Unveiling the charge distribution of a GaAs-based nanoelectronic device: A large experimental dataset approach

Unveiling the charge distribution of a GaAs-based nanoelectronic device: A large experimental dataset approach

Blog Article

In quantum nanoelectronics, numerical simulations have become a ubiquitous tool.Yet the comparison with experiments is often done at a qualitative level or restricted to a single device with a handful of fitting parameters.In this work, we assess the predictive power of these simulations by comparing the results of a single model with a large experimental dataset of 110 grandpas best devices with 48 different geometries.

The devices are quantum point contacts of various shapes and sizes made with electrostatic gates deposited on top of a high mobility GaAs/AlGaAs two-dimensional electron gas.We study the pinch-off voltages applied on the gates to deplete the two-dimensional electron gas in various spatial positions.We argue that the pinch-off voltages are a very robust turbo air m3f24-1 signature of the charge distribution in the device.

The large experimental dataset allows us to critically review the modeling and arrive at a robust one-parameter model that can be calibrated in situ, a crucial step for making predictive simulations.