A Framework for Computing Transport Properties of Carbon Nanotube-based Conductance Biochemical Sensors

TL;DR

This paper introduces a fast computational framework for quantum conductance in carbon nanotube sensors, utilizing a novel parameterization and scalable algorithms to enhance biochemical detection capabilities.

Contribution

It presents a new parameterization method based on isospectral matrix flows and a scalable algorithm for quantum conductance calculations in nanotube sensors.

Findings

Carbon nanotubes are suitable for aromatic amino acid detection.

The framework enables rapid and accurate conductance calculations.

Potential improvements in biochemical sensing applications.

Abstract

In this paper we present a framework for fast quantum conductance calculations of carbon nanotube-based sensing devices targeting aromatic amino acids within a tight binding approximation. The method begins by a novel parameterization procedure based on isospectral matrix flows. With the properly parameterized Hamiltonian we employ a linearly scaling algorithm to compute the quantum conductance in the coherent transport regime. A few conclusions are presented regarding the suitability of carbon nanotubes in aromatic amino acid detection.