# Quantized transport, strain-induced perfectly conducting modes and valley filtering on shape-optimized graphene Corbino devices

## TL;DR

This paper demonstrates how shape-optimized graphene Corbino devices can utilize strain-induced pseudomagnetic fields for directional electronic transmission and valley filtering, advancing valleytronics applications.

## Contribution

It introduces a framework for designing graphene devices with optimal shapes to generate specific pseudomagnetic field profiles for electronic control.

## Key findings

- Strain-engineered graphene can produce tunable pseudomagnetic fields.
- Shape optimization enables directional control of electronic transmission.
- Devices can filter charge carriers by valley and current direction.

## Abstract

The extreme mechanical resilience of graphene and the peculiar coupling it hosts between lattice and electronic degrees of freedom have spawned a strong impetus towards strain-engineered graphene where, on the one hand, strain augments the richness of its phenomenology and makes possible new concepts for electronic devices and, on the other hand, new and extreme physics might take place. Here, we demonstrate that the shape of substrates supporting graphene sheets can be optimized for approachable experiments where strain-induced pseudomagnetic fields (PMF) can be tailored by pressure for directionally selective electronic transmission and pinching-off of current flow down to the quantum channel limit. The Corbino-type layout explored here furthermore allows filtering of charge carriers according to valley and current direction, which can be used to inject or collect valley-polarized currents, thus realizing one of the basic elements required for valleytronics. Our results are based on a framework developed to realistically determine the combination of strain, external parameters, and geometry optimally compatible with the target spatial profile of a desired physical property --- the PMF in this case. Characteristic conductance profiles are analyzed through quantum transport calculations on large graphene devices having the optimal shape.