Interview with JMI's Author: Dr. Lixin Chen
In JMI's 2023 Annual "Best Paper Award" selection, the paper titled "High-entropy alloy catalysts: high-throughput and machine learning-driven design" stood out. In an interview with JMI, Dr. Lixin Chen, the first author of the paper, shared insights into her team's research on high-entropy alloy catalyst design, the challenges they encountered, and her perspectives on the future development of materials informatics.
Here are the details of the Interview:
Interview Questions:
Q1: Could you briefly introduce your team's current research field and share your research plans for the future?
Q2: Congratulations to your team on winning the JMI Best Paper Award for your article, "High-entropy alloy catalysts: high-throughput and machine learning-driven design"! What challenges did you encounter during the research process? How did you overcome these challenges?
Q3: How do you view the current status and future trends of materials informatics research?
Q4: As an author for JMI, do you have any thoughts or suggestions regarding our editorial services?
Interviewee Introduction:
Dr. Lixin Chen is a lecturer at Changchun University of Technology, China, and completed her postdoctoral training at the University of Toronto, Canada. Her research focuses on combining experiments, density functional theory (DFT), and machine learning to design two-dimensional and high-entropy materials with enhanced active sites, conductivity, stability, and catalytic performance for hydrogen evolution. She has published 18 SCI papers as first or corresponding author, including a highly cited paper, with over 1,500 citations and an H-index of 17.
Editor: Mengyu Yang
Language Editor: Emma Chen
Production Editor: Ting Xu
Respectfully Submitted by the Editorial Office of the Journal of Materials Informatics
