SURFACE ANALYSIS OF ALUMINUM ALLOYS INFLUENCED BY SULFATE- REDUCING BACTERIA

The morphology and chemical compositions of surface and corrosion phases for two aluminum alloys(7075 and 2024 ) in the aqueous mediums containing sulfate reducing bacteria(SRB) were studied by the methods of scanning electron microscopy (SEM) and energy dispersive x ray analysis (EDXA). The results showed that serious pitting corrosion took place when aluminum alloys were exposed in the mediums containing SRB, whereas no pitting corrosion were found on the surfaces of aluminum alloys only exposed in blank mediums non containing SRB. It was demonstrated with EDXA that corrosion of aluminum alloys exposed in the solutions containing SRB, whereas the corrosion in the solution non containing microorganisms was attributed to the presence of chloride ions(Cl ).

Analysis of Metallographic Characteristics of Aluminum Alloy for Turbocharged Impellers

In this paper, the composition, two-dimensional and three-dimensional microstructure of heat-resistant wrought aluminum alloy with strong oxidation resistance, heat resistance and easy processing are analyzed by using direct reading spectrometer, metallographic microscope and scanning electron microscope. The main alloy elements of heat-resistant forging aluminum alloy include Cu, Mg, Si, Ni and Fe. The α solid solution of each element in aluminum consists of S phase (Al2CuMg), Mg2Si phase, bright gray Al2CuNi phase and dark brown Al9FeNi phase. The distribution of each phase in the aluminum alloy is determined by the three-dimensional energy spectrum analysis of the microstructure, and the distribution of each phase in the crystal position is analyzed. The mechanism of heat resistance, easy processing type and wear resistance is obtained, which provides the theoretical basis for the development and use of heat-resistant forged aluminum alloy.

Quantitative analysis of impurities in aluminum alloys by laser-induced breakdown spectroscopy without internal calibration

To develop a fast and sensitive alloy elemental analysis method,a laser-induced breakdown spectroscopy(LIBS)system was established and used to carry out quantitative analysis of impurities in aluminum alloys in air at atmospheric pressure.A digital storage oscilloscope was used as signal recording instrument,instead of traditional gate integrator or Boxcar averager,to reduce the cost of the whole system.Linear calibration curves in the concentration range of 4×10-510-2 are built for Mg,Cr,Mn,Cu and Zn using absolute line intensity without internal calibrations.Limits of detection for these five elements in aluminum alloy are determined to be(2-90)×10-6.It is demonstrated that LIBS can provide quantitative trace elemental analysis in alloys even without internal calibration.This approach is easy to use in metallurgy industries and relative research fields.

Effect of the target positions on the rapid identification of aluminum alloys by using filament-induced breakdown spectroscopy combined with machine learning

Filament-induced breakdown spectroscopy(FIBS)combined with machine learning algorithms was used to identify five aluminum alloys.To study the effect of the distance between focusing lens and target surface on the identification accuracy of aluminum alloys,principal component analysis(PCA)combined with support vector machine(SVM)and Knearest neighbor(KNN)was used.The intensity and intensity ratio of fifteen lines of six elements(Fe,Si,Mg,Cu,Zn,and Mn)in the FIBS spectrum were selected.The distances between the focusing lens and the target surface in the pre-filament,filament,and post-filament were 958 mm,976 mm,and 1000 mm,respectively.The source data set was fifteen spectral line intensity ratios,and the cumulative interpretation rates of PC1,PC2,and PC3 were 97.22%,98.17%,and 95.31%,respectively.The first three PCs obtained by PCA were the input variables of SVM and KNN.The identification accuracy of the different positions of focusing lens and target surface was obtained,and the identification accuracy of SVM and KNN in the filament was 100%and 90%,respectively.The source data set of the filament was obtained by PCA for the first three PCs,which were randomly selected as the training set and test set of SVM and KNN in 3:2.The identification accuracy of SVM and KNN was 97.5%and 92.5%,respectively.The research results can provide a reference for the identification of aluminum alloys by FIBS.

Microstructure and Strain Fatigue Dislocation Structure of 7075-RRA Aluminum Alloy

The microstructure and the strain fatigue dislocation substructure of 7075-RRA (Retrogression and Reaging) aluminum alloy have been studied by using transmission electron microscopy. From these, a competitive mechanism of cyclic microscopic softening/hardening is put forward to explain the relation between macroscopic cyclic stability behavior and microscopic substructure.

Corrosion behavior on aluminum alloy LY12 in simulated atmospheric corrosion process

The corrosion behavior of typical high-strength aluminum alloy LY12 was studied by accelerated corrosion tests of cyclic wet-dry-immersion containing media of NaHSO3 and NaCl to simulate the corrosion process in different atmosphere environment, and the corrosion mechanism was also discussed. The main experimental techniques include mass loss, morphological check, analysis of corrosion products and electrochemical measurement. The result shows that the mass loss of LY12, with or without cladding, has linear relationship with test time in the three kinds of chemical media, 0.02 mol/L NaHSO3, 0.006 mol/L NaCl and 0.02 mol/L NaHSO3+0.006 mol/L NaCl, respectively. A layer of cladding on high-strength aluminum alloy can raise evidently the resistance of atmospheric corrosion. Cl- can promote pitting generation on the oxide film of LY12 when HOS 3-exists, LY12 can react much intensely with HOS3- derived from anions.

硼砂煅制工艺优化及质量评价

目的 优化硼砂煅制工艺,并对其进行质量评价。方法 以铺设厚度、煅制温度、煅制时间为影响因素,失水率、蓬松度、粉碎率、四硼酸钠含量为评价指标,星点设计-效应面法优化硼砂煅制工艺。采用扫描电镜(SEM)、热重分析(TG)、拉曼光谱、X射线衍射(XRD),比较硼砂煅制前后质量差异。结果 最佳条件为铺设厚度2 cm,煅制温度365℃,煅制时间100 min。煅制后,硼砂微观形态、成分组成、晶型结构发生变化,失去全部结晶水而转变为非晶体状态。结论 该方法稳定可行,可用于工业大批量生产煅硼砂。

激光诱导击穿光谱的自适应基线校正方法

为了降低远程激光诱导击穿光谱原位分析中连续背景辐射、随机噪声和样品基体效应对特征光谱的影响,提出一种通过适应度函数将粒子群优化和非对称重加权正则最小二乘相融合的自适应基线校正方法,旨在提高远程激光诱导击穿光谱的分析能力。以三种掺杂相近微量元素的铝基合金标样为研究对象,相同实验条件下利用所提出的基线校正方法研究并对比自适应迭代重加权正则最小二乘算法、非对称重加权正则最小二乘算法处理后的光谱信噪比与拟合基线的变化趋势。为了验证所提方法的有效性,构建了三次核函数支持向量机的铝基合金标样精细分类模型,其独立测试集的混淆矩阵分类准确率为100%。结果表明,自适应基线校正方法所拟合的基线变化趋势与激光诱导击穿光谱的实际基线轨迹相吻合,且特征光谱能够清晰地分离。该方法可有效降低随机噪声对光谱数据分析的影响,对于提高远程激光诱导击穿光谱原位分析的准确性和可靠性具有意义。

工艺参数对6082-T6/AlSi10MnMg异种铝合金热融自攻丝接头成形性的影响

为探究工艺参数对6082-T6/AlSi10MnMg真空压铸铝合金热融自攻丝接头成形性的影响,采用正交试验法,将穿孔转速、进给速度和拧紧扭矩作为试验变量,通过极差分析研究了工艺参数对最小衬套高度和平均螺牙深度的影响规律。在正交试验结果的基础上,建立了参数值与被测指标的响应面模型,研究了各参数对成形质量影响的显著性。对最优工艺参数组合的接头进行了强度测试。结果表明,穿孔转速和进给速度对最小衬套高度影响显著,但二者的交互作用对最小衬套高度影响较小。平均螺牙深度主要受拧紧扭矩的影响,穿孔转速和进给速度对平均螺牙深度的影响较弱。在拉拔和拉剪工况下,工艺参数对接头强度有较大影响,参数优化后接头强度分别提高了9.48%和8.64%,剪切工况下接头强度变化较小。

