Statistics for topic materials-science
RepositoryStats tracks 632,784 Github repositories, of these 100 are tagged with the materials-science topic. The most common primary language for repositories using this topic is Python (57). Other languages include: Jupyter Notebook (19)
Stargazers over time for topic materials-science
Most starred repositories for topic materials-science (view more)
Trending repositories for topic materials-science (view more)
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Pro...
A deep learning package for many-body potential energy representation and molecular dynamics
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Pro...
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Pro...
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
A deep learning package for many-body potential energy representation and molecular dynamics
Evaluation of universal machine learning force-fields https://arxiv.org/abs/2412.10516
A foundational potential energy dataset for materials
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Pro...
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
A deep learning package for many-body potential energy representation and molecular dynamics
A foundational potential energy dataset for materials
Home for GSAS-II: crystallographic and diffraction-based structural characterization of materials
Evaluation of universal machine learning force-fields https://arxiv.org/abs/2412.10516
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
Graph-Aware Attention for Adaptive Dynamics in Transformers
Evaluation of universal machine learning force-fields https://arxiv.org/abs/2412.10516
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
A deep learning package for many-body potential energy representation and molecular dynamics
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Pro...
Home for GSAS-II: crystallographic and diffraction-based structural characterization of materials
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
