The present tensor-based recommender system database provides currently unknown chemically relevant compositions from database entries (ICSD, ICDD, and Springer Materials). If you use the recommender system database for academic purposes, please cite the following article [1].
The sqlite database of recommender-*.sqlite is distributed using Git LFS. The database can be downloaded separately from recommender.py. Enter the link of recommender-*.sqlite, and click on the Download link.
> python3 $(recommender)/recommender.py -e Al Si O -n 4 -d recommender-2024-07-01.sqlite
# Composition, Score
Al2Ba2O7Si1 0.74232
Al2O12Si3Zn3 0.4814
Al1Li1O12Si5 0.41613
Al2Ba3O14Si4 0.39355
Al2O14Si4Sr3 0.34611
> python3 $(recommender)/recommender.py -e N -n 4 -d recommender-2024-07-01.sqlite
# Composition, Score
Ba2Li3N4Sb1 0.48867
Ba2Cu1Li1N2 0.4738
Ba3Li4N6Si2 0.46901
Li3N4Sb1Sr2 0.4068
Ba3Ge2Li4N6 0.39811
Li1Mo2N7Sr4 0.3572
> python3 $(recommender)/recommender.py -e Mg Zn -n 2 3 -d recommender-2024-07-01.sqlite
# Composition, Score
Zn1Mg3 0.39168
Zn1Mg2 0.37147
Mg1Zn4 0.26386
Mg1Zn3 0.24094
Zn1Mg4 0.2309
Mg1Zn6 0.16608
> python3 $(recommender)/recommender.py -e Mg Zn -n 2 3 --threshold 0.3 -d recommender-2024-07-01.sqlite
# Composition, Score
Zn1Mg3 0.39168
Zn1Mg2 0.37147
- elements: None
- n (number of atomic species): 3
- threshold: 0.01
usage: recommender.py [-h] [-d DATABASE] [-n [NARY ...]] [-e [ELEMENTS ...]]
[--threshold THRESHOLD]
options:
-h, --help show this help message and exit
-d DATABASE, --database DATABASE
Database name
-n [NARY ...], --nary [NARY ...]
Number of atomic species in recommended compositions
-e [ELEMENTS ...], --elements [ELEMENTS ...]
Elements in recommended compositions
--threshold THRESHOLD
Score threshold for recommendation