光谱预处理小波基函数的选择对结合FIBS技术和机器学习的铝合金识别精确度影响研究

随着经济不断发展,工业建筑领域产生了大量的废弃铝合金材料,对废弃铝合金材料分类回收可以提升废弃资源的利用效率,缓解能源紧张。选取了工业领域常用的五种型号的铝合金,开展了等离子体丝诱导击穿光谱(FIBS)光谱预处理小波变换基函数对铝合金分类识别精度的影响的研究。分别采用bior2.2、bior2.4和bior2.6正交小波基函数对铝合金的FIBS光谱进行预处理,结合线性判别分析(LDA)、网格搜索优化的支持向量机(GSSVM)和反向传播神经网络(BPNN)实现了铝合金型号的快速分类识别。结果表明bior2.2、bior2.4和bior2.6正交小波基函数结合LDA-GSSVM实现铝合金型号的平均识别准确率为90%、100%和76.67%,结合LDA-BPNN实现铝合金型号的平均识别准确率为96.67%、100%和90%,因此选择合适的正交小波基函数对FIBS光谱预处理,对于提高铝合金型号识别准确率有较大作用。

LASSO-LSSVM与激光诱导击穿光谱技术结合提高铝合金中Mn成分检测精度研究

铝合金作为一种重要的航空航天装备材料,其元素含量是决定铝合金材料质量和性能的关键因素,其组成成分的多样性对铝合金的铸造、冶炼以及回收分类有较大的影响,其中Mn是铝合金中的重要元素,能够止铝合金的再结晶过程,提高再结晶温度。铝合金成分的定量测定是合金成分在线检测的重要组成部分。信号波动(激光能量波动、等离子体不稳定性、样品不均匀性等)和自吸收效应对激光诱导击穿光谱(LIBS)技术测定铝合金中微量元素有一定影响。为了消除自吸收效应和信号波动所引起的偏差,提出了一种利用LIBS技术结合LASSO-LSSVM机器学习法检测铝合金材料中微量元素含量的新方法。利用最小绝对收缩和选择算子(LASSO)模型对光谱特征向量进行选择,降低光谱数据的维度从而与训练样本相匹配,降低了过拟合风险,有效提取表征LIBS光谱最重要的特征。利用最小二乘支持向量机(LSSVM)模型对LASSO所选择的特征光谱进行训练,分析结果与内标法和偏最小二乘回归(PLSR)相比,LASSO-LSSVM回归模型的精度和准确性都有所提高,其中,Mn元素回归曲线的相关系数(R^(2))从74.62%提高到99.29%,平均相对误差(ARE)从22.38%降低到3.56%,训练集均方根误差(RMSEC)从0.66 wt%降低到0.040 wt%,测试集均方根误差(RMSEP)从0.58 wt%降低到0.042 wt%。LASSO-LSSVM回归模型适用于复杂、不确定性较高的高维光谱数据,能够大大降低输入光谱数据的维数和冗余信息,因此,该模型减少了LSSVM的过拟合问题。研究结果表明,LIBS技术和LASSO-LSSVM回归模型的结合可以有效改善LIBS技术对于铝合金材料的定量分析性能,是一种简单、可靠、高精度检测合金含量的新方法。

