World Academy of Ceramics Forum 2020
It was decided to cancel the WAC FORUM 2020. Anyway a Special Symposium on the Forum topic endorsed by the World Academy of Ceramics will be organized in the frames of CIMTEC 2022.
Big Data and Machine Learning Methods for Materials Advancements
The traditional way of innovations and development in materials field are human-centred, where scientists and engineers design, conduct, analyse and interpret results obtained through simulations, experiments, or literature review. Such results are often high-dimensional, huge in number and heterogeneous in nature, which hinders researcher’s capability to draw insight from extensive information. As we approach the new era of explosive generation of big data and creative concept of artificial intelligence and machine learning, we may envisage a completely different paradigm for generating knowledge and advancing technology. Machine-aided innovation will accelerate important leaps towards better and more affordable solutions for the sustainable development of human society. Big data enhanced emerging technologies would be able to pioneer the new paradigm to discover truth beyond information and generate knowledge.
This Symposium, endorsed by the World Academy of Ceramics, features two sessions. The first one would address virtual materials design, integration of information technology and the next-generation manufacturing. The technical program will identify key challenges and opportunities for big data enhanced technologies in accelerating materials innovation and creating sustainable development. Some of the key topics which will be covered are high throughput materials design and characterization, artificial intelligence aided smart manufacturing, and other information enhanced emerging technologies for sustainable advancements of ceramic materials.
Quantification of microstructure by data analysis and machine learning methods will be of specific interest for the second session. Indeed, Central to materials science are the links between processing and microstructure, and between microstructure and properties. Advances made in recent years include the ability to image microstructures over large areas with high resolution using multiple electron beams that raster simultaneously in SEM and obtaining high resolution 3D images using tomography or reconstruction methods. Developing methods to quantify size, shape, curvature, texture, distributions of these quantities, topology, connectivity, and spatial correlations between such characteristics of microstructure features would greatly enhance our ability to design and fabricate ceramics microstructures to optimize properties.
The overall symposium is expected to generate interest and discussion on how the ceramic community might facing the challenges of sustainable development and industry 4.0.
Contributions are welcome in each of the following Session Topics:
CB-1 Big data emerging technologies for innovative materials design and manufacturing
CB-2 Quantification of microstructure by data analysis and machine learning methods