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English(EN) Parity-equivariant prediction of conformer-resolved electronic circular dichroism spectra accelerates absolute configuration assignment

PhysECD框架通过精确的ECD光谱预测加速手性分子分析

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了PhysECD，这是一个新设计的机器学习框架，用于预测电子圆二色谱（ECD）谱图。该方法比传统的瞬态密度泛函理论（TDDFT）计算速度显著更快，TDDFT目前用于手性分子的绝对构型分配。PhysECD达到了最先进的准确度，并已通过实验数据进行了验证，为复杂的分子分析提供了一种有前景的替代方案。 AI

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PhysECD框架通过精确的ECD光谱预测加速手性分子分析

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该集群包含一篇详细介绍用于科学研究的新计算方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Yi Jiang, Letian Chen, Runhan Shi, Lea Bae, Zheng Ling, Dong Ha Kim, Tong Zhu, Yang Yang ·

    对称等变预测解析构象的电子圆二色谱加速绝对构型分配

    arXiv:2608.21892v2 Announce Type: replace-cross Abstract: Electronic circular dichroism (ECD) is a key experimental probe for assigning the absolute configuration of chiral molecules, but interpreting measured spectra often requires costly time-dependent density functional theory…

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