CO and NO Detection by MN 4 @ SWCNT in Background Gases: Multiscale DFT , Microkinetic, Boltzmann Transport Study

ABSTRACT Detecting hazardous gases like CO and NO at room temperature is vital for environmental and health monitoring. While single‐walled carbon nanotubes (SWCNTs) are a potential material for a room‐temperature sensor, their pristine forms exhibit very weak adsorption toward CO and NO gases. This study investigates the sensing performance of SWCNTs embedded with transition metal‐nitrogen (MN 4 ) active sites (M = Mn, Fe Co, Ni, Cu). These active sites are known for their ability to properly bind small gases in various catalytic applications. By combining density functional calculations, microkinetic simulations, and Boltzmann conductivity calculations, we account for atmospheric background gases to provide a realistic evaluation of sensor selectivity and response. Our findings indicate that relative adsorption energies govern surface coverage, while changes in conductivity correlate with the density of states near the Fermi level. Our results show that the CuN 4 @SWCNT system emerges as the optimal candidate for CO detection within the 1–10 5 ppm working range. The NiN 4 @SWCNT system is also viable for CO detection in this range, provided that interfering species such as NO and NO 2 are absent. For NO detection, the NiN 4 @SWCNT system is identified as the best performer, operating effectively in the ultra‐low concentration range (~0.01–100 ppb) with high selectivity. This work also elucidates the fundamental trade‐off between adsorption strength and recovery time, offering a robust theoretical framework for designing highly selective and reversible gas sensors relevant to health risk monitoring and early warning applications.

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Publication Details

Journal
Journal of Computational Chemistry
Published
2026-09-11
DOI
https://doi.org/10.1002/jcc.70507
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
Field-Weighted Citation Impact
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article

CO and NO Detection by MN 4 @ SWCNT in Background Gases: Multiscale DFT , Microkinetic, Boltzmann Transport Study

Adhitya Gandaryus Saputro, Ira Puspitasari, Farrel Dzaudan Naufal, Febdian Rusydi et al.
Journal of Computational Chemistry
Gas Sensing Nanomaterials and Sensors
article

CO and NO Detection by MN 4 @ SWCNT in Background Gases: Multiscale DFT , Microkinetic, Boltzmann Transport Study

Adhitya Gandaryus Saputro, Ira Puspitasari, Farrel Dzaudan Naufal, Febdian Rusydi, Chin-Sung Hsiao, Imran Shakir, Dicky Setianto
article en

Abstract

ABSTRACT Detecting hazardous gases like CO and NO at room temperature is vital for environmental and health monitoring. While single‐walled carbon nanotubes (SWCNTs) are a potential material for a room‐temperature sensor, their pristine forms exhibit very weak adsorption toward CO and NO gases. This study investigates the sensing performance of SWCNTs embedded with transition metal‐nitrogen (MN 4 ) active sites (M = Mn, Fe Co, Ni, Cu). These active sites are known for their ability to properly bind small gases in various catalytic applications. By combining density functional calculations, microkinetic simulations, and Boltzmann conductivity calculations, we account for atmospheric background gases to provide a realistic evaluation of sensor selectivity and response. Our findings indicate that relative adsorption energies govern surface coverage, while changes in conductivity correlate with the density of states near the Fermi level. Our results show that the CuN 4 @SWCNT system emerges as the optimal candidate for CO detection within the 1–10 5 ppm working range. The NiN 4 @SWCNT system is also viable for CO detection in this range, provided that interfering species such as NO and NO 2 are absent. For NO detection, the NiN 4 @SWCNT system is identified as the best performer, operating effectively in the ultra‐low concentration range (~0.01–100 ppb) with high selectivity. This work also elucidates the fundamental trade‐off between adsorption strength and recovery time, offering a robust theoretical framework for designing highly selective and reversible gas sensors relevant to health risk monitoring and early warning applications.

Journal of Computational ChemistryVol. 47(24)
Bandung Institute of Technology (ID), Asia University (TW), Universitas Airlangga (ID), Islamic University of Madinah (SA)
Openalex Percentile: Top 20%
Gas Sensing Nanomaterials and Sensors
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