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Production of Synthetic Nuclear Melt Glass

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Published on: January 4, 2016

Nonadiabatic effects in electronic and nuclear dynamics.

Martin P Bircher¹, Elisa Liberatore¹, Nicholas J Browning¹

¹Laboratory of Computational Chemistry and Biochemistry, Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.

Structural Dynamics (Melville, N.Y.)

|January 30, 2018

Summary

Ultrafast phenomena often involve nonadiabatic effects, requiring advanced computational methods beyond the Born-Oppenheimer approximation. This review explores these methods for describing electronic and nuclear quantum dynamics in various processes.

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Area of Science:

Quantum dynamics
Ultrafast phenomena
Computational chemistry

Background:

Ultrafast processes frequently exhibit nonadiabatic effects.
The Born-Oppenheimer approximation and static models are insufficient for describing these dynamics.
A time-dependent quantum mechanical treatment of both electrons and nuclei is necessary.

Purpose of the Study:

To review nonadiabatic processes in electronic and nuclear dynamics.
To provide an overview of computational methods for simulating these phenomena.
To illustrate the application of these methods in understanding ultrafast science.

Main Methods:

Discussion of theoretical approaches beyond the Born-Oppenheimer approximation.
Overview of methods ranging from full quantum solutions to semiclassical and classical frameworks.
Focus on time-dependent quantum dynamics simulations.

Main Results:

Identification of key nonadiabatic processes: tunnel ionization, conical intersections, vibrational mode coupling.
Presentation of a hierarchy of computational methods for simulating nonadiabatic dynamics.
Demonstration of simulation power through applications and comparison with experimental data.

Conclusions:

Advanced computational methods are crucial for understanding nonadiabatic effects in ultrafast science.
The reviewed methods enable accurate descriptions of complex quantum dynamics.
Confrontation with experimental measurements validates the utility of these simulation tools.