A benzene vapor sensor based on a metal-organic framework-modified quartz crystal microbalance

A benzene vapor sensor based on a metal-organic framework-modified quartz crystal microbalance

Journal Pre-proof A benzene vapor sensor based on a metal-organic framework-modified quartz crystal microbalance Zhiheng Ma, Tongwei Yuan, Yu Fan, Luyu...

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Journal Pre-proof A benzene vapor sensor based on a metal-organic framework-modified quartz crystal microbalance Zhiheng Ma, Tongwei Yuan, Yu Fan, Luyu Wang, Zhiming Duan, Wei Du, Dan Zhang, Jiaqiang Xu

PII:

S0925-4005(19)31564-3

DOI:

https://doi.org/10.1016/j.snb.2019.127365

Reference:

SNB 127365

To appear in:

Sensors and Actuators: B. Chemical

Received Date:

26 January 2019

Revised Date:

28 October 2019

Accepted Date:

29 October 2019

Please cite this article as: Ma Z, Yuan T, Fan Y, Wang L, Duan Z, Du W, Zhang D, Xu J, A benzene vapor sensor based on a metal-organic framework-modified quartz crystal microbalance, Sensors and Actuators: B. Chemical (2020), doi: https://doi.org/10.1016/j.snb.2019.127365

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier.

A benzene vapor sensor based on a metalorganic framework-modified quartz crystal microbalance Zhiheng Maa, Tongwei Yuana, Yu Fana, Luyu Wangb, Zhiming Duana, Wei Dua, Dan Zhanga, Jiaqiang Xua*

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NEST Lab, Department of Physics, Department of Chemistry, College of Science, Shanghai University, Shanghai 200444, PR China b

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Institute of Fiber Based New Energy Materials, The Key Laboratory of Advanced Textile Materials and Manufacturing Technology of Ministry of Education, School of Materials Science and Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China *E-mail: [email protected]



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Highlights:

The MOF-14-based QCM has an excellent sensitivity (1200 [email protected] ppm) and

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selectivity to benzene, as well as ultra-low detection limit (150 ppb) and good stability.

It has always been a tough problem to detect the most toxic benzene vapor. For the

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first time, We have produced a high selective benzene sensor. 

Through computational simulation, we found the selective response of MOF-14 to

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benzene is related not only to the interaction between ligands and detection

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molecules, but also to the steric hindrance effect of adsorption process.

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Abstract

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As one of the BTEX (benzene, toluene, ethylbenzene, xylene) from living environment, benzene has the greatest carcinogenic, anesthetic and neurotoxic effects. At the same time, due to its chemical inertness and nonpolar characteristics, benzene is also the most difficult to detect in BTEX. Herein, based on QCM (quartz crystal microbalance) platform, MOF-14, a metal-organic framework, is first employed to detect benzene vapor by the host−guest interaction of MOF with benzene molecule, as well as Lewis acid-base interaction. By comparing with other three types of MOF materials, it was found that the effect of the ligand on the adsorption is greater than that of the metal point of junction. On the other hand, the different steric hindrance effects in BTEX restrict their adsorption capacity. Thus, the MOF-14 modified QCM sensor exhibits high sensing performance to benzene vapor with a detection limit at the level of 150 ppb. Our studies also indicate that the sensor shows good selectivity to oppose various kinds of interfering gases. Even toluene has a structure similar to that of benzene, it also can be distinguished. And the measurements on repeatability and longterm stability are both approved for the excellent reliability of the MOF-14 modified QCM sensor. By using computational simulation, we explored that why benzene and toluene can be distinguished by MOF-14 modified QCM sensor. This work extended the usages of MOF based QCM for high performance benzene sensing. Keywords: Quartz crystal microbalance (QCM), Gas sensor, Metal−organic framework (MOF), Sensing mechanism, Benzene detection

