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钛合金是航空航天的重要材料之一,但保载疲劳寿命通常要比想象的低很多,主要原因是与其它合金相比,钛合金中存在“Macrozones”(宏区)。 近10多年来,通过EBSD技术的表征发现,几乎所有的近α和α+β型钛合金中都存在 “宏区”(figure 1)。不同“宏区”中晶粒择优取向程度不同。利用EBSD技术分离“宏区”中的初生α和次生α相,发现攒簇的初生α相和次生α相的c轴有近乎一致的取向,从而造成整体具有非常锋锐的织构(figure 2)。结合EBSD技术的表征和它的加工过程,Gey将“宏区”的形成归结于2个原因:

“宏区”会大大降低钛合金的保载疲劳寿命,由于“宏区”内部所有晶粒的取向几乎一致,因此可以把这个整体区域看做一个大晶粒。众所周知,裂纹向前扩展的过程中,如果遇到晶界,会受到阻碍。但“宏区”整体相当于一个大晶粒,晶界阻碍作用较小,裂纹扩展的速率大大提高,从而降低了保载疲劳的寿命。另外,相较而言,“宏区”周围的晶粒与这个“大晶粒”有较大的取向差,属于“硬晶粒”,变形过程中应力更加容易集中在“宏区”内部,增加了裂纹形核的概率。Figure 3 为“宏区”内部裂纹扩展的示意图。


LocMis的全称为Local Misorientation,KAM的全称为Kernel Average Misorientation(见figure 6)。两者名称不同,但所描述的意义却差不多,均为局部取向差;KAM或LocMis可以定性反映塑性变形的均匀化程度,数值较高的地方表示塑性变形程度较大或者缺陷密度较高。因此,在诸如应力腐蚀开裂、晶界变形协调性等研究中有广泛的应用。 (KAM)是由24个最近的相邻点组成的一个核心点,它被用来给每一个点分配一个标量值,表示它的局部取向差。EBSD中得到的KAM图可以用来计算几何位错密度,从而判断在变形过程中材料应力分布的状态。

Figure 6 Ti6242S合金锻造后横截面获取的KAM图(笔者数据)

Figure 7 AZ31B镁合金在不同循环周期下利用KAM图计算几何位错密度值[5]。


Figure 8 Ti6242S合金边部到心部的大小角晶界分布图;绿色的线代表小角度晶界,黑色的线代表大角度晶界(此图也是笔者的数据资料)[6]。

大小角晶界分布图除了能够判断晶粒是否发生回复和再结晶之外,还能够研究材料相变过程中是否有变体选择现象。笔者是研究钛合金的,就以钛合金举例。钛合金β→α转变时,可以生成12种不同取向的变体。通过理论计算,同一β晶内的这12种变体之间仅仅存在5类取向差,分别是10.5°、60°、60.832°、63.262°、90°。但如果在双相区热加工冷却后,取向差不集中于10°、60°、90°左右的峰或5种取向差不满足理论比例,则一定有变体选择发生。Figure 9 为Ti60合金在空冷和炉冷条件下析出的α板条之间的取向差,可以看出,有一部分晶界小于10°,这意味着在β相→α相转变过程中发生了变体选择,在β/β晶界两侧析出了许多具有小角度晶界的次生α相。

Figure 9 Ti60合金在(a)空冷、(b)炉冷条件下析出的次生α板条之间的取向差[7]


钛合金低温下呈HCP结构,其有12个滑移系,而体心立方(BCC)结构则具有48个滑移系。因此在变形尤其在冷变形该过程中,HCP结构的材料很容易启动孪晶。纯钛由于所含的合金元素较少,在室温下不含β相,所以在冷变形过程中很容易出现孪晶,这也是纯钛塑形相对较好的重要原因之一。一般来说,纯钛在变形过程中主要启动两种类型的孪晶,即拉伸孪晶和压缩孪晶,以实现HCP晶格调控。孪晶的启动还会造成织构变化,同时孪晶界的形成也造成了晶界强化。在EBSD技术出现之前,人们只能通过透射电镜来研究材料变形带来的孪晶,但是透射电子扫查的区域非常小,不利于材料中孪晶的大量统计。而EBSD扫查的区域与扫描电镜相当,可以对孪晶进行数目统计。通过IPF图和极图可以明显看出孪晶的取向以及孪晶会使晶粒怎么转动变形。如figure 10为纯钛板材在RD方向冷压缩后进行EBSD实验所获得的结果。可以看出,压缩后材料中拉伸孪晶和压缩孪晶都出现了,但两种孪晶所占百分比不一样,分别约为57%和5.9%。对A晶粒分析的结果表明:变形过程中首先形成拉伸孪晶再出现压缩孪晶,且变形中出现了1个孪晶变体,5个孪晶变体。在(0001) 极图上可看出,孪晶偏离c轴约85°,也就是说其在变形过程中更容易形成柱面织构(c轴沿着TD方向排列),而孪晶的分布比较杂乱,最终晶粒c轴的取向也比较分散。

Figure 10 沿RD压缩至15%纯钛的EBSD测量结果

(a)IPF图;(b) A晶粒中启动的孪晶类型及其变体; (d) A粒的散点(0001)极图,其中单个离散极点用与反极图相同的颜色标记[8]。

[1] Gey N, Bocher E, Germain L, Humbert M. Texture and microtexture variations in a near-α titanium forged disk of bimodal microstructure[J]. Acta Materialia, 2012. 60(6-7), 2647-2655.

[2] Germain L, Gey N, Humbert M, Vo, P, Jahazi, M,Bocher, 在IQ Option中使用趋势级别信号策略进行交易 P. Texture heterogeneities induced by subtransus processing of near α titanium alloys[J]. Acta Materialia, 在IQ Option中使用趋势级别信号策略进行交易 2008. 56(16), 4298-4308.

[3] E UTA, N GEY,BOCHER P, HUMBERT M, 在IQ Option中使用趋势级别信号策略进行交易 Texture heterogeneities in αp/αs titanium forging analysed by EBSD-Relation to fatigue crack propagation[J]. Journal of Microscopy, 2009. 233, 451–459.

[4] Wenyuan Li, Zhiyong Chen, Jianrong Liu, Qingjiang WangandGuoxin Sui. Effect of texture on anisotropy at 600℃in a near-α titanium alloy Ti60plate. Materials Science & Engineering: A, 2017, 688: 322-329;

[5] Zhifeng Yan, Denghui Wang, 在IQ Option中使用趋势级别信号策略进行交易 在IQ Option中使用趋势级别信号策略进行交易 在IQ Option中使用趋势级别信号策略进行交易 Xiuli He. Deformation behaviors and cyclic strength assessment of AZ31B magnesium alloy based on steady ratcheting effect Materials Science & Engineering A, 723 (2018) 212–220;

[6] Guoming Zheng, Xiaonan Mao, Lei Li, Rui Dang. The variation of microstructures, textures and mechanical properties from edge to center in cross section of Ti6242s titanium alloy. Vacuum, 160 (2019) 81–88;

[7] Z.B. Zhao, Q.J. Wang, J.R. Liu, R. Yang. Effect of heat treatment on the crystallographic orientation evolution in a near-a titanium alloy Ti60. Acta Materialia 131 (2017) 305-314

[8] Jong Woo Won , Daehwan Kim, Seong-Gu Hong, Chong Soo Lee. Anisotropy in twinning characteristics and texture evolution of rolling textured high purity alpha phase titanium. Journal of Alloys and Compounds 683 (2016) 92-99

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