First-principles study of 2D V–V binary material <i>α</i> -AsN for VOCs-sensing applications

Increased emissions of volatile organic compounds (VOCs) are prone to cause health issues like cancer and central nervous system disorders, making the development of efficient VOCs-sensing materials crucial. Monolayer<i>α</i>-AsN, a two-dimensional (2D) V-V binary material with a wrinkled honeycomb structure, features better environmental stability (higher cohesive energy than black phosphorus, BP) and tunable electrical properties (unlike single-target VOC-sensing TMDs). It overcomes flaws of existing 2D sensors (BP's poor stability, TMDs' narrow selectivity) while retaining high surface-to-volume ratio, and shows superior adsorption efficiency and selectivity for alcohol VOCs versus BP and acetone-specialized Janus TMDs. However, its VOCs-sensing performance remains uninvestigated. This study employed density functional theory and nonequilibrium Green's function to systematically investigate the adsorption and sensing behaviors of monolayer<i>α</i>-AsN toward the five VOCs. Electronic localization function analysis confirmed physical adsorption (no chemical bonding) between<i>α</i>-AsN and all VOCs. Among the tested VOCs, methanol and ethanol exhibited the highest adsorption energy and density (ethanol slightly higher), with ultra-low detection limits (7.69 × 10<sup>-</sup>⁴ p.p.b. for methanol and 4.88 × 10<sup>-</sup>⁵ p.p.b. for ethanol). Critically, methanol adsorption reduced<i>α</i>-AsN's current by 30%, while ethanol increased it by 100%. These findings demonstrate that monolayer<i>α</i>-AsN holds great application potential for the selective detection of methanol and ethanol.

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Journal
Nanotechnology
Published
2026-01-05
DOI
https://doi.org/10.1088/1361-6528/ae3318
Primary Topic
2D Materials and Applications
Type
article
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article

First-principles study of 2D V–V binary material α -AsN for VOCs-sensing applications

Shuangying Lei, Chia-Hsiang Hung, Zixian Li, Zai-fa Zhou
Nanotechnology
2D Materials and Applications
article

First-principles study of 2D V–V binary material α -AsN for VOCs-sensing applications

Shuangying Lei, Chia-Hsiang Hung, Zixian Li, Zai-fa Zhou
article en

Abstract

Increased emissions of volatile organic compounds (VOCs) are prone to cause health issues like cancer and central nervous system disorders, making the development of efficient VOCs-sensing materials crucial. Monolayer<i>α</i>-AsN, a two-dimensional (2D) V-V binary material with a wrinkled honeycomb structure, features better environmental stability (higher cohesive energy than black phosphorus, BP) and tunable electrical properties (unlike single-target VOC-sensing TMDs). It overcomes flaws of existing 2D sensors (BP's poor stability, TMDs' narrow selectivity) while retaining high surface-to-volume ratio, and shows superior adsorption efficiency and selectivity for alcohol VOCs versus BP and acetone-specialized Janus TMDs. However, its VOCs-sensing performance remains uninvestigated. This study employed density functional theory and nonequilibrium Green's function to systematically investigate the adsorption and sensing behaviors of monolayer<i>α</i>-AsN toward the five VOCs. Electronic localization function analysis confirmed physical adsorption (no chemical bonding) between<i>α</i>-AsN and all VOCs. Among the tested VOCs, methanol and ethanol exhibited the highest adsorption energy and density (ethanol slightly higher), with ultra-low detection limits (7.69 × 10<sup>-</sup>⁴ p.p.b. for methanol and 4.88 × 10<sup>-</sup>⁵ p.p.b. for ethanol). Critically, methanol adsorption reduced<i>α</i>-AsN's current by 30%, while ethanol increased it by 100%. These findings demonstrate that monolayer<i>α</i>-AsN holds great application potential for the selective detection of methanol and ethanol.

NanotechnologyVol. 37(4)
Southeast University (CN)
Openalex Percentile: Top 97%
2D Materials and Applications
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First-principles study of 2D V–V binary material <i>α</i> -AsN for VOCs-sensing applications — Shuangying Lei, Chia-Hsiang Hung, et al. · Nanotechnology (2026) | TGRS Research Map | TGRS