An ultrasensitive 2,4,6-trinitrophenol nanofluidic sensor inspired by olfactory sensory neurons in sniffer dogs

Abstract

Explosives, as high-energy materials, could generate huge destructive explosions along with a massive release of energy. The regulatory or illegal transportation of explosives threatens the peace and stability worldwide. Among the many high-powered explosives, 2,4,6-trinitrophenol (TNP) is not only frequently used in many terrorist attacks, but also seriously jeopardizes environmental safety and human health. Hence, dependable methods for high-sensitivity, rapid and portable detection are desperately needed. Inspired by olfactory sensory neurons (OSNs) in sniffer dogs, we present a nanofluidic sensor for ultrasensitive TNP detection by in situ growing dense UiO-66-NH₂ layers on the surface of anodic aluminum oxide (AAO) nanochannels. TNP could be specifically captured by UiO-66-NH₂ of the sensor through charge transfer to form Meisenheimer complexes, which cause the ionic current change. The TNP concentrations are quantitatively analyzed by monitoring the changed ionic current. And the detection range is from 10⁻¹⁴ to 10⁻¹⁰ g mL⁻¹ with a limit of detection as low as 6.5 × 10⁻¹⁶ g mL⁻¹, which is far beyond those of the state-of-the-art sensors. This work provides a novel strategy for ultrasensitive detection of TNP as well as other explosives, which opens new and promising routes to various breakthroughs in the fields of homeland security, military applications, security inspections and environmental monitoring.

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Introduction

Explosives, as high-energy materials, are widely used in the fields of weapon systems, explosive forming, space applications and engineering blasting. Also, explosives have become the powerful weapon in terrorist attack that threaten peace and stability worldwide.^1–3 As a more powerful explosive than trinitrotoluene (TNT), 2,4,6-trinitrophenol (TNP) is a frequent ingredient in industrial explosives and is often used in many unexploded bombs and terrorist attacks around the world.^4,5 It not only causes enormous devastation, but also damages the human nervous system and internal organs, as a pollutant in the earth and water.^6,7 Hence, it is of utmost significance to invent a rapid and sensitive detection method for TNP.^8–11 Until now, a series of detection methods have been developed, including using animals, ion mobility spectrometry, surface-enhanced Raman spectroscopy, fluorescence quenching, colorimetry, mass spectrometry and so on. Their expensive cost and sophisticated pretreatment limit their wide application during in-field use.¹² Therefore, fabricating a sensor for TNP detection with portable and sensitive performance is a challenge that needs to be urgently addressed.

Nanofluidic sensors would be an ideal answer to the above challenges as a powerful tool with rapid, low-cost, portable and ultrasensitive advantages.^13–15 Among numerous nanofluidic devices, bioinspired solid-state nanochannels are widely used to achieve smart sensing of diverse targets because of their advantages of functionalization, adjustable size, high mechanical stability, and controllable shape.^16–19 After targets are captured by the recognition element, the physicochemical properties (surface charge, wettability and steric hindrance) of nanochannels would be changed and significantly presented via transmembrane ionic current.¹⁷ Bioinspired nanofluidic sensors have been demonstrated for an extensive range of detection applications, including ions,^20–22 gas molecules,^23,24 small molecules,^25–27 biomolecules^28–31 and cells.^32,33 Recently, chemical modification on the outer-surface of nanochannels has provided an alternative strategy for functional layer construction to recognize the target sensitively. Meanwhile, tunable pore metrics, structural diversity and rich functionality are also the key parameters for nanofluidic sensing performances. Metal–organic framework (MOF) materials, which have a large surface area, high porosity and abundant functional sites, are the prime candidates for designing nanofluidic sensors.⁸ Combining MOFs with nanochannels would provide an advanced TNP detection strategy.

Here, we demonstrate a biomimetic olfactory nanofluidic sensor for ultrasensitive TNP detection. Inspired by the dog's sensory neurons in the acute olfactory system, a TNP-responsive nanofluidic sensor (AAO@UiO-66-NH₂) is constructed by growing dense MOF (UiO-66-NH₂) layers in situ on the outer surface of anodic aluminum oxide. When TNP molecules are specifically captured by the amino groups of AAO@UiO-66-NH₂ through charge transfer and hydrogen bonding interaction,^2,34–36 the surface charge density and steric hindrance of the nanochannels would be regulated by the specific molecular recognition, which governs the ion transport behaviors. The concentrations of TNP are quantitatively analyzed by monitoring the changed ionic current, and the concentration range of TNP is from 1 × 10⁻¹⁴ to 1 × 10⁻¹⁰ g mL⁻¹. The nanofluidic sensor has an ultra-low detection limit of 6.5 × 10⁻¹⁶ g mL⁻¹ which outperforms that of reported detection methods. This portable sensor is suitable for rapid quantitative analysis for strictly supervising TNP as well as other hazardous explosives to effectively lower the disastrous threat of terrorism.

