Pdn Cluster Structure Optimization

Dataset, statistical learning-based energy model and structure optimization algorithms in Python for subnanometer Pd clusters supported on Ceria

Computational Framework

Pd cluster structure dataset

The dataset contains Pdn cluster structures in the size range from 1 to 21.

Pd cluster energy model

LASSO-assisted Cluster Expansion (CE), an efficient mapping from structures to energies

Structure optimization algoirthms in cannoical ensembles

The detailed usage can be found in the links.

Dependencies

Python version 3.6+
Numpy: Used for vector and matrix operations
Matplotlib: Used for plotting
Scipy: Used for linear algebra calculations
Pandas: Used to import data from Excel files
Sklearn: Used for training machine learning models
Seaborn: Used for plotting
Networkx: Used for graph opertations

How to cite this work

Wang, Y., Su, Y., Hensen, E. J. M., & Vlachos, D. G. (2020). Finite-Temperature Structures of Supported Subnanometer Catalysts Inferred via Statistical Learning and Genetic Algorithm-Based Optimization. ACS Nano. https://doi.org/10.1021/acsnano.0c06472