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使用深度学习语言模型对材料的基于组成的氧化状态预测

Nihang Fu1, Jeffrey Hu1,2, Ying Feng3

  • 1Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29201, USA.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|August 8, 2023
PubMed
概括

预测无机化合物的氧化状态 (OS) 现在可以使用一种新的深度学习模型,BERTOS. 这种人工智能方法只从化学成分准确地确定OS,有助于发现新材料.

关键词:
深度学习是一种深度学习.语言模型语言模型材料的发现发现.材料选 材料选 材料选 材料选神经网络的神经网络的神经网络氧化状态是指氧化状态.变压器的变压器是一个变压器.

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