Collaborative Research: Learning Microstructure- and Temperature-Dependencies of Grain Boundary Plastic Deformation Localization via Multi-modal In situ Characterization

合作研究：通过多模态原位表征学习晶界塑性变形局部化的微观结构和温度依赖性

• 批准号: 2234892
• 负责人: jean-charles stinville
• 金额: $ 44.97万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2234892&HistoricalAwards=false
• 关键词: Collaborative; Research; Learning; Microstructure; Temperature

NON-TECHNICAL SUMMARY:Numerous failure mechanisms in engineering alloy parts are correlated to how deformation is transmitted across the boundaries between the microscopic crystals (grains) that comprise the part. Despite extensive study, definitive experimental evidence of the conditions at which deformation will and will not transmit across grain boundaries is elusive, particularly at extreme temperatures in conditions found during space travel or hypersonic propulsion. New electron microscopy and X-ray measurements, which can look in detail at and below the sample surface, are being used together to watch how deformation is transmitted across grain boundaries as it occurs. Using these measurements and machine-learning techniques, a set of rules are being established describing how deformation is transmitted as a function of temperature in a range of model atomic crystal structures representing various forms of commonly used structural alloys. These rules can then be used to improve the usage of existing alloys in the field and to design new high-performance alloy systems.TECHNICAL SUMMARY:State-of-the-art in situ characterization techniques are being taken advantage of to learn the temperature-dependence of microstructural conditions governing plastic deformation localization at and near grain boundaries (GBs) in cubic engineering alloys. A complimentary combination of in situ characterization techniques (high-resolution digital image correlation in the scanning electron microscope and synchrotron X-ray-based 3D reconstructions) capable of probing micromechanical response and microstructural state simultaneously are being used to interrogate the high-dimensional space of microstructural configurations that can exist across GBs in model face-centered cubic (FCC) and body-centered cubic (BCC) alloys. Existing machine-learning (ML) tools are also being used to perform automated classification of the large number of microstructural pairings probed during each in situ experiment and learn criteria for predicting the evolution of plastic deformation localization behaviors at GBs with temperature and associated deformation mechanism activation. In this effort, activation of twinning through cryogenic deformation and its effects on GB plastic deformation localization are being used to create a generalized framework with which the effect of activation of other deformation mechanisms, such as climb, cross-slip, and GB sliding, can be evaluated.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非技术摘要：工程合金部件中的许多故障机制与构成零件的显微晶体（晶粒）之间的边界之间的变形相关。尽管进行了广泛的研究，但对于在太空旅行或超音速推进期间发现的条件下，变形将且不会在晶界传播的条件的确定性实验证据是难以捉摸的。新的电子显微镜和X射线测量值可以在样品表面的详细范围内进行详细介绍，以观察其在发生晶界的跨晶界的变形。使用这些测量值和机器学习技术，正在建立一组规则，描述了如何在一系列模型原子晶体结构中传输变形，以代表各种形式的常用结构合金。然后，这些规则可用于改善现场合金的使用情况，并设计新的高性能合金系统。技术摘要：正在利用原位表征技术的优势来学习在晶粒边界和附近的晶状体边界（GBS）中塑料塑料条件的温度依赖性（GBS）。能够探测微力机械响应和微结构状态的能够同时使用微型机械响应和微观结构状态的微观结构构建的近距离结构的高维空间（在模型中，g gbs中的高维空间）的相结构构成的相结构构成的相结构，从而在扫描电子显微镜和基于X射线的3D重建方面的相互作用组合（扫描电子显微镜和基于X射线的3D重建的高分辨率数字图像相关性）的免费组合（基于X射线的3D重建）。 （BCC）合金。现有的机器学习（ML）工具还用于对每个原位实验期间探测的大量微观结构配对进行自动分类，并学习预测与温度和相关变形机制激活GBS在GBS上塑性变形定位行为的演变的标准。在这项努力中，通过低温变形及其对GB塑性变形定位的影响的激活正在创建一个通用框架，该框架使用其他变形机制的激活效果，例如攀登，交叉滑移和GB滑动，可以评估这一奖项，这反映了NSF的法定任务和构成的范围，并具有宽广的影响。 标准。

项目成果

Strain localization in the Alloy 718 Ni-based superalloy: From room temperature to 650 °C

• DOI: 10.1016/j.actamat.2024.119759
• 发表时间: 2024-02
• 期刊: Acta Materialia
• 影响因子: 9.4
• 作者: D. Texier;J. Milanese;Malo Jullien;J. Genée;J. Passieux;Didier Bardel;Eric Andrieu;M. Legros;J. Stinville

Micro-strain and cyclic slip accumulation in a polycrystalline nickel-based superalloy

• DOI: 10.1016/j.actamat.2024.119657
• 发表时间: 2024-01
• 期刊: Acta Materialia
• 影响因子: 9.4
• 作者: R.L. Black;D. Anjaria;J. Genée;V. Valle;J. Stinville

Microstructural statistics for low-cycle fatigue crack initiation in α+β titanium alloys: A microstructure based RVE assessment

α β 钛合金低周疲劳裂纹萌生的微观结构统计：基于微观结构的 RVE 评估

• DOI: 10.1016/j.ijfatigue.2023.107854
• 发表时间: 2023
• 期刊: International Journal of Fatigue
• 影响因子: 6
• 作者: Bean, C.;Stinville, J.C.;Naït-Ali, A.;Wu, Z.;Sun, F.;Prima, F.;Hémery, S.
• 通讯作者: Hémery, S.