logo
ResearchBunny Logo
Filming movies of attosecond charge migration in single molecules with high harmonic spectroscopy

Physics

Filming movies of attosecond charge migration in single molecules with high harmonic spectroscopy

L. He, S. Sun, et al.

This groundbreaking study led by Lixin He and colleagues reveals the intricate dynamics of electron migration in molecules, providing a fascinating look at how light-matter interaction drives these processes. By employing machine learning to analyze high-order harmonics from fixed molecules, they unveil swirling patterns of electron holes in N2 and CO2, marking a significant advance in our understanding of ultrafast electron dynamics.

00:00
00:00
Playback language: English
Abstract
Electron migration in molecules is crucial for chemical reactions and biological functions after light-matter interaction. This study demonstrates the retrieval of complex amplitudes and phases of harmonics from single fixed-in-space molecules using machine learning analysis of high-order harmonics generated by two-color laser pulses. This allows for the construction of movies of laser-driven electron migration in N2 and CO2 molecules at 50-attosecond time steps, resolving angular dependence. The observed electron hole migration shows swirling patterns around atom centers, not just along the laser polarization direction. This work establishes a general scheme for studying ultrafast electron dynamics in molecules and controlling photochemical reactions.
Publisher
Nature Communications
Published On
Aug 06, 2022
Authors
Lixin He, Siqi Sun, Pengfei Lan, Yanqing He, Bincheng Wang, Pu Wang, Xiaosong Zhu, Liang Li, Wei Cao, Peixiang Lu, C. D. Lin
Tags
electron migration
high-order harmonics
machine learning
light-matter interaction
ultrafast dynamics
Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny