# Bismuth iodide@carbon nanotube nanohybrids for sensitive detection of low concentrations of benzene

Ikanyeng Serero, Emmanuel Flahaut, George Chimowa

► To cite this version:

Ikanyeng Serero, Emmanuel Flahaut, George Chimowa. Bismuth iodide@carbon nanotube nanohybrids for sensitive detection of low concentrations of benzene. Journal of Applied Physics, 2025, 137 (23), pp.234503. 10.1063/5.0269755. hal-05127684

HAL Id: hal-05127684

https://hal.science/hal-05127684v1

Submitted on 24 Jun 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Bismuth iodide@carbon nanotube nanohybrids for sensitive detection of low concentrations of benzene

Ikanyeng A. M. Serero iD; Emmanuel Flahaut iD; George Chimowa iD

<figure><img src="image_2.png" /></figure>

Check for updates

J. Appl. Phys. 137, 234503 (2025)

https://doi.org/10.1063/5.0269755

<figure><img src="image_3.png" /></figure>

View
Online

<figure><img src="image_4.png" /></figure>

Export
Citation

## Articles You May Be Interested In

ZnO/graphene heterostructure nanohybrids for optoelectronics and sensors

J. Appl. Phys. (August 2021)

Performance experimental investigation of novel multifunctional nanohybrids on enhanced oil recovery

AIP Conf. Proc. (January 2018)

Ferromagnetism of double-walled carbon nanotubes

Appl. Phys. Lett. (June 2010)

<figure><img src="image_5.png" /></figure>

AIP
Publishing

<figure><img src="image_6.png" /></figure>

Journal of Applied Physics

Special Topics
Open for Submissions

Learn More

<figure><img src="image_7.png" /></figure>

AIP
Publishing
# Bismuth iodide@carbon nanotube nanohybrids for sensitive detection of low concentrations of benzene

Cite as: J. Appl. Phys. **137**, 234503 (2025); doi: 10.1063/5.0269755

Submitted: 7 March 2025 · Accepted: 1 June 2025 ·

Published Online: 17 June 2025

<figure><img src="image_8.png" /></figure>

View Online

<figure><img src="image_9.png" /></figure>

Export Citation

<figure><img src="image_10.png" /></figure>

CrossMark

Ikanyeng A. M. Serero,<fnref n="1" /> ID Emmanuel Flahaut,<fnref n="2" /> ID and George Chimowa<fnref n="1" />,ª ID

## AFFILIATIONS

## ABSTRACT

The timely and accurate detection of volatile organic compounds (VOCs), particularly aromatic compounds such as benzene, toluene, and xylene, is critical for environmental monitoring and industrial safety. Benzene is a known carcinogen with strict exposure limits [Occupational Safety and Health Administration: 1 ppm 8 h—time-weighted average, 5 ppm short-term exposure limit; WHO guidelines: ~17 µg/m³ (~5.5 ppb) for 10⁻⁴ lifetime risk]. This study investigated the gas-sensing performance of bismuth iodide (BiI₃)-carbon nanotube (DWNT) nanohybrids (BiI₃@DWNT). The sensor demonstrated high sensitivity to benzene with response/recovery times of 35.2 and 73.3 s, respectively, and minimal cross-sensitivity to alkanes (hexane and hexadecane) under tested conditions. The enhanced performance is attributed to charge transfer effects, quantum confinement effects, and improved gas adsorption. Furthermore, the gas sensor operates efficiently at room temperature, making it an energy-efficient alternative. These findings highlight the potential of BiI₃@DWNT nanohybrids as a promising platform for next-generation VOC sensors.

© 2025 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). https://doi.org/10.1063/5.0269755

## I. INTRODUCTION

The detection of aromatic volatile organic compounds (VOCs), such as benzene, toluene, ethylbenzene, and xylene (BTEX), is of significant importance due to their widespread presence in industrial and urban environments and their well-documented health hazards.<fnref n="1" /> These compounds are known carcinogens and neurotoxicants, with prolonged exposure leading to severe respiratory conditions and organ damage. For instance, the Occupational Safety and Health Administration (OSHA) has set a permissible exposure limit for benzene at 1 part per million (ppm) averaged over an 8 h workday,<fnref n="2" /> underscoring the critical need for accurate detection in occupational settings. Additionally, as environmental regulations become more stringent, there is an increasing demand for continuous air quality monitoring to detect and control BTEX emissions in industrial and residential settings. While conventional analytical techniques such as gas chromatography–mass spectrometry (GC–MS) provide high sensitivity and

specificity, they are often costly, require bulky instrumentation, and are not ideal for real-time, portable applications.³ As a result, there is a growing need for miniaturized, cost-effective, and selective gas sensors capable of detecting aromatic VOCs under ambient conditions.

Chemoresistive gas sensors have emerged as promising alternatives due to their simplicity, low-power consumption, and ability to be integrated into portable sensing platforms.³ Many existing gas sensors, particularly those based on metal oxide semiconductors (MOS) such as NiO, CuO, and ZnO, require high operating temperatures (300°–600°) to enhance adsorption and promote charge transfer reactions.⁴ While high-temperature MOS sensors can achieve good sensitivity and selectivity, they suffer from increased power consumption, structural degradation over time (due to the high operating temperatures), and potential interference from non-target gases.³,⁴ These limitations highlight the need for low-power gas sensors that can effectively operate at room temperature while maintaining high sensitivity and selectivity.

<footnote n="1">¹Department of Physics and Astronomy, Botswana International University of Science and Technology, Private Bag 16, Palapye, Botswana</footnote>

<footnote n="2">²CIRIMAT, Université Toulouse, de Toulouse INP, CNRS, 118 Route de Narbonne, Toulouse 31062, France</footnote>

<footnote>ªAuthor to whom correspondence should be addressed: chimowag@biust.ac.bw</footnote>
The use of nanomaterials has provided a pathway toward
improved room-temperature gas sensing by offering high surface
areas, tunable electronic properties, and enhanced gas adsorption
characteristics.⁵,⁶ However, these sensors face several limitations,
such as slow recovery times, and limited selectivity, particularly for
non-polar compounds.⁶ Two-dimensional (2D) nanomaterials,
such as bismuth oxyhalides (BiOX), graphene oxide, and MXenes,
have demonstrated enhanced gas adsorption and charge transfer
properties, making them attractive candidates for next-generation
gas sensors.⁷ Among these, bismuth-based materials have gained
increasing attention due to their low toxicity, high environmental
stability, and strong electron affinity, making them well-suited for
low-power gas-sensing applications.⁸,⁹ Bismuth nanoparticles, with
their high surface area, good stability, and tunable properties, allow
for low-concentration gas sensing (ppb to ppm). Furthermore, bis-
muth's low cost and low toxicity make it an appealing candidate
for portable detection applications.⁸,⁹ Carbon nanotubes (CNTs)
are another class of materials widely explored for gas sensing due
to their high conductivity, large surface area, and chemical stability.⁵
Various functionalization strategies, including polymer coatings, nano-
particle decoration, and hybrid nanocomposites, have been developed
to improve CNT dispersion and chemical sensitivity.⁷

