Kai Tang

His extensive research focuses primarily on pyrometallurgy and materials science. Key areas of his work include the production and purification of silicon, the study of molten slags and alloys, and applying machine learning for metallurgical processes. He is a leading expert in the recycling of critical raw materials, including rare earth elements from magnets and batteries. He has published over 200 papers (h-index 31, cited over 3000 times).

Education

PhD., Shanghai University, China, 1992-1997

Competence and research areas

Computational Thermodynamics
Kinetic Modelling
Machine Learning and Reinforcement Learning
Ferroalloy Process Simulations
Recycling of critical raw materials
Anode Materials for Li-ion and Na-ion batteries

Linkedin

https://www.linkedin.com/in/kai-tang-48000940/

ResearchGate

https://www.researchgate.net/profile/Kai-Tang-18

ORCID

https://orcid.org/0000-0002-6657-5187