First-principles quantum transport investigation of Fe-functionalized phosphorene for high-sensitivity NO2 detection
Year: 2026
Type: article
Abstract: Significantly sensitive and energy-efficient gas sensors using 2D materials are an essential research topic for environmental monitoring applications. In this work, we carried out a comprehensive study on an iron-functionalized black phosphorene interface for nitrogen dioxide gas detection using a first-principles quantum transport method. Density functional theory and the non-equilibrium Green’s function method were employed to investigate structural stability, electronic structure modulation, charge transfer, and bias-dependent transport characteristics. Numerical convergence of self-consistent field calculations confirms computational stability, as the total energy change is found to be below 1.0 × 10 −4 eV. The adsorption energy of −2.67 eV confirms strong chemisorption of NO 2 on the Fe active site. The Hirshfeld population method indicates a charge transfer of −0.16 e on the NO 2 molecule and a Fe atom with a charge of + 0.21 e, confirming it as an electron donor site. The analysis of the electronic structure indicates a reduction in the band gap of 54% from 0.04895 eV to 0.02241 eV and a shift in the Fermi level of 0.145 eV. The work function is increased by 0.34 eV, indicating that interfacial dipoles are formed. Transmission spectra indicate a suppression in conducting channels close to the Fermi level. Bias-dependent transport simulations indicate a maximum sensitivity of 32% for a voltage of 0.2 V. Quasi-ohmic behavior is indicated with a rectification ratio close to unity. Hence, the device is confirmed to operate in a resistive type p-type mode. Fe-functionalized phosphorene is confirmed to be a promising platform for detecting NO₂ with high sensitivity and low voltage.
Source: Next Materials
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,280
OpenAlex ID: W7153983372