Bismuth iodide (BiI₃) is a *p*-type semiconductor with a layered crystal structure, as seen in Fig. 1, offering strong charge transfer properties and enhanced chemical stability. When integrated into double-walled carbon nanotubes (DWNTs), BiI₃ forms a heterostructure, enabling enhanced selectivity and response through electron transfer mechanisms.³ Previous studies have shown that bilayer sensors, such as CeO₂ (cerium dioxide), whose top layers act as filters by oxidizing non-aromatic interferents, can effectively detect aromatic VOCs.¹ Against this background, we present BiI₃-filled DWNTs (BiI₃@DWNT) as a room-temperature sensor for aromatic VOCs, specifically targeting benzene. Our BiI₃@DWNT nanohybrid sensor yields high benzene response, with much lower responses to tested alkanes. We interpret these results as enhanced benzene sensitivity (or partial selectivity).

Benzene is classified as a genotoxic carciogen with permissible
8 h exposure limit (PEL) of 1 ppm and a 15 min short-term expo-
sure limit (STEL) of 5 ppm² as outlined earlier. Many gas sensors
struggle to meet these low thresholds with sufficient selectivity and
reliability. Our BiI₃@DWNT sensor addresses this challenge through a
unique architecture that combines bismuth iodide with DWNTs in an
encapsulated, one-dimensional configuration. Unlike conventional

Bi-based or CNT sensors that rely on external surface coatings or
require high operating temperatures, this system leverages internal
charge transfer between encapsulated BiI₃ and the CNT host. Prior
work has shown that inserting molecular guests or metal species into
CNTs can modulate the band structure and the Fermi level without
introducing defects.<sup>10,11</sup> BiI₃ encapsulation forms an “inside-out” het-
erojunction that dopes the CNT internally while preserving structural
integrity, offering a high conductivity, catalytically active interface for
gas detection. These features, combined with ambient-temperature
operation, allow the BiI₃@DWNT sensor to detect benzene at or
below regulatory thresholds while minimizing power consumption
and enhancing material longevity. The novel BiI₃@DWNT nanohy-
brid sensor leverages the high conductivity of CNTs and benzene
affinity to BiI₃ to achieve low-ppm benzene detection at ambient con-
ditions. BiI₃@DWNTs were prepared by capillary filling.

II. METHODOLOGY

A. Material synthesis

The DWNTs were prepared as outlined in Ref. 12. Pristine
DWNTs were mixed with bismuth iodide (BiI₃: Sigma Aldrich, Cas
No: 7787-64-6, 25 g, >99%), ground together with a mass ratio of
1:4, and then transferred into a quartz ampoule. The ampoule was
subsequently evacuated at 0.1 mbar and sealed under vacuum. It
was then heated inside a tubular furnace for a 24 h dwell tempera-
ture of 440 °C (~30 °C above the melting point of BiI₃). This facili-
tates the filling of the DWNTs via capillary action under vacuum
conditions before slowly cooling. After cooling, the resulting
BiI3@DWNTs were collected and washed using 0.1 M hydrochloric
acid to remove the excess, non-encapsulated material.

B. Sample characterization

After synthesis, the structural properties of the bismuth iodide
functionalized DWNT samples (BiI3@DWNT) were studied using
a Bruker D8 Advance x-ray diffractometer with Cu Kα radiation of
wavelength λ = 1.5418 Å. Raman spectroscopy studies were done
using a Horiba LabRAM HR Evolution Raman Spectrometer with
a 532 nm in the range 100–2000 cm⁻¹. High-Resolution Transmission
Electron Microscopy (HRTEM) and the accompanying energy disper-
sion x-ray spectroscopy (EDX) data were acquired from a JEOL
JEM-ARM 200F Cold FEG Probe Cs connected, operated at 80 kV, to
resolve the chemical composition of the composite material.

C. Gas-sensing setup

The sensor materials were dispersed in ethanol by ultrasound
sonication, in a Branson 1800, 1.91 l sonicator operating at 40 kHz,
for 10 min to form a homogenous suspension. The resulting dis-
persion was drop-cast onto prefabricated gold electrodes, ensuring
the material was evenly deposited across the contacts to create a
resistive gas sensor. The gas or VOC sensing measurements were
conducted at room temperature and the flow rates of the carrier
gas (nitrogen) and target gas (stimulant) were controlled using
Alicat Mass Flow controllers, managed via LabVIEW software.
Nitrogen was used as it is an inert and stable gas at room tempera-
ture and, thus, can be a good alternative to low-cost gas carrier to
helium, when it bubbles through most VOCs. The gas-sensing

<figure><img src="image_11.png" /><figcaption>FIG. 1. Schematic illustration of layered bismuth iodide (BiI$_{3}$) showing a layered 1D structure, which might be a possible structure inside the DWNTs.</figcaption></figure>
response was determined by monitoring the DC resistance with a Keithley 2450 Source Meter, with data acquisition and recording facilitated by the LabVIEW program. The stimulants butyraldehyde, n-hexane, hexadecane, and benzene were used in the state they were received from the supplier. The different concentrations of the gas vapors inside the sensing chamber were obtained by controlling the flow rates of the two mass flow controllers, using Eq. (1). See Fig. 2 (FC1 and FC2),

$$ppm = \frac{Q_{\text{target}}}{Q_{\text{target}} + Q_{\text{carrier}}} \times \eta \times \frac{10(A - \frac{B}{C} + T)}{P_{\text{total}}} \times 10^6, \quad (1)$$

where $Q_{\text{target}}$ and $Q_{\text{carrier}}$ are the carrier and target flow rates in SLPM (Standard Liters Per Minute), $\eta$ is the efficiency coefficient factor that accounts for the incomplete mass transfer of vapor from the target liquid into the gas, A, B, and C are the Antoine coefficients of the targeted gas, $P_{\text{total}}$ is the default total vapor pressure, T is the temperature in degrees Celsius, and $10^6$ converts the resulting mole fraction into ppm.

