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arXiv 2401.08069physics.chem-ph
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预测挑战:环丁酮超快电子衍射谱的第一性原理模拟

Prediction challenge: First principles simulation of the ultrafast electron diffraction spectrum of cyclobutanone

Jiří Suchan, Fangchun Liang, Andrew S. Durden, Benjamin G. Levine

AI总结:

本文采用TAB混合量子-经典模拟预测环丁酮激发至3s Rydberg态后的超快电子衍射信号,揭示C3和C2两条解离通道及其产物,并分析预测误差。

摘要:

长期以来,计算机模拟一直是超快实验的重要伙伴,能够将微观机制细节赋予低维光谱数据。然而,理论对超快实验结果进行先验预测的能力相对而言尚未得到充分检验。本文作为一项社区挑战的一部分,尝试在已有实验数据的背景下,利用最先进的理论预测即将进行的超快光化学实验的信号。具体而言,我们采用从头算Ehrenfest with collapse to a block(TAB)混合量子-经典模拟,描述环丁酮激发至3s Rydberg态后电子与原子核的实时演化。我们模拟了气相超快电子衍射(GUED)信号,以便与斯坦福直线加速器实验室即将开展的实验进行直接比较。在初始开环之后,观察到通过两个不同通道的解离:C3解离通道生成环丙烷和CO,C2通道生成CH$_2$CO和C$_2$H$_4$。对GUED信号的直接计算表明,开环中间体、C2产物和C3产物如何在GUED信号中被区分。我们还报告了对预测中预期误差的先验分析:在不知道实验结果的情况下,我们认为谱图中哪些特征被正确预测具有信心,哪些特征可能存在错误?

英文摘要:

Computer simulation has long been an essential partner of ultrafast experiments, allowing the assignment of microscopic mechanistic detail to low-dimensional spectroscopic data. However, the ability of theory to make a priori predictions of ultrafast experimental results is relatively untested. Herein, as a part of a community challenge, we attempt to predict the signal of an upcoming ultrafast photochemical experiment using state-of-the-art theory in the context of preexisting experimental data. Specifically, we employ ab initio Ehrenfest with collapse to a block (TAB) mixed quantum-classic simulations to describe the real-time evolution of the electrons and nuclei of cyclobutanone following excitation to the 3s Rydberg state. The gas-phase ultrafast electron diffraction (GUED) signal is simulated for direct comparison to an upcoming experiment at the Stanford Linear Accelerator Laboratory. Following initial ring-opening, dissociation via two distinct channels is observed: the C3 dissociation channel, producing cyclopropane and CO, and the C2 channel, producing CH$_2$CO and C$_2$H$_4$. Direct calculations of the GUED signal indicate how the ring-opened intermediate, the C2 products, and the C3 products can be discriminated in the GUED signal. We also report an a priori analysis of anticipated errors in our predictions: without knowledge of the experimental result, which features of the spectrum do we feel confident we have predicted correctly, and which might we have wrong?

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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