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Updated: Dec 3, 2025

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
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使用部分监督学习对晶体的基于结构的合成性预测

Jidon Jang1, Geun Ho Gu1, Juhwan Noh1

  • 1Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Republic of Korea.

Journal of the American Chemical Society
|October 26, 2020
PubMed
概括

预测材料合成是一项挑战. 使用图形卷积神经网络的新机器学习模型准确地预测了可合成性 (CLscore),改善了仅仅热力学稳定性之外的材料发现.

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