The gas-sensing experiment began with a 5 min chamber purging period to ensure an inert gas-sensing atmosphere (nitrogen gas). After that, the analyte gas was introduced into the gas detection chamber for 2 min. A recovery period of 5 min was allowed to get a total experiment runtime of 12 min.

### III. RESULTS AND ANALYSIS

#### A. Material characterization

Figure 3(a) provides insight into the structural modifications upon BiI$_3$ encapsulation. The DWNTs exhibit a very broad (002) reflection at $2\theta = 28.52^{\circ}$, which has been observed by other researchers at $26.4^{\circ}$ and has been cited as characteristic of graphitic carbon.13–15 The (100) peak at $2\theta = 43.40^{\circ}$ is characteristic of the honeycomb structure of the DWNTs and aligns with graphite reflections observed in regular stacking.14,15 The pristine bismuth triiodide (BiI$_3$) powder diffraction spectra [blue in Fig. 3(a)] confirms an R-3 rhombohedral crystal structure with a dominant (113) reflection at $2\theta = 26.99^{\circ}$, consistent with (JCPDS PDF No. 48-1795) data.16 In contrast, the XRD analysis of the BiI$_3$@DWNT hybrid (red spectra) exhibits a noticeably sharp (002) peak, attributed

primarily to encapsulated BiI$_3$ experiencing confinement effects rather than residual material on the outer walls. Notably, this peak is absent in the bulk BiI$_3$ XRD pattern, suggesting that its emergence in the hybrid material results from structural modification due to encapsulation. However, this still requires further investigation. The presence of a strong low-angle peak (11.98°) further confirms that BiI$_3$ is abundant within the nanotubes, likely undergoing reorganization upon confinement. The BiI$_3$ characteristic peaks dominate the spectra for the hybrid material, with little noticeable contribution from DWNTs, primarily because the halide material far outweighs the CNTs in mass. The XRD analysis suggests that the structural modification of encapsulated BiI$_3$, influenced by nanoscale confinement within the DWNTs, may play a significant role in the sensing behavior of the hybrid material.

Raman spectroscopy illustrates that in pristine DWNTs [Fig. 3(b)], the D-band and G-band are observed at 1335.13 and 1581.54 cm$^{-1}$, respectively, with an $I_D/I_G$ ratio of 0.27, indicative of high crystallinity.17 Upon BiI$_3$ encapsulation, the G-band and D-band shift marginally to 1580.38 and 1335.53 cm$^{-1}$, with an $I_D/I_G$ ratio of 0.25, confirming that the encapsulation does not induce significant defects in the DWNT structure. These observations indicate that BiI$_3$ is confined within the nanotube structure without compromising the integrity of the carbon lattice, in agreement with previous studies,18 such as those of various halide- or metal-filled CNTs that typically report only minor shifts in D/G peak positions, without the emergence of a strong D peak. In one report comparing pristine, PbCl$_2$-filled, and RbI-filled single-walled carbon nanotubes (SWCNTs), only small shifts and intensities were seen in the D and 2D bands,19 implying no severe damage. This supports that BiI$_3$ encapsulation affects electronic doping but induces negligible structural disorder in agreement with the prior literature.11,19

The dark field and bright field HRTEM images of the BiI$_3$ composite material [Figs. 4(b) and 4(c)] show that the nanocrystals are confined in the inner channel of the DWNTs and that BiI$_3$ is well crystallized within the cavity of the DWNTs, elongated along their axis. The type of crystal structure observed for encapsulated BiI$_3$ [Fig. 4(d)] is broadly similar to that previously reported for NiI$_2$ and PbI$_2$, exhibiting a layered CdCl$_2$ structure in the R-3mH symmetry.20 Figure 4(f) displays a distinct rhombohedral ordering that is consistent with the high structural stability of encapsulated BiI$_3$. This well-defined structure, combined with the confirmed presence of Bi, I, and C in the energy dispersive x-ray spectroscopy (EDS) spectra [Fig. 4(e)], strongly supports that the material confined within the DWNTs is indeed BiI$_3$.

#### B. Gas-sensing results

Gas-sensing performance is an essential characteristic in evaluating the practical applicability of any sensor material. The transient response of the sensor is crucial for practical deployment, as it describes how the sensor's resistance changes over time in response to the presence and removal of an analyte gas. The response time ($\tau_{res}$) is defined as the time required for the sensor to reach 90% of the total resistance change after exposure to the gas, while the recovery time ($\tau_{rec}$) represents the duration necessary for the sensor to return to its baseline resistance after the gas is removed.

<figure><img src="image_12.png" /><figcaption>FIG. 2. Schematic illustration of the gas-sensing system that uses LABVIEW to control the Keithley software and record data.</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>FIG. 3. XRD spectra of (a) pristine double-walled carbon nanotubes (DWNTs), bismuth iodide functionalized nanotubes (BiI$_{3}$@DWNT), and bismuth iodide (BiI$_{3}$), showing the structural evolution upon nanocomposite formation. (b)–(d) Raman spectra of DWNTs, BiI$_{3}$, and BiI$_{3}$@DWNT, respectively, highlighting vibration and electronic interactions in the composite material.</figcaption></figure>

We used pure nitrogen ($N_2$) as the carrier gas in all sensing experiments. This inert environment prevents interference from atmospheric oxygen, which has been reported to significantly influence sensor response and baseline drift in chemiresistive systems.<sup>21,22</sup> In these systems, the presence of oxygen can contribute additional surface reactions, particularly for metal oxide-based materials, by introducing adsorbed $O^{2-}$ species that participate in charge transfer. In contrast, under a nitrogen atmosphere, the sensor surface is essentially oxygen-deficient, with minimal chemisorbed oxygen. This has critical implications for baseline stability and selectivity. In air, oxide-based sensors often rely on lattice oxygen or adsorbed oxygen species to interact with the analyte, whereas in nitrogen, the baseline conductivity reflects the sensor's

intrinsic state, allowing analyte-induced changes (e.g., from benzene) to be isolated more precisely. Prior studies have shown that switching from air to $N_2$ reduces baseline variability and suppresses secondary redox interactions.<sup>23</sup> Therefore, we used $N_2$ both as a carrier and dilution gas to create a consistent, oxygen-free background, ensuring that observed conductance changes result primarily from target gas adsorption on the BiI<sub>3</sub>@DWNT surface. The controlled $N_2$ flow also facilitates uniform benzene delivery to the active sensing region, improving response reproducibility.