Results and discussion

Fabrication of the nanofluidic sensor

“We see the world, dogs can smell it.³⁷” Dogs have gotten honour in homeland security, military applications and security inspections due to their surpassing olfactory. Once the odour molecules bind to the corresponding receptor, G-proteins will be activated to generate cAMP molecules by the OSNs of the dog. The stepwise amplification process of the signal leads to ion transport through selective biological nanochannels, which realizes the conversion of chemical information to neural signals³⁸ (Scheme 1). Inspired by the dog's olfactory sensory neurons, we constructed a TNP-responsive nanofluidic sensor with excellent sensitivity and selectivity by AAO coupling UiO-66-NH₂ for TNP detection. As an electron-deficient nitroaromatic compound, TNP forms Meisenheimer complexes with electron-rich amino groups through charge-transfer complexing interactions due to the strong electron-withdrawing effect of the nitro group.^2,34–36 As a result, TNP molecules captured on AAO@UiO-66-NH₂ will regulate the ion transport through the confined interface of the nanofluidic sensor. The transmembrane ionic current will correspond to the concentration of TNP after the molecular recognition on AAO@UiO-66-NH₂.

Scheme 1 The scheme of the OSNs-inspired nanofluidic sensor (AAO@UiO-66-NH₂) for TNP detection. TNP jeopardizes public safety and human health due to its extremely high explosive power and irreversible bodily harm. Large specific surface area in the maxilla turbinate and the hundreds of millions of olfactory receptors give dogs an extremely sensitive sense of smell. The detailed process is as follows, targets bind to their specific receptor, and the associated G-protein is activated which activates adenylyl cyclase and transforms adenosine triphosphate into adenosine 3′–5′-cyclic monophosphate (cAMP). The cAMP would open ion channels (a cyclic nucleotide-gated (CNG) channel), which leads to the occurrence of cation (Na⁺ and Ca²⁺) influx and action potentials are eventually generated. Inspired by the olfactory system, a biomimetic olfactory nanofluidic sensor based on in situ growth of UiO-66-NH₂ is fabricated to sensitively detect TNP.

The nanofluidic sensor is fabricated by in situ synthesis of a dense UiO-66-NH₂ layer on the barrier layer of AAO (Fig. 1a and S1†). First, (3-aminopropyl)triethoxysilane (APTES) molecules are modified on AAO as the covalent linker between the MOFs and AAO. During the growth process of UiO-66-NH₂ crystals, benzoic acid molecules are used to control the growth process and crystal size of UiO-66-NH₂, which is important to manufacture the dense and continuous MOF crystal layer. Compared with the AAO (Fig. 1b and S2†), the dense and continuous UiO-66-NH₂ layer is successfully grown on the outer surface of AAO (Fig. 1c). The thickness of UiO-66-NH₂ on the barrier layer of AAO is about 580 nm. As shown in the cross-section image of AAO@UiO-66-NH₂ in Fig. 1d, the membrane is divided into two regions: the UiO-66-NH₂ layer and AAO channels. The diameter of the nanochannel of AAO is about 40–70 nm (Fig. S3†) and the diameter of sub-nanometer channels of AAO is about 1.3 nm.³² X-ray photoelectron spectroscopy (XPS) demonstrates the modification process by the N 1s and Zr 3d typical peaks (Fig. 1e). The quantitative atomic analysis of XPS reveals the changes before and after modification (Fig. S4†). The decrease of Al (mole percentage) and increase of C and Zr prove the successful growth of UiO-66-NH₂ on AAO. The energy-dispersive spectroscopy (EDS) also confirms the successful modification compared with the unmodified nanochannels (Fig. S5–S7†). The roughness of the membrane also increases after the successful in situ growth of MOFs on the AAO (Fig. S8†). BET pore size distribution shows almost inherent pores with diameters of 6–7 Å and 1.06 nm in every single UiO-66-NH₂ crystal (Fig. 1f). The X-ray diffraction (XRD) patterns of AAO@UiO-66-NH₂ also prove the successful synthesis of UiO-66-NH₂ crystals (Fig. 1g).

