Decoding the conductance of disordered nanostructures: a quantum inverse problem

TL;DR

This paper presents a robust inversion method to decode conductance spectra and extract impurity information in disordered nanoscale devices, applicable to simple and complex materials.

Contribution

It extends a previously proposed inversion methodology to identify impurity concentration and nature from conductance spectra in various nanoscale systems.

Findings

Method successfully decodes conductance spectra for simple and complex materials.

Robustness confirmed across different electronic structures.

Able to probe disorder distribution on sublattice structures.

Abstract

Obtaining conductance spectra for a concentration of disordered impurities distributed over a nanoscale device with sensing capabilities is a well-defined problem. However, to do this inversely, i.e., extracting information about the scatters from the conductance spectrum alone, is not an easy task. In the presence of impurities, even advanced techniques of inversion can become particularly challenging. This article extends the applicability of a methodology we proposed capable of extracting composition information about a nanoscale sensing device using the conductance spectrum. The inversion tool decodes the conductance spectrum to yield the concentration and nature of the disorders responsible for conductance fluctuations in the spectra. We present the method for simple one-dimensional systems like an electron gas with randomly distributed delta functions and a linear chain of atoms. We prove the generality and robustness of the method using materials with complex electronic structures like hexagonal boron nitride, graphene nanoribbons, and carbon nanotubes. We also go on to probe the distribution of disorders on the sublattice structure of the materials using the proposed inversion tool.