Two-probe electrical measurements were conducted for analyte gas at various concentrations. The transient response was calculated using the following equation:
<figure><img src="image_14.png" /><figcaption>FIG. 4. High-resolution TEM images and EDS spectra of BiI$_{3}$@DWNT nanohybrids. (a)–(d) TEM images showing encapsulated BiI$_{3}$ structures within DWNTs. (e) EDS confirming the presence of Bi, I, and C. (f) Structural model of encapsulated BiI$_{3}$ displaying rhombohedral ordering.</figcaption></figure>

$$S(\%) = \frac{R_g - R_a}{R_a} \times 100, \quad (2)$$

where $R_a$ is the resistance in nitrogen environment and $R_g$ is the resistance in the presence of the target (analyte gas). The response parameter $S (\%)$ quantifies the sensor's sensitivity to different VOCs, enabling a comparative evaluation of BiI$_{3}$, DWNTs, and BiI$_{3}$@DWNT under similar conditions.

The gas-sensing responses of BiI$_{3}$, DWNTs, and BiI$_{3}$@DWNT were evaluated under similar analyte exposure conditions, as illustrated in Fig. 5. The pristine BiI$_{3}$ sensor exhibited high sensitivity across multiple VOCs [Figs. 5(a), 5(d), and 5(g)]. However, despite its strong gas interactions, BiI$_{3}$ suffered from substantial baseline noise, poor signal stability, and sluggish recovery times, making it unsuitable for real-time and continuous monitoring applications. The prolonged response-recovery cycles observed in pristine BiI$_{3}$ suggest strong gas adsorption and inefficient desorption dynamics, leading to hysteresis effects that compromise its repeatability and reliability.

In contrast, pristine DWNTs alone displayed minimal response across all tested VOCs, indicating low intrinsic gas sensitivity. While minor interactions were observed for hexadecane and butyraldehyde, the overall response values remained significantly lower than those of BiI$_{3}$ or BiI$_{3}$@DWNT. This behavior is expected, as pristine carbon nanotubes (CNTs) lack chemically active sites for effective gas adsorption, reinforcing their poor standalone sensing capabilities. However, when combined with BiI$_{3}$ in the BiI$_{3}$@DWNT nanohybrid, a dramatic enhancement in response intensity, selectivity, and stability was observed.

The BiI$_{3}$@DWNT nanohybrid sensor exhibited substantially higher responses to benzene: 1.81% (1 ppm), 2.32% (5 ppm), and 3.23% (10 ppm) compared to BiI$_{3}$ and the DWNTs [Figs. 5(j)–5(l)]. This improvement suggests that BiI$_{3}$ confinement within DWNTs enhances sensor response processes and optimizes the gas adsorption-desorption equilibrium, leading to stronger yet reversible gas interactions. Interestingly, BiI$_{3}$@DWNT demonstrated poor detection of alkanes (n-hexane and hexadecane), (<0.1%) to 1–10 ppm, and only ~0.73% to 10 ppm butyraldehyde. The superior benzene response and suppressed alkane response reinforce the sensor's preferential interaction with aromatic VOCs under our test conditions. This partial selectivity is consistent with typical chemiresistors which often show different degrees of response to similar gases. For instance, recent studies demonstrated that tin-oxide sensors with catalytic overlayers exhibited partial selectivity patterns.²⁴ This preferential interaction of BiI$_{3}$@DWNT toward benzene is crucial for applications in industrial emissions tracking, workplace safety, and air quality monitoring, where selective detection of hazardous compounds, such as benzene, is imperative.

The bar charts [Figs. 5(j)–5(l)] provide a summary of the BiI$_{3}$@DWNT sensor response across different VOCs, reaffirming its consistent superiority over pristine BiI$_{3}$ and DWNTs. The response-recovery analysis (Table I) further validates that BiI$_{3}$@DWNT maintains a stable and reversible gas interaction mechanism, preventing excessive gas retention and ensuring rapid sensor reset—a critical feature for real-time monitoring applications.

Response and recovery dynamics are critical for practical sensor applications. The response and recovery times of the three materials (shown in Table I) were evaluated, with BiI$_{3}$@DWNT consistently outperforming both BiI$_{3}$ and DWNTs in terms of
<figure><img src="image_15.png" /><figcaption>FIG. 5. Gas-sensing performance of Bil$_{3}$, DWNTs, and Bil$_{3}$@DWNT toward selected volatile organic compounds (VOCs) at varying concentrations (1, 5, and 10 ppm): (a)–(c) dynamic response curves of Bil$_{3}$, DWNTs, and Bil$_{3}$@DWNT at 1 ppm, illustrating initial sensitivity trends, (d)–(f) dynamic response curves of Bil$_{3}$, DWNTs, and Bil$_{3}$@DWNT at 5 ppm, demonstrating concentration-dependent variations in response and recovery behavior, (g)–(i) dynamic response curves of Bil$_{3}$, DWNTs, and Bil$_{3}$@DWNT at 10 ppm, highlighting Bil$_{3}$'s high sensitivity but poor signal stability and recovery times, DWNTs' minimal gas interaction confirming its weak intrinsic sensing properties, and Bil$_{3}$@DWNT's significantly enhanced selectivity and stability, particularly toward benzene and butyraldehyde, and (j)–(l) bar graphs summarizing the comparative response values of Bil$_{3}$, DWNTs, and Bil$_{3}$@DWNT across all tested VOCs at different concentrations, reinforcing Bil$_{3}$@DWNT's superior sensing performance.</figcaption></figure>
<table><caption>**TABLE I.** Response and recovery times of BiI<sub>3</sub>@DWNT, DWNTs, and BiI<sub>3</sub> for various VOCs at 1 ppm.</caption><thead><tr><th>Target gas</th><th>BiI<sub>3</sub>@DWNT (s)</th><th>DWNTs (s)</th><th>BiI<sub>3</sub> (s)</th></tr></thead><tbody><tr><td>Benzene</td><td>35.2/73.3</td><td>59.9/77.4</td><td>22.2/72.1</td></tr><tr><td>Butyraldehyde</td><td>33.1/47.3</td><td>77.8/75.4</td><td>137.7/164.2</td></tr><tr><td>Hexadecane</td><td>17.2/76.4</td><td>71.3/74.2</td><td>109.6/173.3</td></tr><tr><td>n-hexane</td><td>56.3/74.9</td><td>54.0/197.2</td><td>61.0/36.4</td></tr></tbody></table>

speed and reliability. BiI<sub>3</sub> alone, despite its high sensitivity, suffered from prolonged recovery times, exceeding 160 s for butyraldehyde and 173 s for hexadecane, indicative of strong gas adsorption but weak desorption mechanisms. Such behavior is unfavorable for sensors requiring rapid cycling as it leads to baseline drift and response lag over extended operation periods. DWNTs exhibited even slower response and recovery times, with some gases exceeding 190 s for complete signal reset, further confirming their limited applicability as standalone gas sensors.