Fig. 1 Preparation and characterization of AAO@UiO-66-NH₂. (a) Scheme of the fabrication process of AAO@UiO-66-NH₂. (b) Top view scanning electron microscopy (SEM) images of AAO with a barrier. (c) Top view and (d) cross-section view of AAO@UiO-66-NH₂, indicating a continuous and dense UiO-66-NH₂ layer with a thickness of about 580 nm in situ growing on the AAO barrier. Inset: the amplified SEM images of the (c) top view and (d) cross-section view of AAO@UiO-66-NH₂. (e) X-ray photoelectron spectra (XPS) of AAO and AAO@UiO-66-NH₂. (f) Nominal pore size distributions of UiO-66-NH₂ calculated based on the N₂ adsorption/desorption isotherms. (g) X-ray diffraction (XRD) patterns of AAO and AAO@UiO-66-NH₂.

TNP detection by the nanofluidic sensor

Due to the strong electron-withdrawing effect of the three nitro groups, TNP with the electron-deficient aromatic ring could form strong interactions with electron-rich –NH₂ of UiO-66-NH₂ on the outer surface of AAO. The charge transfer from amino groups to aromatic rings leads to the formation of Meisenheimer complexes between TNP and the primary amino groups in UiO-66-NH₂ (Fig. S9†). On the other hand, TNP is selectively adsorbed by UiO-66-NH₂ because the phenolic hydroxyl group of TNP strongly and selectively interacts with the Lewis base of UiO-66-NH₂via hydrogen bonding interactions. Meanwhile, this combination between TNP and UiO-66-NH₂ would influence the ionic transport behavior, which in turn alters the transmembrane currents. The quantitative analysis of TNP is realized by establishing a functional relationship between the concentrations of TNP and currents. The ion signal is monitored by using two Ag/AgCl electrodes and the obtained electrical signal could be visualized to represent the concentration of TNP (Fig. 2a and S10†). It's worth noting that the anode is placed on the MOF layer side and 0.1 M KCl is chosen as the electrolyte. In order to achieve the optimum capturing time, TNP is dropped on the MOF side and incubated for different times (10, 20, 30, 40, 50, 60, 90, 120, 180 seconds) at room temperature (Fig. 2b). The transmembrane current changed significantly in a very short period of time and reached a stable result within 180 seconds. As shown in Fig. 2c, the transmembrane currents decrease from 5.2 μA to 0.47 μA when UiO-66-NH₂ is grown on the outer surface of AAO. Nevertheless, the currents increase from 0.47 μA to 3.3 μA after AAO@UiO-66-NH₂ capturing TNP. The surface charge density (zeta potential) decreases from −33.5 to −3.1 mV after modifying MOFs and increases to −29.8 mV after capturing TNP, respectively (Fig. 2d). Furthermore, AAO@UiO-66-NH₂ is observed to be more hydrophilic compared with unmodified AAO (Fig. 2e), which is attributed to the extra amino and carboxyl groups of UiO-66-NH₂ (contact angle (CA) from 91.7° to 71.7°). But after capturing TNP, AAO@UiO-66-NH₂ is more hydrophobic (CA from 71.7° to 83.9°) because of the extra benzene ring and nitro groups of TNP. The transmembrane current reduces because of the reduced surface charge density and the increased steric hindrance. After capturing TNP, the Meisenheimer complexes are formed between AAO@UiO-66-NH₂ and TNP, and the zeta potential of AAO@UiO-66-NH₂ is significantly elevated, which enhances the surface charge density and is reflected in the transmembrane current increase. UiO-66 without amino groups is also grown on the AAO using the same preparation strategy to prove the binding mechanism. After detecting the same concentration of TNP, the currents of AAO@UiO-66 barely increase ((I − I₀)/I₀ = 0.6) compared with AAO@UiO-66-NH₂ ((I − I₀)/I₀ = 6.1) (Fig. S11†). In order to further reveal the mechanism of the effect on the nanochannel variations on the currents, two additional sensors (AAO@UiO-67-NH₂ and AAO@UiO-68-NH₂) are obtained by in situ growth of MOFs with similar structures but different organic ligand lengths. XPS demonstrates the successful growth of MOFs on AAO (Fig. S12–S14†). It is obviously observed that the currents of all three sensors increase after detecting TNP (Fig. S15†). However, the three sensors exhibit different sensitivities which could be distinguished by the relative change of currents. The relative change of currents of AAO@UiO-66-NH₂, AAO@UiO-67-NH₂ and AAO@UiO-68-NH₂ is 6.1, 1.4 and 0.3, respectively, which means that AAO@UiO-66-NH₂ has the highest sensitivity among the three sensors (Fig. 2f). This is attributed to the size-matched relationship between the three MOFs and TNP. The spatial dimensions of TNP (Fig. S16†) are bigger than the pore limiting diameter (PLD) of UiO-66-NH₂ (3.7 Å) but smaller than the PLD of UiO-67-NH₂ (6.0 Å) and UiO-68-NH₂ (8.8 Å) (Table S1†). In this circumstance, it is difficult for TNP to enter UiO-66-NH₂ but it is adsorbed on the surface of UiO-66-NH₂ (Fig. 2g). The change of surface charge density dominates mass transport behavior compared to steric hindrance. But as for UiO-67-NH₂ and UiO-68-NH₂, TNP is able to enter the inter composition which leads to a combination of size and charge effects controlling ion transport behavior (Fig. 2h and i). Therefore, the transmembrane currents all exhibit an increase after detecting TNP due to charge enhancement, but the relative change of currents decreases sequentially with increasing length of the organic ligand because of steric hindrance.

