Experimental Investigations of Micro-Meso Damage Evolution for a Co/WC-Type Tool Material with Application of Digital Image Correlation and Machine Learning.
Experimental Investigations of Micro-Meso Damage Evolution for a Co/WC-Type Tool Material with Application of Digital Image Correlation and Machine Learning.
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应用数字图像相关和机器学习对 Co/WC 类刀具材料的微细观损伤演化进行实验研究。
DOI：
10.3390/ma14133562
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发表时间：
2021-06-25
期刊：
影响因子：
--
通讯作者：
Tillmann W
中科院分区：
文献类型：
--
作者：
Schneider Y;Zielke R;Xu C;Tayyab M;Weber U;Schmauder S;Tillmann W
工业Co/WC/金刚石复合材料是一种非常有用的硬质合金工具材料，其韧性和准脆性行为都是可能的。这项工作实验研究其损伤演化依赖于微观结构特征。目前的研究调查了不同类型的Co/WC型刀具材料，其含有90体积% Co而不是通常的<50 vol. %。所研究的复合材料表现出准脆性行为。自行设计的试验机实现了加载条件下的原位微型计算机断层扫描（CT）。这种先进的设备可以在加载过程中以3D方式记录局部损伤。数字图像相关技术基于断层图像提供2D和3D的局部位移/应变图。如纳米压痕测试所示，金刚石颗粒附近的基体区域不具有比其他区域更高的硬度值。由于具有高应力的局部位置通常与具有高应变的位置重合，因此旨在实现具有高硬度的复合材料的金刚石对强度的贡献小于WC相。说明准脆性行为的样品具有比具有延性行为的样品高约100-130 MPa的拉伸强度。空洞及其连接（形成微小/小裂纹）占主导地位的检测到的损伤，这意味着空洞的萌生，增长和合并应该是损坏的机制。空洞以脱粘的形式出现。尽管如此，它被发现，钴金刚石之间的脱粘起着重要作用，在挑起致命的断裂复合材料与准脆性行为。优化的微结构应避免金刚石簇及其局部体积浓度。为了提高CT图像分割的时间效率和对象识别精度，应用了机器学习（ML），卷积神经网络（深度学习）中的U-Net。该方法仅需约40分钟即可分割出700多幅图像，即，与手工作业相比，大大提高了时间效率，并保持了准确性。上述结果为Co/WC/金刚石复合材料的强化和损伤机理提供了理论依据这种工具材料（>50体积%）的材料性质到目前为止，很少出版。ML部分的努力有助于实现材料科学中大数据驱动科学的自主处理过程。
Commercial Co/WC/diamond composites are hard metals and very useful as a kind of tool material, for which both ductile and quasi-brittle behaviors are possible. This work experimentally investigates their damage evolution dependence on microstructural features. The current study investigates a different type of Co/WC-type tool material which contains 90 vol.% Co instead of the usual <50 vol.%. The studied composites showed quasi-brittle behavior. An in-house-designed testing machine realizes the in-situ micro-computed tomography (CT) under loading. This advanced equipment can record local damage in 3D during the loading. The digital image correlation technique delivers local displacement/strain maps in 2D and 3D based on tomographic images. As shown by nanoindentation tests, matrix regions near diamond particles do not possess higher hardness values than other regions. Since local positions with high stress are often coincident with those with high strain, diamonds, which aim to achieve composites with high hardnesses, contribute to the strength less than the WC phase. Samples that illustrated quasi-brittle behavior possess about 100–130 MPa higher tensile strengths than those with ductile behavior. Voids and their connections (forming mini/small cracks) dominant the detected damages, which means void initiation, growth, and coalescence should be the damage mechanisms. The void appears in the form of debonding. Still, it is uncovered that debonding between Co-diamonds plays a major role in provoking fatal fractures for composites with quasi-brittle behavior. An optimized microstructure should avoid diamond clusters and their local volume concentrations. To improve the time efficiency and the object-identification accuracy in CT image segmentation, machine learning (ML), U-Net in the convolutional neural network (deep learning), is applied. This method takes only about 40 min to segment more than 700 images, i.e., a great improvement of the time efficiency compared to the manual work and the accuracy maintained. The results mentioned above demonstrate knowledge about the strengthening and damage mechanisms for Co/WC/diamond composites with >50 vol.% Co. The material properties for such tool materials (>50 vol.% Co) is rarely published until now. Efforts made in the ML part contribute to the realization of autonomous processing procedures in big-data-driven science applied in materials science.
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影响因子：
2.8
作者：
Hoppe, Kevin;Maricanov, Michail;Pieloth, Damian
通讯作者：
Pieloth, Damian
WC-Co 硬质合金中的低能晶界
影响因子：
9.4
作者：
Liu, Xingwei;Liu, Xuemei;Nie, Zuoren
通讯作者：
Nie, Zuoren
DOI：
10.1016/0025-5416(78)90163-5
发表时间：
1978-01-01
期刊：
MATERIALS SCIENCE AND ENGINEERING
影响因子：
--
作者：
LEE, HC;GURLAND, J
通讯作者：
GURLAND, J
影响因子：
6.1
作者：
Agrawal, Ankit;Choudhary, Alok
通讯作者：
Choudhary, Alok
影响因子：
2.4
作者：
Lu, H;Cary, PD
通讯作者：
Cary, PD