Collaborative Research: Enhancing the Fracture Strength of Advanced Ceramics by Process Control at the Microstructural Scale

合作研究：通过微观结构尺度的过程控制提高先进陶瓷的断裂强度

• 批准号: 0301273
• 负责人: Alice Smith
• 金额: $ 10万
• 依托单位: Auburn University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-15 至 2005-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0301273&HistoricalAwards=false
• 关键词: Collaborative; Research; Enhancing; Fracture; Strength

The wide application of advanced structural ceramics is limited by the problems related to structural reliability that are common to all brittle materials. Ceramics do not yield before fracture and therefore fracture strength is often the basis for the prediction of a design limit. Unfortunately, the strength of ceramics is found to be very sensitive to processing variables in ways that are difficult to predict. In recent years much effort has gone into toughening ceramics using mechanisms that result in the need for complex microstructures. Such work is usually isolated from studies in process control resulting in relatively few systematic and quantitative evaluations of the relationships between processing conditions and fracture behavior. This project uses a closely integrated interdisciplinary approach to determine the relationships between ceramics processing variables and fracture behavior of alumina. For this first year effort, correlations will be made between the distribution of microstructural heterogeneities and the structure of both polished and ground surfaces along with a limited number of fracture strength measurements. Ceramics processing, microstructural evolution, hardness distributions and fracture behavior will be linked through quantitative neural network based process models at the microstructural level combined with image analysis. The end result will be an improved quantitative understanding of the effects of processing variables on the fracture of advanced ceramics -- an understanding based on sound statistical analysis of microstructure evolution, and one which can be used to properly manufacture these ceramics. This project will be a timely application of image analysis and computational intelligence in the processing of advanced materials and will contribute to the emerging paradigm of studying materials as complex systems. Furthermore, the successful demonstration of process modeling of high strength ceramics will motivate a shift of the emphasis in ceramics processing to a quantitative understanding of microstructural control. Finally, the educational outcomes will provide resources to teach materials processing as an interdisciplinary subject to university students, and engage young middle school students in the realms of material science and image processing.

先进结构陶瓷的广泛应用受到所有脆性材料所共有的结构可靠性问题的限制。陶瓷在断裂前不会屈服，因此断裂强度通常是预测设计极限的基础。不幸的是，人们发现陶瓷的强度对加工变量非常敏感，而且难以预测。近年来，人们在使用机制来增韧陶瓷方面付出了很大的努力，这导致了对复杂微观结构的需求。此类工作通常与过程控制研究相隔离，导致对加工条件和断裂行为之间关系的系统和定量评估相对较少。该项目采用紧密集成的跨学科方法来确定陶瓷加工变量与氧化铝断裂行为之间的关系。在第一年的工作中，将在微观结构不均匀性的分布与抛光和磨削表面的结构以及有限数量的断裂强度测量之间建立关联。陶瓷加工、微观结构演化、硬度分布和断裂行为将通过基于微观结构水平的定量神经网络工艺模型与图像分析相结合。最终结果将是对加工变量对先进陶瓷断裂影响的定量理解得到改进——这种理解基于对微观结构演变的可靠统计分析，并且可用于正确制造这些陶瓷。该项目将图像分析和计算智能在先进材料处理中的及时应用，并将有助于将材料作为复杂系统进行研究的新兴范式。此外，高强度陶瓷工艺建模的成功演示将促使陶瓷加工的重点转向对微观结构控制的定量理解。最后，教育成果将为大学生教授材料处理作为一门跨学科学科提供资源，并吸引年轻中学生进入材料科学和图像处理领域。