The observed enhancement in gas-sensing characteristics of BiI<sub>3</sub>@DWNT can be attributed to charge transfer effects between BiI<sub>3</sub> and DWNTs. The metal halide increases the density of states for the DWNTs and enhances the capacity for resistance modulation due to stimulant gas. Pristine BiI<sub>3</sub> is a p-type semiconductor, where gas adsorption modulates its charge carrier density, altering its electrical resistance. Filling CNTs with halides is known to induce p-type doping on the CNTs,<sup>19</sup> this implies that the composite material BiI<sub>3</sub>@DWNT is also p-type. In BiI<sub>3</sub>@DWNT, the encapsulation of BiI<sub>3</sub> within the confined interior of DWNTs may induce subtle structural modifications, leading to localized distortions in the Bi<sup>3+</sup>-I<sup>-</sup> coordination environment. Such confinement-induced changes can alter the spacing and alignment of iodine anions, thereby influencing the electronic structure and charge mobility within the composite. Similar phenomena have been observed in studies that imaged lattice defects and distortions in alkali-metal iodides encapsulated within double-walled carbon nanotubes<sup>25</sup> and in investigations of single-walled BiI<sub>3</sub> nanotubes encapsulated within carbon nanotubes.<sup>26</sup>

This effect could alter the spacing and alignment of iodine anions, thereby influencing the electronic structure and charge mobility within the nanohybrid. The presence of DWNTs as a conductive scaffold ensures that the outer layer properties are preserved. This explains the faster response times and improved recovery rates observed in BiI<sub>3</sub>@DWNT, as it enables more efficient charge transport upon gas exposure and reduces the trapping of adsorbed species, thereby facilitating quicker desorption. The

enhanced interfacial charge interactions (BiI<sub>3</sub>/DWNTs) lead to stable resistance changes upon gas adsorption. This is primarily due to the formation of a p-n heterojunction at their interface, facilitating efficient charge transfer and Fermi level alignment. Additionally, the nanoconfinement of BiI<sub>3</sub> within DWNTs modifies its electronic density of states, resulting in controlled adsorption/desorption dynamics and stabilized resistance changes.<sup>27,28</sup>

These electronic changes can be further understood though recent theoretical and experimental studies. The encapsulation of BiI<sub>3</sub> inside DWNTs has a strong influence on CNT electronic behavior. One-dimensional guest species inside nanotubes can induce charge transfer or doping even if the tube wall itself remains intact. As noted above, earlier studies showed that filling CNTs with donor or acceptor molecules can shift the Fermi level and change conductivity without creating defects.<sup>10</sup> In our case, BiI<sub>3</sub> has a polar lattice that likely donates electrons (or draws electrons) from the CNT, effectively doping the DWNT. This internal doping changes the work function and carrier density of the CNT channel, enhancing its baseline conductivity and sensitivity to adsorbates. Such effects have been documented, e.g., Lee *et al.* showed that encapsulating fullerenes inside SWCNTs modulates the bandgap of the tubes.<sup>10</sup> By analogy, BiI<sub>3</sub> inside the nanotube can modulate the electronic structure of DWNTs. These modulation effects explain why we see different electrical behaviors in BiI<sub>3</sub>@DWNT vs pristine DWNTs, beyond what surface adsorption alone would produce. Importantly, this interior effect does not require covalent modification: the Raman and EDS data suggest the DWNT lattice remains undamaged (see Figs. 3 and 4), consistent with the idea that the BiI<sub>3</sub> acts as a guest dopant. Thus, the novelty of our sensor lies in using encapsulated BiI<sub>3</sub> to tune the DWNT's electronics *in situ*, which is distinct from ordinary surface doping or decoration used in other sensors.

To contextualize these results, the superior sensing characteristics of BiI<sub>3</sub>@DWNT were benchmarked against state-of-the-art benzene sensors (Table II).

Unlike WO<sub>3</sub> and Rh-TiO<sub>2</sub>-based sensors, which require elevated operating temperatures (300-425 °C) to achieve optimal detection, limiting their practical use, BiI<sub>3</sub>@DWNT operates efficiently at room temperature, making it a low-power alternative for portable and real-time applications. While Au NPs-multi-walled carbon nanotube (MWCNT)-based benzene sensors offer an ultra-low limit-of-detection (LOD) of 600 ppt, their longer recovery times (90 s) make them less favorable for rapid cycling compared to BiI<sub>3</sub>@DWNT. The sensor's room-temperature operation, fast response (35 s), and recovery (73.3 s) make it a promising alternative for environmental benzene monitoring. These results position BiI<sub>3</sub>@DWNT as a highly promising gas-sensing material, offering a

<table><caption>**TABLE II.** Comparison of BiI<sub>3</sub>@DWNT with existing benzene sensors. Boldface denotes the data referred by this article.</caption><thead><tr><th>Sensor type</th><th>Temp. (°C)</th><th>LOD (ppm)</th><th>Resp. (s)</th><th>Recov. (s)</th><th>Reference</th></tr></thead><tbody><tr><td>BiI<sub>3</sub>@DWNT</td><td><strong>RT</strong></td><td><strong>1</strong></td><td><strong>35.2</strong></td><td><strong>73.3</strong></td><td>...</td></tr><tr><td>Au NPs-MWCNT sensor</td><td>RT</td><td>0.0006</td><td>60</td><td>90</td><td>29</td></tr><tr><td>MEMS WO<sub>3</sub> sensor</td><td>300</td><td>0.2</td><td>35</td><td>75</td><td>30</td></tr><tr><td>Rh-TiO<sub>2</sub>/SnO<sub>2</sub></td><td>325-425</td><td>ppm range</td><td>40</td><td>80</td><td>24</td></tr></tbody></table>
unique balance of selectivity, sensitivity, and operational stability. Its ability to rapidly and selectively detect hazardous VOCs while operating at room temperature makes it a viable candidate for next-generation environmental sensors.

