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Optimized Fabrication Procedure for High-Quality Graphene-based Moiré Superlattice Devices

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Accelerated Percolation Path Identification in Twisted Bilayer Graphene.

Benjamin H Sjølin¹, William Sandholt Hansen¹, Katrine Hjort¹

¹Department of Energy Conversion and Storage, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark.

Journal of Chemical Theory and Computation

|February 25, 2026

Summary

This summary is machine-generated.

We developed a fast computational method to find ion pathways in twisted bilayer graphene. This approach reveals how twist angle affects ion movement, crucial for battery materials.

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Area of Science:

Computational Materials Science
Condensed Matter Physics
Electrochemistry

Background:

Twisted bilayer graphene is a promising material for energy storage applications.
Efficient ion transport is critical for the performance of battery anode materials.
Identifying ion diffusion pathways is computationally intensive.

Purpose of the Study:

To present a novel computational workflow for accelerating the identification of percolation pathways in twisted bilayer graphene.
To investigate the influence of twist angle on Li-ion diffusion in twisted bilayer graphene.
To establish a general and efficient method for mapping percolation paths in materials.

Main Methods:

Utilized charge density from a single ab initio Density Functional Theory calculation.
Developed a three-step workflow: intercalation site identification, migration graph generation, and path-finding algorithm.
Applied the workflow to Li-diffusion in 21 twist-angle structures of twisted bilayer graphene.

Main Results:

Successfully identified physically plausible percolation pathways for Li-diffusion in all tested twisted bilayer graphene structures.
Discovered a significant relationship between the twist angle and the ease of ion percolation.
Demonstrated the computational workflow's speed and generality compared to conventional methods.

Conclusions:

The novel computational workflow efficiently maps ion percolation pathways in twisted bilayer graphene.
Twist angle is a critical parameter influencing ion diffusion kinetics in these materials.
The method facilitates rapid exploration of ion transport in diverse 2D and 3D materials for energy applications.