Energy transfer between a nanosystem and its host fluid: a multiscale factorization approach.

Area of Science:

• Computational chemistry
• Biophysics
• Molecular dynamics

Background:

• Energy transfer is crucial for molecular function.
• Simulating energy transfer in large systems is computationally challenging.
• Existing methods struggle to bridge different time and length scales.

Purpose of the Study:

• To develop an efficient multiscale simulation framework for macromolecular energy transfer.
• To provide a mathematical formalism for coevolving coarse-grained and atomistic dynamics.
• To validate the approach using relevant biological examples.

Main Methods:

• Utilizing Newton's equations and Lie-Trotter factorization.
• Treating molecular energy as a coarse-grained variable.
• Simulating the coevolution of energy with atomistic degrees of freedom.

Main Results:

• Demonstrated that molecular energy evolves slower than atomic vibrations.
• Established Lie-Trotter factorization as a suitable framework for multiscale energy transfer.
• Presented a validated mathematical formalism and simulation workflow.

Conclusions:

• The proposed multiscale method enables efficient simulation of energy transfer.
• The framework accurately models energy flow in complex biological structures.
• This work offers a new tool for studying molecular dynamics and function.