Using calibration, we computed a sensor sensitivity of ~0.22% per ppm (slope of response vs conc, Fig. 6 for benzene). Applying the 3σ method, the LOD is given by $LOD = 3σ/S$.³¹ In our case, the noise of the baseline (pure N₂) was about 0.14%, giving $LOD ≈ (3 × 0.14%)/(0.22%/ppm) ≈ 0.20$ ppm. This LOD corresponds to the concentration where SNR = 3. Our calculated LOD (~200 ppb) matches the observed limit of reliable detection (1 ppm). We note that signal-to-noise ratio, $SNR = signal/σ ≈ 15$. These derived LOD and SNR are standard for analytic sensors. The calibration shows that $BiI₃@DWNT$ is more sensitive to benzene than butyraldehyde as evidenced by a ~6.81× larger slope and by much higher percent responses at low ppm. Consequently, the benzene LOD ≈ 200 ppb is significantly lower than the butyraldehyde LOD ≈ 1.36 ppm, indicating that benzene can be detected at much smaller concentrations. In practical terms, these results imply the sensor will reliably detect benzene at sub-10 ppm levels, but butyraldehyde would require higher concentrations to exceed the noise floor. This quantitative finding supports the preference of $BiI₃@DWNT$ toward benzene and poor sensitivity to interfering VOCs.

Beyond individual compounds sensing, we also tested sensor response to the effects of VOC co-exposure and humidity. The gas-sensing response was evaluated in a water-vapor environment by gradually increasing the water concentration [using Eq. (1)] from 1 to 100 ppm. The response was subsequently measured for gas mixtures both without and with benzene to determine whether the sensor exhibits preferential sensitivity. Equal volumes of analytes were introduced via the bubbler system and cycled through the

sensing protocol (see Fig. 7 for the dynamic response curves and bar graph summaries).

Figures 7(a) and 7(b) clearly show that increasing humidity adversely affects sensor sensitivity, while Fig. 7(c) demonstrates the inherent preferability toward benzene, with a suppressed but visible response at 1 ppm compared to negligible responses for other interfering compounds. Comparative to Fig. 5(i), though the sensor reliably detects benzene, incremental sensitivity is markedly suppressed under co-exposure conditions, indicative of interference from other species significantly affecting response. These observations underscore that while $BiI₃@DWNT$ preferentially senses benzene, any strongly adsorbing interferents could impact the signal. This is a common situation in gas sensing²⁴ and suggests that sensor arrays or pre-filtering may be needed for complex environments.

## 1. Sensing mechanism

The gas-sensing performance of $BiI₃@DWNT$ is governed by charge transfer interactions between $BiI₃$, the double-walled carbon nanotube (DWNT) matrix, and adsorbed gas molecules, leading to distinct resistance modulations upon exposure to volatile organic compounds (VOCs). The $BiI₃@DWNT$ is a p-type semiconductor. When benzene adsorbs, it donates electrons to the $BiI₃@DWNT$ material upon exposure from the π-orbital electrons. Since the hybrid material is a p-type semiconductor, the Fermi level is closer to the valence band, which facilitates hole conduction (Fig. 8). This electron donation increases the density of states near the conduction band, causing the Fermi level to shift upward toward the conduction band. As a result, the concentration of holes decreases, leading to a reduction in p-type behavior and an increase in electrical resistance. This rise in resistance is observed as a positive sensor response (Fig. 5), indicating the presence of benzene.

The $BiI₃$ surfaces and any defects on the DWNT walls provide active sites for benzene adsorption. Defects can enhance binding strengths and facilitate charge exchange.¹⁹,³² Since the nanohybrid is highly porous³³ and has a large surface area, there are more adsorption pathways, and this enhancing sensitivity toward benzene.³⁴

Furthermore, the sensor response and recovery are governed by more than just charge transport. In nanostructured sensors, surface chemistry and morphology play key roles. The $BiI₃@DWNT$ network is inherently porous and possesses a very high surface-to-volume ratio, which facilitates rapid gas diffusion. Porous materials are known to exhibit excellent response and recovery times and high sensitivity due to their large surface area and abundance of active sites.³⁵ Additionally, carbon nanotubes naturally contain intrinsic defect sites—such as vacancies and non-hexagonal rings—that act as low-energy adsorption centers.³⁶ Adsorption at these sites leads to stronger analyte binding and enhanced charge transfer, contributing significantly to sensor output. Prior studies by Robinson *et al.* and Perkins *et al.* demonstrated that introducing a small fraction of functional groups or defects on CNTs can boost sensor response by orders of magnitude.³⁷ In the $BiI₃@DWNT$ system, the encapsulated $BiI₃$ likely contributes further catalytic activity and adsorption affinity, lowering the activation energy required for charge exchange with aromatic molecules.

<figure><img src="image_16.png" /><figcaption>FIG. 6. Calibration plots for (a) benzene (data points purple) and linear fit red. (b) Butyraldehyde (data points red) and linear fit gray. Each fit's slope S gives the sensitivity to compute LOD and SNR.</figcaption></figure>
<figure><img src="image_17.png" /><figcaption>FIG. 7. Effects of humidity and VOC co-exposure on sensor performance. (a) Sensor response in a water-vapor environment. (b) Response to VOC mixtures including water, butyraldehyde, hexane, and *n*-hexane. (c) Comparison of co-exposure effects, indicating selective response to benzene. (d) Bar chart summarizing the impact of humidity and co-exposure on sensor response.</figcaption></figure>

<figure><img src="image_18.png" /><figcaption>FIG. 8. A schematic illustration of the interaction of benzene with $BiI_3$@DWNT.</figcaption></figure>

At room temperature, molecular desorption is slower than at elevated temperatures, potentially increasing recovery time. However, this is balanced by the chemical specificity of $BiI_3$ and the open porous network of the DWNTs, which allow for both strong interaction with benzene and efficient molecular transport. Such interactions highlight the sensor's sensitivity to aromatic compounds, utilizing electronic changes at the molecular level for detection.

