affjljoo3581/Samsung-AI-Challenge-for-Scientific-Discovery
🥇Samsung AI Challenge 2021 1등 솔루션입니다🥇
Predicts crucial molecular properties like excitation energy gaps (e.g., between S1 and T1 states) from a molecule's 3D structure. This helps chemists and materials scientists understand how molecules will behave. You input 3D molecular structures, and it outputs the predicted energy gaps and other properties, assisting in chemical discovery and material design.
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Use this if you need to accurately predict molecular excitation energies and other properties from 3D molecular structures for scientific discovery or materials research.
Not ideal if your primary input is a 2D molecular representation like SMILES, or if you need to predict properties that are not highly dependent on the molecule's precise 3D geometry and atomic relationships.
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54
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7
Language
Python
License
Apache-2.0
Category
Last pushed
Nov 12, 2021
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