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applications | 4 days ago | |
cmake | 3 months ago | |
docs | 3 months ago | |
mindchemistry | 1 month ago | |
CMakeLists.txt | 3 months ago | |
LICENSE | 3 months ago | |
NOTICE | 3 months ago | |
README.md | 4 days ago | |
README_CN.md | 4 days ago | |
RELEASE.md | 4 days ago | |
RELEASE_CN.md | 4 days ago | |
build.sh | 3 months ago | |
requirements.txt | 4 days ago | |
setup.py | 3 months ago | |
version.txt | 3 months ago |
ENGLISH | 简体中文
Conventional chemistry studies have long been confronted with numerous challenges. The process of experimental design, synthesis, characterization, and analysis can be time-consuming, costly, and highly dependent on experts’ experiences.
The synergy between AI and chemistry offers unprecedented opportunities to overcome the limitations of conventional approaches and unlock new frontiers in scientific discovery and innovation. AI techniques can efficiently process vast amount of data, mining underneath patterns and generating predictive models. By leveraging AI, chemistry and material science researchers can accelerate the design and optimization of chemical processes and the design and analysis of novel materials.
MindSpore Chemistry(MindChemistry) is a toolkit built on MindSpore endeavoring to integrate AI with conventional chemistry research. It supports multi-scale tasks including molecular generation, property prediction and synthesis optimization on multiple chemistry systems such as organic, inorganic and composites chemistry systems. MindChemistry dedicates to enabling the joint research of AI and chemistry with high efficiency, and seek to facilitate an innovative paradigm of joint research between AI and chemistry, providing experts with novel perspectives and efficient tools.
2024.04.30
MindChemistry 0.1.0 is released.Electronic Structure Prediction:
Prediction of crystalline material properties:
Because MindChemistry is dependent on MindSpore, please click MindSpore Download Page according to the corresponding relationship indicated in the following table. Download and install the corresponding whl package.
MindChemistry | Branch | MindSpore | Python |
---|---|---|---|
master | master | \ | >=3.8 |
0.1.0 | r0.6 | >=2.2.12 | >=3.8 |
pip install -r requirements.txt
Hardware | OS | Status |
---|---|---|
Ascend 910 | Ubuntu-x86 | ✔️ |
Ubuntu-aarch64 | ✔️ | |
EulerOS-aarch64 | ✔️ | |
CentOS-x86 | ✔️ | |
CentOS-aarch64 | ✔️ |
Download source code from Gitee
git clone https://gitee.com/mindspore/mindscience.git
cd {PATH}/mindscience/MindChemistry
Compile in Ascend backend
bash build.sh -e ascend -j8
Install whl package
cd {PATH}/mindscience/MindChemistry/output
pip install mindchemistry_*.whl
Thanks goes to these wonderful people 🧑🤝🧑:
yufan, wangzidong, liuhongsheng, gongyue, gengchenhua, linghejing, yanchaojie
[1] Rao Z, Tung P Y, Xie R, et al. Machine learning-enabled high-entropy alloy discovery[J]. Science, 2022, 378(6615): 78-85.
[2] Batzner S, Musaelian A, Sun L, et al. E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials[J]. Nature communications, 2022, 13(1): 2453.
[3] Musaelian A, Batzner S, Johansson A, et al. Learning local equivariant representations for large-scale atomistic dynamics[J]. Nature communications, 2023, 14(1): 579.
MindScience is scientific computing kits for various industries based on the converged MindSpore framework.
Jupyter Notebook Python Unity3D Asset Pickle nesC other
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