## IV. CONCLUSION

This study has shown that the enhanced gas-sensing performance of $BiI_3$ encapsulated double-walled carbon nanotubes ($BiI_3$@DWNTs) for the selective detection of aromatic and volatile organic compounds (VOCs) at room temperature. Compared to pristine $BiI_3$ and DWNTs, $BiI_3$@DWNT exhibits superior sensitivity, stability, and selectivity, particularly toward benzene (1.81%),
(2.32%), and (3.23%) at 1, 5, and 10 ppm, while showing negligible response to alkanes such as hexadecane and *n*-hexane, and only a minimum response to butyraldehyde (0.73%) at 10 ppm. This highlights BiI₃@DWNT's preferential selectivity toward benzene at low concentrations, 1 ppm (the legal airborne permissible exposure limit on an 8 h working shift) and 5 ppm (the 15 min short-term exposure limit), as emphasized by the Occupational Safety and Health Organization.² The encapsulation of BiI₃ within DWNTs improves gas adsorption efficiency, enhances charge transfer interactions, and facilitates faster response (35.2 s) and recovery (73.3 s) times compared to pristine BiI₃. The improved performance of BiI₃@DWNT is attributed to synergistic interactions between BiI₃ and DWNTs, where nanoconfinement enhances surface interactions, carrier mobility, and gas adsorption-desorption dynamics, making it a low-power, energy-efficient alternative. These findings establish BiI₃@DWNT as a promising candidate for next-generation VOC sensors with applications in industrial emissions monitoring, air quality assessment, and environmental pollution control.

## ACKNOWLEDGMENTS

This article has been produced with the financial assistance of the European Union (Grant No. DCI-PANAF/2020/420-028), through the African Research Initiative for Scientific Excellence (ARISE), pilot programme. ARISE is implemented by the African Academy of Sciences with support from the European Commission and the African Union Commission. The contents of this document are the sole responsibility of the author(s) and can under no circumstances be regarded as reflecting the position of the European Union, the African Academy of Sciences, and the African Union Commission.

## AUTHOR DECLARATIONS

### Conflict of Interest

The authors have no conflicts to disclose.

### Author Contributions

**Ikanyeng A. M. Serero:** Formal analysis (equal); Investigation (lead); Methodology (lead); Validation (equal). **Emmanuel Flahaut:** Formal analysis (equal); Investigation (equal); Methodology (equal); Validation (equal). **George Chimowa:** Conceptualization (lead); Formal analysis (equal); Funding acquisition (lead); Investigation (equal); Methodology (equal); Supervision (lead); Validation (equal).

## DATA AVAILABILITY

The data that support the findings of this study are available from the corresponding author upon reasonable request.

## REFERENCES

¹S.-Y. Jeong, Y. K. Moon, J. Wang, and J.-H. Lee, "Exclusive detection of volatile aromatic hydrocarbons using bilayer oxide chemiresistors with catalytic over-layers," *Nat. Commun.* **14**, 233 (2023).

²O. Safety and H. A. OSHA, "Benzene standard—1910.1028 app a" (2024) (last accessed February 17, 2025).

³M. M. Kiaee, T. Maeder, and J. Brugger, "Near-room-temperature detection of aromatic compounds with inkjet-printed plasticized polymer composites," *ACS Sens.* **9**, 1382–1390 (2024).

⁴H. AlQahantani, M. Sugden, D. Puzzovio, L. Hague, N. Mullin, T. Richardson, and M. Grell, "Highly sensitive alkane odour sensors based on functionalised gold nanoparticles," *Sens. Actuators B Chem.* **160**, 399–404 (2011).

⁵M. Kaloumenou, E. Skotadis, N. Lagopati, E. Efstathopoulos, and D. Tsoukalas, "Breath analysis: A promising tool for disease diagnosis—The role of sensors," *Sensors* **22**, 1238 (2022).

⁶H. Xu, J. Xu, H. Li, W. Zhang, Y. Zhang, and Z. Zhai, "Highly sensitive ethanol and acetone gas sensors with reduced working temperature based on Sr-doped BiFeO₃ nanomaterial," *J. Mater. Res. Technol.* **17**, 1955–1963 (2022).

⁷Z. Yuan, C. Yang, and F. Meng, "Strategies for improving the sensing performance of semiconductor gas sensors for high-performance formaldehyde detection: A review," *Chemosensors* **9**, 179 (2021).

⁸P. Sivasubramanian, J.-H. Chang, S. Nagendran, C.-D. Dong, M. Shkir, and M. Kumar, "A review on bismuth-based nanocomposites for energy and environmental applications," *Chemosphere* **307**, 135652 (2022).

⁹Y. E. Jung, J. H. Yang, and M.-S. Yim, "Investigation of bismuth-based metal-organic frameworks for effective capture and immobilization of radioiodine gas," *J. Hazard. Mater.* **467**, 133777 (2024).

¹⁰K. Y. Lee, U. Choi, and A. Zettl, "Recent progress in realizing novel one-dimensional polymorphs via nanotube encapsulation," *Nano Convergence* **11**, 1–21 (2024).

¹¹J.-L. Xu, R.-X. Dai, Y. Xin, Y.-L. Sun, X. Li, Y.-X. Yu, L. Xiang, D. Xie, S.-D. Wang, and T.-L. Ren, "Efficient and reversible electron doping of semiconductor-enriched single-walled carbon nanotubes by using decamethylcolbaltocene," *Sci. Rep.* **7**, 6751 (2017).

¹²E. Flahaut, R. Baca, A. Peigney, and C. Laurent, "Gram-scale CCVD synthesis of double-walled carbon nanotubes," *Chem. Commun.* **12**, 1442–1443 (2003).

¹³J. Cambedouzou, M. Chorro, R. Almairac, L. Noé, E. Flahaut, S. Rols, M. Monthioux, and P. Launois, "X-ray diffraction as a tool for the determination of the structure of double-walled carbon nanotube batches," *Phys. Rev. B* **79**, 195423 (2009).

¹⁴R. Das, S. Bee Abd Hamid, M. Eaqub Ali, S. Ramakrishna, and W. Yongzhi, "Carbon nanotubes characterization by x-ray powder diffraction—A review," *Curr. Nanosci.* **11**, 23–35 (2015).

¹⁵D. N. Futaba, T. Yamada, K. Kobashi, M. Yumura, and K. Hata, "Macroscopic wall number analysis of single-walled, double-walled, and few-walled carbon nanotubes by x-ray diffraction," *J. Am. Chem. Soc.* **133**, 5716–5719 (2011).