基于表面粗糙度和反射率多目标优化的6061铝合金超精密车削工艺研究

目的探究工艺参数对6061铝合金滚压件超精密车削性能的影响,对工件超精密车削加工表面粗糙度和表面光学反射率进行协同优化研究。方法首先,对6061铝合金材料表面进行单向超声振动滚压以提高工件表面质量。其次,设计了四因素四水平的超精密车削正交试验,研究了切削工艺参数(主轴转速、进给速度、背吃刀量、刀尖半径)对6061铝合金滚压件表面粗糙度及表面光学反射率的影响规律。最后,采用灰色关联分析方法,将多个工艺目标参数优化问题转化为单目标的灰色关联度优化问题,通过超精密车削试验对优化结果进行验证。结果主轴转速对表面粗糙度Ra和Sa的影响最显著,其次是刀尖半径和背吃刀量,进给速度的影响最小;工艺参数对可见光波段和中红外光波段反射率的影响程度与表面粗糙度一致,各参数按对近红外光波段反射率影响程度由大到小的顺序依次为背吃刀量、刀尖半径、进给速度、主轴转速;通过灰色关联分析获得优化工艺参数组合为主轴转速3000 r/min、进给速度10 mm/min、背吃刀量5μm、刀尖半径0.5 mm,此时对应的表面粗糙度R_(a)和S_(a)分别为2.162 nm和7.855 nm,可见光、近红外光、中红外光波段反射率分别为88.892%、88.893%、97.788%。结论通过优化结果能够有效降低表面粗糙度、提升表面光学反射率,对制造高水平金属反射镜具有十分重要的现实意义和研究价值。

铝合金三价铬化学氧化用无磷脱脂剂的制备及性能

[目的]针对某厂家在铝合金三价铬化学氧化过程中所用脱脂剂含磷的问题,研制一款无磷脱脂剂。[方法]采用响应面法对多种常见的表面活性剂、金属螯合剂和助剂进行筛选及用量优化,同时研究了脱脂剂的使用浓度、温度和时间对其清洗效果及腐蚀性的影响。[结果]在脱脂温度60℃、脱脂时间10 min的条件下,由8.4 g/L OP-10、12.4 g/L葡萄糖酸钠、0.44 g/L钼酸钠、15.0 g/L四硼酸钠、5.4 g/L二乙二醇单丁醚和1.6 g/L硅酸钠组成的脱脂剂的净洗力达到99.85%,对2024铝合金的腐蚀速率为0.15 g/(m^(2)·h)。[结论]与某市售脱脂剂相比,自制脱脂剂的净洗力略高,腐蚀性明显降低。

熔体氢含量对铝合金圆铸锭表面气泡缺陷的影响

在生产实践的基础上,研究了熔体氢含量对6063、7003铝合金圆铸锭表面气泡缺陷的影响。利用光学显微镜观察铸锭表面气泡缺陷的结构,扫描电子显微镜及配备的能谱分析仪分析铸锭表面气泡缺陷的组分。结果显示,铸锭表面气泡缺陷的成分与铝基体的相同。铸锭表面气泡缺陷为熔体凝固析氢引起的熔体溢出行为所致。

X射线荧光光谱法测定铝合金中的元素含量

利用X射线荧光光谱特征峰强度与元素含量之间的关系,可确定铝合金中金属元素种类和含量。本试验测量了系列铝合金标准样品(已知金属元素成分含量)X射线荧光光谱(XRF),根据金属元素特征谱线绘制XRF特征峰值与元素含量线性关系曲线。结果表明,使用XRF法检测铝合金中的元素结果准确,灵敏度高,Cu元素质量分数检出限可达3×10^(-6),灵敏度相对低的Ti元素质量分数检出限也可达16×10^(-6);用XRF法检测了散热铝合金样品中各金属元素含量,其中Cu、Zn的测量结果与激光烧蚀火花诱导击穿光谱法所测结果一致。

An Experimental and Numerical Study of Effect of Textured Surface by Arc Discharge on Strength of Adhesively Bonded Joints

