MLatticeABC is a random forest machine learning model with a new feature set combined with the standard composition features such as Magpie descriptors for effective lattice constant prediction.
If you find our software is useful, please cite it as:
Li Y, Yang W, Dong R, et al. MLatticeABC: generic lattice constant prediction of crystal materials using machine learning[J]. ACS omega, 2021, 6(17): 11585-11594.
Developed in 2020.9-10 at
School of Mechanical Engineering
Guizhou University, Guiyang, China
Machine Learning and Evolution Laboratory
Department of Computer Science and Engineering
University of South Carolina, Columbia, USA
Prediction performance of MLatticeABC in terms of R2 score for a,b,c over different crystal systems （10 repeats of random split 9:1)
| Crystal system | train set size | test set size | a | b | c |
|---|---|---|---|---|---|
| Cubic | 16492 | 1833 | 0.979±0.016 | ||
| Hexagonal | 8318 | 925 | 0.892±0.019 | 0.760±0.061 | |
| Trigonal | 9977 | 1109 | 0.843±0.025 | 0.705±0.065 | |
| Tetragonal | 13188 | 1466 | 0.846±0.024 | 0.685±0.044 | |
| Orthorhombic | 24120 | 2681 | 0.770±0.019 | 0.579±0.074 | 0.638±0.028 |
| Monoclinic | 26884 | 2988 | 0.520±0.021 | 0.507±0.016 | 0.489±0.029 |
| Triclinic | 13767 | 1530 | 0.800±0.022 | 0.771±0.014 | 0.650±0.056 |
To use MLatticeABC you need to create an environment with the correct dependencies. Using Anaconda this can be accomplished with the follow commands:
conda create --name mlatticeabc python=3.6
conda activate mlatticeabc
conda install --channel conda-forge pymatgen
pip install matminer
pip install scikit-learn==0.23.1Once you have setup an environment with the correct dependencies you can install mlatticeabc using the following commands:
conda activate mlatticeabc
git clone https://github.com/usccolumbia/MLatticeABC
cd MLatticeABC
pip install -e .Pre-trained models are stored in google drive. Download the file model.zip from from the drive. After downing the file, copy it to MLatticeABC and extract it. the Model folder should be in the MLatticeABC directory after the extraction is completed.
In order to test your installation you can run the following example from your MLatticeABC directory:
cd /path/to/MLatticeABC/
python predict.py -i full_formula -s crystal_system
for example:
python predict.py -i Mn16Zn24Ge24O96 -s cubic
python predict.py -i Mn16Zn24Ge24O96The following cyrstal_system values are accepted
crystal # crystal system unknown.
cubic
hexagonal
trigonal
tetragonal
orthorhombic
monoclinic
triclinic