Computational Quest of High-Performance Sorbents for Water Treatment: From Mechanism Understanding to Big-Data-Driven Prediction

Summary: 

Dr. Zhongfang Chen is a full Professor in the Department of Chemistry, University of Puerto Rico, Rio Piedras campus, USA. He earned his PhD from Nankai University (China) in 2000. Before joining University of Puerto Rico as an associate professor in 2008, he worked in University of Erlangen-Nuremberg and Max-Plank Institute for Coal Research in Germany, University of Georgia, and had a short stint in Rensselaer Polytechnic Institute. Dr. Chen has delivered over 200 lectures around the world, and contributed over 300 papers, including five in Chem. Rev., and over 30 in J. Am. Chem. Soc., Angew. Chem. Int. Ed., and Phys. Rev. Lett.. Ten papers were highlighted by professional journals (Chem. & Eng. News and/or Nachrichten aus der Chemie, Nature China, Nature Chemistry). These papers gained him over 25,000 citations, and an H-index of 80.

The removal of contaminants of emerging concern (CECs), which are ubiquitous and can induce considerable ecological toxicity/effects, is urgent to guarantee the water safety. In this talk, we will introduce our recent efforts in designing high-performance sorbents towards some representative CECs, such as siloxanes and organic pollutants, by means of density functional theory calculations, GCMC simulations, QSAR, and machine learning techniques. We will emphasize the importance of understanding the adsorption mechanisms, and how the big-data-driven approach is revolutionizing the materials discovery and innovation.

Date: 

Saturday, May 8, 2021 - 13:00 to 15:00

City: 

Johannesburg