Suppr超能文献

跃迁路径飞行时间与非绝热电子跃迁

Transition Path Flight Times and Nonadiabatic Electronic Transitions.

作者信息

He Xin, Wu Baihua, Rivlin Tom, Liu Jian, Pollak Eli

机构信息

Beijing National Laboratory for Molecular Sciences, Institute of Theoretical and Computational Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China.

Chemical and Biological Physics Department, Weizmann Institute of Science, 76100 Rehovot, Israel.

出版信息

J Phys Chem Lett. 2022 Aug 4;13(30):6966-6974. doi: 10.1021/acs.jpclett.2c01425. Epub 2022 Jul 25.

Abstract

Transition path flight times are studied for scattering on two electronic surfaces with a single crossing. These flight times reveal nontrivial quantum effects such as resonance lifetimes and nonclassical passage times and reveal that nonadiabatic effects often increase flight times. The flight times are computed using numerically exact time propagation and compared with results obtained from the Fewest Switches Surface Hopping (FSSH) method. Comparison of the two methods shows that the FSSH method is reliable for transition path times only when the scattering is classically allowed on the relevant adiabatic surfaces. However, where quantum effects such as tunneling and resonances dominate, the FSSH method is not adequate to accurately predict the correct times and transition probabilities. These results highlight limitations in methods which do not account for quantum interference effects, and suggest that measuring flight times is important for obtaining insights from the time-domain into quantum effects in nonadiabatic scattering.

摘要

研究了在具有单个交叉点的两个电子表面上散射的跃迁路径飞行时间。这些飞行时间揭示了诸如共振寿命和非经典通过时间等重要的量子效应,并表明非绝热效应通常会增加飞行时间。使用数值精确的时间传播来计算飞行时间,并与从最少开关表面跳跃(FSSH)方法获得的结果进行比较。两种方法的比较表明,仅当散射在相关绝热表面上经典允许时,FSSH方法对于跃迁路径时间才是可靠的。然而,在诸如隧穿和共振等量子效应占主导的情况下,FSSH方法不足以准确预测正确的时间和跃迁概率。这些结果突出了未考虑量子干涉效应的方法的局限性,并表明测量飞行时间对于从时域深入了解非绝热散射中的量子效应很重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e436/9358656/6a55a084b064/jz2c01425_0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验