Fig. 2 The OSNs-inspired nanofluidic sensor (AAO@UiO-66-NH₂). (a) Scheme of the experimental setup for monitoring the ion current of the sensor. (b) The transmembrane currents of the nanofluidic sensor are obtained at different incubation times. (c) The ionic currents are obtained from AAO, AAO@UiO-66-NH₂ and TNP-responsive (TNP concentration: 10⁻¹⁰ g mL⁻¹). (d) Zeta potential and (e) contact angle (CA) of the AAO, AAO@UiO-66-NH₂ and TNP-responsive. (f) ((I − I₀)/I₀) relative change of ionic current versus different organic ligands of MOFs, where I stands for current at voltage +2 V after capturing TNP (concentration: 10⁻¹⁰ g mL⁻¹), and I₀ stands for the transmembrane current of the fabricated sensors. Different organic ligands have similar structures, distinguished by their lengths. (g–i) The calculation of micromolecular adsorption states on the three sensors.

TNP detection performance of the nanofluidic sensors

The detection performances of AAO@UiO-66-NH₂, AAO@UiO-67-NH₂ and AAO@UiO-68-NH₂ at different concentrations of TNP are verified to meet analysis needs. Different concentrations of TNP solution are used to assess their detection range and limit. The changed transmembrane currents of the three detection platforms could be obviously observed at different TNP concentrations. With the increase in TNP concentrations (10⁻¹⁴ to 10⁻¹⁰ g mL⁻¹), the currents of AAO@UiO-66-NH₂ increase from 1.3 to 3.3 μA (Fig. 3a) and the relative change of current increases from 1.7 to 6.1 μA (Fig. 3d). By plotting the (I − I₀)/I₀ at +2.0 V versus the logarithm of TNP concentration (lg C), the calibration curve is obtained. The curve equation is y = 1.151 × lg C + 17.496 (R² = 0.9585). The limit of detection (LOD) is 6.5 × 10⁻¹⁶ g mL⁻¹ (3S₀/K) (where S₀ stands for deviation from the blank and K stands for the slope of the calibration curve). Also, the current of AAO@UiO-67-NH₂ increases from 27.5 to 54.5 μA (Fig. 3b) and the relative change of current increases from 0.2 to 1.4 μA (Fig. 3e), which is much smaller than that of AAO@UiO-66-NH₂. The curve equation is y = 0.29 × lg C + 4.313 (R² = 0.984). The limit of detection (LOD) is 2.0 × 10⁻¹⁵ g mL⁻¹ (3S₀/K). But as for AAO@UiO-68-NH₂, the detection performance is worst and the relative change of currents is only 0.25 (Fig. 3c and f). Besides, AAO@UiO-66-NH₂ without a barrier layer is selected as a sensor to detect TNP under the same experimental conditions (Fig. 3g). The current changes are not conspicuous and are far less than those of AAO@UiO-66-NH₂ with barrier layers (Fig. 3h). At last, the effect of incubation position on detection performance is also researched, with separate incubation on the porous and barrier side, and subsequent transmembrane current detection (Fig. 3i). When incubating on the porous side, the current change is small and the relative change is only 0.2.

