中国物理B ›› 2020, Vol. 29 ›› Issue (11): 116103-.doi: 10.1088/1674-1056/abc0e3
所属专题: SPECIAL TOPIC — Machine learning in condensed matter physics
Zhilong Song(宋志龙)1, Xiwen Chen(陈曦雯)1, Fanbin Meng(孟繁斌)1, Guanjian Cheng(程观剑)1, Chen Wang(王陈)1, Zhongti Sun(孙中体)1,†(), Wan-Jian Yin(尹万健)1,‡()
收稿日期:
2020-07-06
修回日期:
2020-08-24
接受日期:
2020-10-14
出版日期:
2020-11-05
发布日期:
2020-11-03
Zhilong Song(宋志龙), Xiwen Chen(陈曦雯), Fanbin Meng(孟繁斌), Guanjian Cheng(程观剑), Chen Wang(王陈), Zhongti Sun(孙中体)†, and Wan-Jian Yin(尹万健)‡
Received:
2020-07-06
Revised:
2020-08-24
Accepted:
2020-10-14
Online:
2020-11-05
Published:
2020-11-03
Contact:
†Corresponding author. E-mail: Supported by:
Zhilong Song(宋志龙), Xiwen Chen(陈曦雯), Fanbin Meng(孟繁斌), Guanjian Cheng(程观剑), Chen Wang(王陈), Zhongti Sun(孙中体), Wan-Jian Yin(尹万健). [J]. 中国物理B, 2020, 29(11): 116103-.
Zhilong Song(宋志龙), Xiwen Chen(陈曦雯), Fanbin Meng(孟繁斌), Guanjian Cheng(程观剑), Chen Wang(王陈), Zhongti Sun(孙中体), and Wan-Jian Yin(尹万健). Machine learning in materials design: Algorithm and application[J]. Chin. Phys. B, 2020, 29(11): 116103-.
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Name | Function | URL |
---|---|---|
Pymatgen | Robust, open-source python library for materials analysis | https://pymatgen.org |
AFLOW π | A minimalist framework for high-throughput first principles calculations | http://aflowlib.org/src/aflowpi |
FireWorks | An open-source code for defining, managing, and executing calculation workflows | https://materialsproject.github.io/fireworks |
AiiDA | A workflow to automate complex numerical procedures of calculation | http://www.aiida.net |
Pymatflow | A workflow simplifier for research on materials science by means of ab initio simulation | http://pymatflow.readthedocs.org |
ASE | Setting up, steering, and analyzing atomistic simulations | https://wiki.fysik.dtu.dk/ase |
Atomate | Built on top of state-of-the-art open-source libraries: pymatgen, custodian, and FireWorks | https://atomate.org |
Custodian | A simple, robust, and flexible just-in-time (JIT) job management framework | https://pypi.org/project/custodian |
MPInterfaces | A python tool that enables high throughput analysis of interfaces using VASP, VASPsol, and MP tools | http://henniggroup.github.io/MPInterfaces |
Imeall | A database framework for the calculation of the atomistic properties of grain boundaries | https://github.com/Montmorency/imeall |
Pylada | A modular python framework to control physics simulations | http://pylada.github.io/pylada |
Pyiron | An integrated development environment (IDE) for computational materials science | https://pyiron.github.io |
"
"
Name | Description | URL |
---|---|---|
QML | A python toolkit for representation learning of properties of molecules and solids | https://www.qmlcode.org |
AMP | A modular approach to machine learning in atomistic simulations | https://amp.readthedocs.io |
Magpie | Materials-agnostic platform for informatics and exploration | https://github.com/amarkrishna/demo1 |
RDkit | A collection of cheminformatics and machine-learning software written in C++ and Python | https://github.com/rdkit/rdkit |
ChemML | A ML program suite for the analysis, mining, and modeling of chemical and materials data | https://pypi.org/project/chemml |
DScribe | Library of descriptors for machine learning in materials science | https://singroup.github.io/dscribe |
Matminer | A Python library for data mining the properties of materials | https://hackingmaterials.lbl.gov/matminer |
SchNet | A deep learning architecture for quantum chemistry | https://github.com/atomistic-machine-learning/SchNet |
DeepChem | Deep-learning models for drug discovery and quantum chemistry | http://github.com/deepchem/deepchem |
MEGNet | An implementation of DeepMind’s graph networks for universal machine learning in materials science | https://github.com/materialsvirtuallab/megnet |
CGCNN | Implement crystal graph convolutional neural networks to arbitrary crystal structures | https://github.com/txie-93/cgcnn |
"
Conventional | Deep learning | Tree-based | Descriptor | Active | Unsupervised | |
---|---|---|---|---|---|---|
Thermodynamic stability | [ | [ | [ | [ | [ | |
Band gap | [ | [ | [ | [ | [ | |
Superconductivity | [ | [ | [ | [ | [ | |
Thermal conductivity | [ | [ | [ | [ | [ | |
Curie temperature | [ | [ | [ | [ | ||
Bulk and shear moduli | [ | [ | [ | [ | ||
Debye temperature and heat capacity | [ | [ | ||||
Density of states | [ | [ | [ | |||
Dielectric breakdown strength | [ | [ | [ | |||
grain boundary structure and properties | [ | [ | [ | [ | [ | |
Lattice parameter | [ | [ | ||||
Lithium ion batteries SOC and conduction | [ | [ | [ | |||
melting temperature | [ | [ | [ |
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