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

先进结构陶瓷的广泛应用受到所有脆性材料共同的结构可靠性问题的限制。陶瓷在断裂之前不会屈服，因此断裂强度通常是预测设计极限的基础。不幸的是，陶瓷的强度被发现是非常敏感的加工变量的方式是难以预测的。近年来，许多努力已经进入韧化陶瓷使用的机制，导致需要复杂的微观结构。这类工作通常与过程控制的研究相分离，导致对加工条件与断裂行为之间的关系的系统和定量评价相对较少。该项目采用紧密结合的跨学科方法来确定陶瓷加工变量和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研磨表面的结构之间建立相关性，并进行有限数量的断裂强度测量。陶瓷加工、显微组织演变、硬度分布和断裂行为将通过基于定量神经网络的过程模型在显微组织水平上与图像分析相结合。最终的结果将是一个更好的定量理解的加工变量对先进陶瓷的断裂的影响-一个理解的基础上健全的微观结构演变的统计分析，并可以用来正确地制造这些陶瓷。该项目将是图像分析和计算智能在先进材料处理中的及时应用，并将有助于研究材料作为复杂系统的新兴范式。此外，高强度陶瓷工艺建模的成功示范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，教育成果将提供资源，将材料处理作为一个跨学科的学科教授给大学生，并让年轻的中学生参与材料科学和图像处理领域。

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.