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arXiv · 2502.11762

Layer-Resolved Quantum Transport in Twisted Bilayer Graphene: Counterflow and Machine Learning Predictions

Matheus H. Gobbo Kuhn·L. A. Silva·D. A. Bahamon
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Abstract

The layer-resolved quantum transport response of a twisted bilayer graphene device is investigated by driving a current through the bottom layer and measuring the induced voltage in the top layer. Devices with four- and eight-layer differentiated contacts were analyzed, revealing that in a nanoribbon geometry (four contacts), a longitudinal counterflow current emerges in the top layer, while in a square-junction configuration (eight contacts), this counterflow is accompanied by a transverse, or Hall, component. These effects persist despite weak coupling to contacts, onsite disorder, lattice relaxation and variations in device size. The observed counterflow response indicates a circulating interlayer current, which generates an in-plane magnetic moment excited by the injected current. Finally, due to the intricate relationship between the electrical layer response, energy, and twist angle, a clusterized machine learning model was trained, validated, and tested to predict various conductances.

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Matheus H. Gobbo Kuhn, L. A. Silva, D. A. Bahamon. 2025-02-17. Layer-Resolved Quantum Transport in Twisted Bilayer Graphene: Counterflow and Machine Learning Predictions. https://doi.org/10.1103/d98y-sv8j

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