用方法。对力信号进行解耦及信号解算，有效地消除了机器人在工作过程中振动，抖动对力信号的污染，使机器人有能力自动识别，跟踪焊缝及焊枪位置修正，从而保证焊接质量。     

低电压氧化锌压敏电阻器的研究

研究了一种制造低电电压氧化锌压敏电阻器的方法。在基本成分的基础上适当加入二氧化钛可降低梯度电压（Ｖ１ｍＡ／ｍｍ），适量掺硼和改进热处理工艺可减小元件的漏电流和提高其稳定性。     

热轧态Si—Mn系双相钢的组织转变

利用Ｇｌｅｅｂｌｅ－１５００热模拟试验机对试验钢进行了热模拟轧制。研究了在不同热轧工艺参数与合金化程度条件下Ｓｉ－Ｍｎ双相钢的组织转变。获得了估算热轧态Ｓｉ－Ｍｎ双相钢马氏体体积百分数和先共翁素体体积百分数的计算式。计算值与实测值相吻合，给出了ｆｍ－Ｔ－Ｖ和ｆＦｐ－Ｔ－Ｖ关系的三维图及相应的ｆＭ和ｆＦｐ等值线图。     

Microhardness and corrosion behavior in CrN/electroless Ni/mild steel complex coating

The electroless nickel–phosphorous (Ni–P) coating was chosen as an interlayer to improve the properties of the CrN/mild steel (MS) composite. A hypophosphite-reduced acid solution was used to first deposit electroless Ni–P onto MS substrates, and then the CrN overlayer was deposited by reactive r.f. magnetron sputtering onto the electroless Ni–P modified substrate. The electroless Ni–P layer crystallizes with the precipitation of a Ni₃P phase during r.f. sputtering, and thus a coating–substrate composite of CrN/Ni–Ni₃P/MS is formed. The electroless Ni–P coating increases the surface hardness of the steel substrate to more than three times. The surface hardness of the CrN coating modified by an electroless Ni–P interlayer exhibits a hardness higher than 2000 HK_0.015. The usual substrate effect on the microhardness of the coatings is nearly eliminated with the complex coating feature, and a significant enhancement of surface hardness in the coating assembly is achieved. The corrosion tests indicate that the Ni–Ni₃P/MS configuration exhibits a more positive E_corr value (i.e. less electronegative) than CrN/MS and the corresponding potential curve is shifted toward the low-current side, indicating a better anti-corrosion performance. Through comparison of the E_corr values and the polarization curves, it is demonstrated that the CrN/Ni–Ni₃P/MS composite exhibits significantly higher corrosion resistance than the Ni–Ni₃P/MS and CrN/MS coating configurations.     

应用人工神经网络理论建立热粘塑性材料的本构关系

本文将人工神经网络（ＡＮＮ）用于建立热粘塑性材料的本构关系，意在探索出一种描述材料变形力学行为的新方法。文中给出了应用人工神经网络建立热粘塑性材料本构关系的ＢＰ模型和学习算法过程，并应用于４５号钢在高温和高速变形条件下的流动应力计算。计算结果与实测结果比较表明，二者吻合良好。因此，应用人工神经网络建立热粘塑性材料的本构关系具有重要的工程应用价值。     

Novel Mo-V Oxide Catalysts with Nanospheres as Templates for the Selective Oxidation of Acrolein to Acrylic Acid

Catalysis Letters - Novel Mo-V-PMMA and Mo-V-PS catalysts are prepared by addition of hard polymethyl methacrylate (PMMA) and polystyrene (PS) nanospheres into Mo/V compounds in the preparation...     

Facile synthesis of nitrogen and oxygen co-doped hierarchical porous carbon materials for high performance super capacitors

Journal of Porous Materials - Nitrogen and oxygen co-doped hierarchical porous carbons (NOPCs) is prepared by the pyrolysis of polyethylene glycol-200 (PEG) and triazine carbon forming agent (CFA)...     

Adsorption characteristics of hexadecyl ammonium with different numbers of carbon chains in montmorillonite and the structure of the prepared composites

Journal of Porous Materials - The dynamics and thermodynamics of adsorption of hexadecyl ammonium with different numbers of carbon chains in montmorillonite (Mt) with different layer charge density...