Enhancing the sensitivity and selectivity of pyrene-based sensors for detection of small gaseous molecules via destructive quantum interference

TL;DR

This paper demonstrates that exploiting destructive quantum interference in pyrene-based molecular sensors significantly enhances their ability to detect and distinguish small gaseous molecules like NO2, H2O, and NH3.

Contribution

It introduces a novel sensing mechanism based on destructive quantum interference in pyrene molecules, enabling high sensitivity and selectivity for gas detection.

Findings

Destructive quantum interference can be used to calibrate sensor sensitivity.

Fano resonance enhances chemiresistive response for NO2 detection.

Sensor sensitivity can be increased by nearly two orders of magnitude.

Abstract

Graphene-based sensors are exceptionally sensitive with high carrier mobility and low intrinsic noise, and have been intensively investigated in the past decade. The detection of individual gas molecules has been reported, albeit the underlying sensing mechanism is not yet well understood. We focus on the adsorption of NO$_2$, H$_2$O, and NH$_3$ on a molecular junction with a pyrene core, which can be considered as a minimal graphene-like unit. We systematically investigate the chemiresistive response within the framework of density functional theory and non-equilibrium Green's functions. We highlight the fundamental role of quantum interference (QI) in the sensing process, and we propose it as a paradigmatic mechanism for sensing. Owing to the open-shell character of NO$_2$, its interaction with pyrene gives rise to a Fano resonance thereby triggering the strongest chemiresistive response, while the weaker interactions with H$_2$O and NH$_3$ result in lower sensitivity. We demonstrate that by exploiting destructive QI arising in the meta-substituted pyrene, it is possible to calibrate the sensor to enhance both its sensitivity and chemical selectivity by almost two orders of magnitude so that individual molecules can be detected and distinguished. These results provide a fundamental strategy to design high-performance chemical sensors with graphene functional blocks.