2022 International Conference on Machine Learning and Knowledge Engineering (MLKE2022)
Assoc.Prof. Zongyou Yin

Assoc.Prof. Zongyou Yin

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Assoc.Prof. Zongyou Yin

 Research School of Chemistry

The Australian National University, Australian

Speech title:Machine learning-aided materials innovations and development


The traditional research and development of functional materials are mainly based on the scientific intuition of researchers and a large number of repeated trial-and-error experiments, which are formidable tasks. With both materials science and data science continued development, the emerging advanced research strategies have been arising recently. In 2011, the Materials Genome Initiative advanced a new paradigm for high-performance materials discovery and design to replace the standard trial-and-error approach. Furthermore, the fourth paradigm (highly intelligent, dataintensive, and data-driven research) facilitated by the integration of machine learning (ML) algorithms and chemistry-related databases attracted more and more attention. In this talk, two recently published works will be shared, where the frameworks of ML-aided crystal design with rational controllable synthesis were developed and then demonstrated with the star-materials of anatase titania (TiO2) and the gold (Au). This innovative framework integrates data-intensive rational design and experimental controllable synthesis is laterally referenceable with the potential to develop wide uniquely functional materials. It also shows the feasibility of an intelligent chemistry future to accelerate the discovery of target material candidates from the laboratory research to the practice.

Brief introduction:

Dr Zongyou Yin’s research is interdisciplinary, encompassing AI-driven materials innovations, nano-to-atomic materials science, fundamental relationship among materials-structures-devices, and synergistic integration of multi-functions towards systems for energy and wearable applications. He has been honoured as World Highly Cited Researchers every year since 2015 (Clarivate Analytics).