¹⁶N. F. Coutinho, S. Cucatti, R. B. Merlo, J. M. C. Silva Filho, N. F. B. Villegas, F. Alvarez, A. F. Nogueira, and F. C. Marques, "The thermomechanical properties of thermally evaporated bismuth triiodide thin films," *Sci. Rep.* **9**, 11785 (2019).

¹⁷M. S. Dresselhaus, G. Dresselhaus, R. Saito, and A. Jorio, "Raman spectroscopy of carbon nanotubes," *Phys. Rep.* **409**, 47–99 (2005).

¹⁸A. Jorio, E. H. M. Ferreira, M. V. O. Moutinho, F. Stavale, C. A. Achete, and R. B. Capaz, "Measuring disorder in graphene with the G and D bands," *Phys. Status Solidi B* **247**, 2980–2982 (2010).

¹⁹M. V. Kharlamova and C. Kramberger, "Metal and metal halogenide-filled single-walled carbon nanotubes: Kinetics, electronic properties, engineering the Fermi level," *Nanomaterials* **13**, 180 (2022).

²⁰C. Nie, A. M. Galibert, B. Soula, L. Datas, J. Sloan, E. Flahaut, and M. Monthioux, "The unexpected complexity of filling double-wall carbon nanotubes with nickel (and iodine) 1-d nanocrystals," *IEEE Trans. Nanotechnol.* **16**, 759–766 (2017).

²¹Y. Wu, M. Yan, C. Tian, Y. Liu, and Z. Hua, "NO₂ sensing properties of Cr₂WO₆ gas sensor in air and N₂ atmospheres," *Front. Chem.* **7**, 907 (2020).

²²D. Sturk, L. Rosell, P. Blomqvist, and A. Ahlberg Tidblad, "Analysis of Li-ion battery gases vented in an inert atmosphere thermal test chamber," *Batteries* **5**, 61 (2019).

²³S. A. Ogundipe, C. L. Ndlangamandla, M. M. Diale, M. Jozela, H. C. Swart, D. E. Motaung, and S. S. Nkosi, "Effect of carrier gas on the gas sensing performance of Co₁₋₂NiₓMnₓFe₂₋ᵧCeᵧO₄ double-substitution spinel in flammable gases and volatile organic compounds," *Coatings* **13**, 1771 (2023).
<footnote n="24">²⁴Y. K. Moon, S.-Y. Jeong, Y.-M. Jo, Y. K. Jo, Y. C. Kang, and J.-H. Lee, "Highly selective detection of benzene and discrimination of volatile aromatic compounds using oxide chemiresistors with tunable Rh-TiO₂ catalytic layers," *Adv. Sci.* **8**, 2004078 (2021).</footnote>

<footnote n="25">²⁵P. M. F. J. Costa, S. Friedrichs, J. Sloan, and M. L. H. Green, "Imaging lattice defects and distortions in alkali-metal iodides encapsulated within double-walled carbon nanotubes," *Chem. Mater.* **17**, 3122–3129 (2005).</footnote>

<footnote n="26">²⁶A. E. Ashokkumar, A. N. Enyashin, and F. L. Deepak, "Single walled BiI₃ nanotubes encapsulated within carbon nanotubes," *Sci. Rep.* **8**, 10133 (2018).</footnote>

<footnote n="27">²⁷K. Weng, J. Peng, Z. Shi, A. Arramel, and N. Li, "Highly NH₃ sensitive and selective Ti₃C₂O₂-based gas sensors: A density functional theory-NEGF study," *ACS Omega* **8**, 4261–4269 (2023).</footnote>

<footnote n="28">²⁸B. Liu, F. Wu, H. Gui, M. Zheng, and C. Zhou, "Chirality-controlled synthesis and applications of single-wall carbon nanotubes," *ACS Nano* **11**, 31–53 (2017).</footnote>

<footnote n="29">²⁹P. Clément, S. Korom, C. Struzzi, E. J. Parra, C. Bittencourt, P. Ballester, and E. Llobet, "Deep cavitand self-assembled on Au NPs-MWCNT as highly sensitive benzene sensing interface," *Adv. Funct. Mater.* **25**, 4011–4020 (2015).</footnote>

<footnote n="30">³⁰M.-T. Ke, M.-T. Lee, C.-Y. Lee, and L.-M. Fu, "A MEMS-based benzene gas sensor with a self-heating WO₃ sensing layer," *Sensors* **9**, 2895–2906 (2009).</footnote>

<footnote n="31">³¹G. Sun, C. Wang, J. Jia, H. Zhang, Y. Hu, Y. Liu, and D. Zhang, "High-performance ammonia detection of polymeric BaTiO₃/Ti₃C₂Tₓ MXENE composite-based sensor for gas emission and leakage," *J. Electron. Mater.* **53**, 3426–3437 (2024).</footnote>

<footnote n="32">³²M. Zhu, H. Yin, J. Cao, L. Xu, P. Lu, Y. Liu, L. Ding, C. Fan, H. Liu, Y. Zhang, Y. Jin, L. Peng, C. Jin, and Z. Zhang, "Inner doping of carbon nanotubes with perovskites for ultralow power transistors," *Adv. Mater.* **36**, 2403743 (2024).</footnote>

<footnote n="33">³³Q.-H. Yang and H.-M. Cheng, "Carbon nanotubes: Surface, porosity, and related applications," *Carbon Nanotechnol.* **2006**, 323–359.</footnote>

<footnote n="34">³⁴K. V. N. S. Lim and W. H. Lee, "Enhancing sensitivity in gas detection: Porous structures in organic field-effect transistor-based sensors," *Sensors* **24**, 2862 (2024).</footnote>

<footnote n="35">³⁵A. Sharma, S. B. Eadi, H. Noothalapati, M. Otyepka, H.-D. Lee, and K. Jayaramulu, "Porous materials as effective chemiresistive gas sensors," *Chem. Soc. Rev.* **53**, 2530–2577 (2024).</footnote>

<footnote n="36">³⁶S.-Y. Guo, P.-X. Hou, F. Zhang, C. Liu, and H.-M. Cheng, "Gas sensors based on single-wall carbon nanotubes," *Molecules* **27**, 5381 (2022).</footnote>

<footnote n="37">³⁷J. A. Robinson, E. S. Snow, Ş. C. Bădescu, T. L. Reinecke, and F. K. Perkins, "Role of defects in single-walled carbon nanotube chemical sensors," *Nano Lett.* **6**, 1747–1751 (2006).</footnote>