This repository contains the code implementation of the CSP method, as discussed in the paper Phase Prediction via Crystal Structure Similarity in the Periodic Number Representation, developed by the TCCDEM team.
This work introduces a novel strategy for crystal structure prediction founded upon the principle of chemical similarity. Our method uses Mendeleev's Periodic Number (PN) as a quantitative measure of substitutability to identify potential crystal structures for unexplored chemical systems. Representation of the workflow for predicting stable materials based on PN similarity is shown below.
PNcsp is a generaliezed version of this workflow. It scans the OQMD for a desired chemical system for given order of neighbors and proposes initial crystal structures that are ready for further analysis.
PLEASE NOTE: the PNcsp code is under active development. Bug reports are welcomed in the GitHub issues!
This program is based on Python 3 under Anaconda.
- Clone the repository.
- Open terminal and locate the directory.
- Install reuqirements or run:
pip install -r requirements.txt- Help page:
python PNcsp.py -h- Run the Python code:
python PNcsp.py <formula> -n <neighbor_order> -f <energy_filter> -t <sleep_time><formula>: Pretty formula of chemical system for query (Ex. Cu2Mn1Al1)
<neighbor_order>: Order of neighbors to be considered in the similarity search.. (Default: 1 (first order neighbors))
<energy_filter>: Selected neighbors are limited to those below the energy filter value. (default: 0) unit: [eV/atom]. Use "none" to disable filter.
<sleep_time>: Sets sleep time between queries. Excessive number of queries may cause the server to halt.(default: "none")
Created prototypes are shown in "output" folder in current directory.
python Similarity.py Na2Cl1 -n 3 -f 0.1