Ongoing Researches

I am developing a data mining framework (a python module called Quandarium) to analyze the relationship between the atomic environment and property of interest, such as cohesive energy. The highlight of our methodology is the AtoMF features, which describe the atomic systems with physical meaningful features, facilitating the interpretations of the founded relationships. The article below addresses the methodology in detail.

The following papers employed AtoMF features:

• Methane dehydrogenation on 3d 13-atom transition-metal clusters: A density functional theory investigation combined with Spearman rank correlation analysis. Fuel, 2020, 275, 117790. DOI: 10.1016/j.fuel.2020.117790
• Ab Initio Insights Into the Formation Mechanisms of 55-Atom Pt-Based Core-Shell Nanoalloys. The Journal of Physical Chemistry, 2020, 124, 1, 1158-1164. DOI: 10.1021/acs.jpcc.9b09561
• Ab initio insights into the structural, energetic, electronic, and stability properties of mixed Ce_nZr_15-nO₃₀ nanoclusters, Physical Chemistry Chemical Physics, 2019, 21, 26637-26646. DOI: 10.1039/C9CP04762J

Currently, I am working on developing models that facilitate the extraction of knowledge and the relationship between AtoMF features and the targets.