Fig. 3 The OSNs-inspired nanofluidic sensor for TNP detection. (a–c) I–V curves of the nanofluidic sensor with different concentrations of TNP using different sensors, AAO@UiO-66-NH₂ (a), AAO@UiO-67-NH₂ (b) and AAO@UiO-68-NH₂ (c). (d–f) The ((I − I₀)/I₀) relative change of current vs. different TNP concentrations of the three sensors, AAO@UiO-66-NH₂ (d), AAO@UiO-67-NH₂ (e) and AAO@UiO-68-NH₂ (f). Inset: linear calibration plot of (I − I₀)/I₀vs. lg C, where I stands for current at voltage +2 V at different concentrations of TNP, I₀ stands for the transmembrane current of the fabricated sensors, and C denotes the TNP concentration. (g) Scheme of two AAO@UiO-66-NH₂ with and without a barrier layer. (h) I–V curves of AAO@UiO-66-NH₂ without a barrier layer for detecting the same concentration of TNP (10⁻¹⁰ g mL⁻¹). Inset: scheme of the experimental setup for monitoring the ion current of the sensor. (i) The ((I − I₀)/I₀) relative change of current of AAO@UiO-66-NH₂ with a barrier layer when incubating TNP on the porous side or barrier side. Inset: I–V curves of AAO@UiO-66-NH₂ with a barrier when incubating TNP on the porous side.

Application feasibility of the nanofluidic sensor

In practical explosives detection scenarios, a variety of explosives would disturb the detection performance of TNP. Fig. 4a illustrates the relative change of current of AAO@UiO-66-NH₂ after detecting prevalent explosives, including hexogen (RDX), diazodinitrophenol (DDNP), 2,4,6-trinitrotoluene (TNT), octogen (HMX), and pentaerythritol tetranitrate (PETN). Compared with the other explosives, the currents of TNP exhibit more pronounced current signal changes. Outstanding selectivity indicates the specificity of the sensor, which effectively avoids false positives. The application feasibility of the nanofluidic sensor is evaluated in the actual environment. The samples collected from soil and cloth containing TNP are tested to evaluate the actual detection performance for TNP. The result exhibits that TNP could be selectively detected in samples from the actual environment (Fig. 4b). Stable current and tiny relative change of current over time indicate that the sensor could maintain long-term reliability (Fig. S17†). Notably, the limit of detection (LOD) of AAO@UiO-66-NH₂ is lower than some reported detection methods, including a variety of detection methods, such as fluorescence quenching, electrochemical, aggregation induced emission and other methods (Fig. 4c). The nanofluidic sensor with good sensitivity and selectivity anticipates broad application viability.

Fig. 4 Application viability of AAO@UiO-66-NH₂ for TNP detection. (a) Comparing the detection performance of different explosives (concentrations are all 10⁻¹⁰ g mL⁻¹). (b) Testing of explosives in the actual environment (soil and cloth). (c) Comparison with the LOD of the reported sensors in the literature.^{10,12,39–52}

Conclusion

In summary, an OSNs-inspired nanofluidic sensor is devised to ultrasensitively detect TNP. The target molecule could be specifically captured by AAO@UiO-66-NH₂ through electrostatic and hydrogen bonding interactions and forms Meisenheimer complexes with amino groups on the framework. The steric hindrance and zeta potential are regulated after capturing targets, which combines to affect the ion transport across the membrane. This nanofluidic sensor enables detection of TNP in the concentration range of 10⁻¹⁴ to 10⁻¹⁰ g mL⁻¹ and has an ultra-low limit of detection of 6.5 × 10⁻¹⁶ g mL⁻¹, making it one of the most advanced sensors in the literature. This work has the potential to trigger further scientific explorations in the design of sensors for trace target analysis, and provide significant guidance for other explosives detection in homeland security, military applications, security inspections and environmental monitoring.

Data availability

The data supporting the findings can be found in the article and ESI,† and are available from the authors upon reasonable request.

Author contributions

Xin Li: conceptualization, methodology, writing – original draft, writing – review & editing, visualization, validation, formal analysis, investigation, resources, and data curation. Zhanfang Liu: resources and investigation. Linsen Yang: investigation and formal analysis. Shengyang Zhou: investigation and resources. Yongchao Qian: methodology and resources. Yuge Wu: investigation and visualization. Zidi Yan: software. Zhehua Zhang: investigation and resources. Tingyang Li: investigation and resources. Qingchen Wang: investigation and resources. Congcong Zhu: investigation, writing – review & editing and resources. Xiang-Yu Kong: investigation, supervision and resources. Liping Wen: conceptualization, supervision and project administration.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was supported by the National Key R&D Program of China (2020YFA0710401), the National Natural Science Foundation of China (22304172, 22122207, and 21988102), and the China Postdoctoral Science Foundation (2023M733449).

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Footnote

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4sc05493h

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