Bridging AI and Material Science: Innovating Material Synthesis and Engineering
NTU MSE Seminar Hosted by Professor Alex Yan Qingyu
Abstract
The development of materials with enhanced properties is crucial for the advancement of various modern technologies. Traditional methods of materials development, often reliant on trial-and-error approaches, are not only time-consuming but also resource-intensive. In this seminar, I will discuss our pioneering work in leveraging artificial intelligence (AI) to expedite the development of novel materials. The presentation will be structured into three segments: I will first introduce some of our key studies in two-dimensional materials that highlight my expertise and set the foundation for my interdisciplinary research. Then, I will outline the challenges identified in conventional materials development and explain how we have successfully integrated AI techniques to overcome these challenges and enhance the speed and efficiency of material synthesis. Lastly, I will share our current projects that span a diverse array of materials and methodologies, underscoring the broad impact of our research.
- Tang, B., Wang, X., Han, M., et al. Phase engineering of Cr5Te8 with colossal anomalous Hall effect. Nature Electronics, 2022, 5(4), 224-232.
- Tang, B., Lu, Y., Zhou, J., et al. Machine learning-guided synthesis of advanced inorganic materials. Materials Today, 2020, 41, 72-80.
- Guo, H., Lu, Y., Lei, Z., … & Tang, B. (corresponding author), Liu, Z., Wang, L. Machine learning-powered multi-objective optimization of carbon quantum dots with superior optical properties. Nature Communications, 2024, 15(1), 4843
Dr. Tang Bijun