Aluminum alloys are being increasingly applied in the automotive industry as a means to reduce mass. Their application to the vehicle structure is typically via a combination of either mechanical or fusion joining with adhesive bonding. Correspondingly, there has been a large effort in improving the adhesive bonding characteristics by changing the surface properties using different surface treatment techniques. One such method is the atmospheric arc discharge process which develops a specific surface roughness which can be leveraged to improve adhesive bonding. In this paper the effect of a textured surface by arc discharge on the failure mode and strength of adhesively bonded aluminum alloy sheets is investigated. A single-lap joint configuration is used for simulation and experimental analysis. A two-dimensional （2D） finite element method （FEM） involving the morphology of treated surfaces and using interfacial elements based on a cohesive zone model （CZM） are used to predict the joint strength which is an enabler for faster product development cycles. The influence of arc process parameters： the arc current and the torch scanning speed, on the surface morphology and joint strength are explored in this study. Specifically, the present study shows that the surface treatment of aluminum alloys by arc discharge can strongly enhance adhesive bond strength. Additionally, arc treatment not only increases the joint strength but also improves the quality of bond along the interface （transition toward cohesive failure mode）. The current FE simulation of adhesive joint using the elastic and elasto-plastic （non-linear） material properties for adherend and adhesive, respectively, and cohesive zone elements for interface shows an accurate prediction of the resulting joint strength. By inclusion of non-linear multi-scale geometry model via considering the surface topographical changes after surface treatment the FE joint strength prediction can be successfully implemented.

Microstructure and properties of an Al–Ti–Cu–Si brazing alloy for SiC–metal joining

An Al–Ti–Cu–Si solid–liquid dual-phase alloy that exhibits good wettability and appropriate interfacial reaction with SiC at 500–600°C was designed for SiC–metal joining. The microstructure, phases, differential thermal curves, and high-temperature wetting behavior of the alloy were analyzed using scanning electron microscopy, X-ray diffraction analysis, differential scanning calorimetry, and the sessile drop method. The experimental results show that the 76.5Al–8.5Ti–5Cu–10Si alloy is mainly composed of Al–Al2Cu and Al–Si hypoeutectic low-melting-point microstructures (493–586°C) and the high-melting-point intermetallic compound AlTiSi (840°C). The contact angle, determined by high-temperature wetting experiments, is approximately 54°. Furthermore, the wetting interface is smooth and contains no obvious defects. Metallurgical bonding at the interface is attributable to the reaction between Al and Si in the alloy and ceramic, respectively. The formation of the brittle Al4C3phase at the interface is suppressed by the addition of 10wt% Si to the alloy. © 2017, University of Science and Technology Beijing and Springer-Verlag Berlin Heidelberg.

Electron spectroscopies and their use for materials characterization

We present here a general overview of electron spectroscopies from a practical point of view. The most frequently used ones are described and the type of structural information they can provide on materials is explained in relation to the physical processes on which they are based. Furthermore, we explore critically and in detail various tools that have been developed to allow a systematic solving of structures by these spectroscopies.

X射线光电子能谱在镁合金研究中的应用

X射线光电子能谱技术作为一种十分有效且应用广泛的表面分析技术,在镁合金领域尤其是解决其表面腐蚀、氧化等问题上具有独特的优势。介绍了近年来X射线光电子能谱在镁合金研究中的应用,阐述了X射线光电子能谱在镁合金的元素组成与含量、化学态分析及关键组分分析中的应用,从而表明其在镁合金材料表面性质分析及腐蚀、磨损机理研究方面的重要作用,并就其应用前景提出了展望。

硬质合金刀具高速切削7075铝合金表面粗糙度预测模型

为提高金属切削加工后工件表面质量,课题组将切削速度vc、进给量f、背吃刀量ap及刀尖圆弧半径R这4个因素结合起来,分析各个因素对工件表面粗糙度的影响。首先,设计了正交方案并进行切削试验,用极差法分析正交试验结果;其次,根据正交试验数据,采用多元非线性回归方程建立了表面粗糙度预测模型;最后,进行了离差平方和显著性检验以及模型试验验证。结果表明:4个因素对表面粗糙度的影响程度为f>R>vc>ap;该预测模型高度显著,且通过试验进行了验证,对比得出其误差率低于6%,可以准确地预测铝合金表面粗糙度。该模型为硬质合金切削Al7075-T6铝合金时,切削参数的合理选择提供了依据;为研究硬质合金切削Al7075-T6铝合金表面粗糙度提供了一种便捷的方法。