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Introduction

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BTEX (benzene, toluene, ethylbenzene, xylene), as important chemical raw materials, are widely used as solvent for fat, resin and iodine. In addition, they are also proverbially employed for decoration of coatings and solvents [1]. However, as typical volatile organic compounds, BTEX are easily released into the air during the processes of synthesis and use. What's worse, they exist widely in the surroundings of residences and vehicles [2, 3]. After a century of research, scientists have shown that long-term exposure to the vapors of BTEX can lead to chronic poisoning, aplastic anemia and leukemia, etc. [4, 5]. Among BTEX, toluene, xylene and ethylbenzene with the methyl or ethyl group on the benzene ring can be oxidized to a carboxyl group in the human body, then excreted to the outside of the body. But benzene cannot be discharged through this process, so it has cumulatively toxic in body, thus it has the greatest toxicity for human [6, 7]. On October 27, 2017, in the list of carcinogens published by the International Agency for Research on Cancer of the World Health Organization, benzene was classified as Category Ⅰ which is certain can cause cancer. while ethylbenzene was in Category Ⅱ B, toluene and xylene were in Category Ⅲ which is possible can cause cancer[8]. Some scientists and technicians have taken various measures to solve this problem. These measures include gas chromatography-mass spectrometry [9, 10], fluorescence analysis [11], semiconductor sensors [12] and so on. Moreover, gas chromatographymass spectrometry equipment is very expensive and requires professional skills. Therefore, it is scientific research, but unsuitable for commercially online detection. Meanwhile, fluorescence analysis also faces similar drawbacks. Semiconductor sensors detect the change of material resistance based on the redox reaction when the sensing materials are exposed to the target gases or vapors at high temperature. Owing to its advantages of low cost and simple operation, some work on semiconductor sensors to detect BTEX has emerged. Ming-Tsun Ke et al. [13] fabricated a benzene gas sensor with a self-heating WO3 sensing layer. At the optimal working temperature, the sensor has a high degree of sensitivity (1.0 KΩ ppm(-1)). Huihua Li et al. [14] manufactured a mesoporous SnO2-based sensor prepared by carbon nanotubes template. Feihu Zhang et al. [15] presented a selective BTEX sensor based on SnO2/V2O5 composite, and the detection limit of BTEX can reach 500 ppb. However, semiconductor sensors need to work at high temperatures, and benzene molecule is chemically inert because of its symmetry and high activation energy of C-H bond. Therefore, it is difficult to detect low concentration benzene vapor via using semiconductor sensors. Unlike semiconductor sensor that need high working temperature, the quartz crystal microbalance (QCM), a bulk acoustic wave (BAW) device, can also apply to gas and humidity sensors [16-18], electronic noses [19] and immunosensors [20] owing to its high sensitivity, stability and especially the property of low working temperature (050℃). QCM is an electromechanical oscillator which utilizes the piezoelectric effect of quartz crystal to transform the surface quality change into the frequency variation of electric signal. It is composed of a thin slice of quartz crystal with double-faced deposited metal electrodes. We observe the equation (1) [21-23], where f0 is the 3

fundamental resonant frequency which depends on the nature of QCM chip, A is the area of the silver plates coated on quartz crystal. μ and ρ is the shear modulus and density of quartz crystal respectively. Meanwhile, c is a related constant that has a fixed value when the area of the wafer are determined, and in this work, the value of c is 0.5. Apart from mentioned invariants above, the frequency shift (Δf) is proportional to the mass change of adsorption (Δm) in the electrode surface of the QCM. 𝜟𝒇 =

𝟐𝒇𝟐𝟎 𝑨√𝝁𝝆

𝜟𝒎 = −𝒄𝜟𝒎

(𝟏)

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Metal organic frameworks (MOFs) have many merits, such as high specific surface area that can provide more adsorption sites, which is a key factor for QCM sensor, adjustable central ion that can provide Lewis acid sites for a specific interaction between MOFs and the electron donor of BTEXs, and tunable pore size that can enhance gas selectivity based on molecular diameter. These merits make MOFs theoretically suitable for QCM sensing materials [24-27]. In prior work, by loading HKUST-1 on mass-gravimetric resonant-cantilevers, Xu, et al. [28] fabricated a xylene sensor and the limit of detection of xylene is 400 ppb. However, we have not found any QCM gas sensor can successfully distinguish benzene from BTEX. Based on the previous research results and theoretical analysis, we speculate that the design of excellent sensors to benzene should be divided into two aspects. On the one hand, by increasing the number of benzene rings in the ligands and changing the kinds of central metals in MOFs, the sensitivity of MOF to benzene can be improved. On the other hand, the selectivity of MOF to benzene in BTEX could be achieved by regulating the pore size which depend on the effect of steric hindrance. Herein, four kinds of MOFs, MOF-14 (Cu(BTB)), HKUST-1 (Cu(BTC)), MOF-177 (Zn(BTB)) and MOF-74 (Mg(DOBDC)), were used to modify QCM chips to investigate the sensitivity to benzene vapor. The gas sensing measurements of four kinds of MOFs indicating that MOF-14 shows the highest sensitivity (1200 [email protected] ppm) and selectivity to benzene, as well as ultralow application detection limits of benzene (500 ppb) and theoretical detection limit (150 ppb). Moreover, this sensor also shows good cyclic stability and reliable long-term stability. Through computational simulation, we found the selective response of MOF14 to benzene is related to not only the interaction between ligands and detection molecules, but also the steric hindrance effect of adsorption process. Our work is expected to develop novel and practical QCM based benzene sensors, which has good market potential.

2. Experimental

2.1. Materials All of the reagents were commercially available and used without any purification. Copper (II) nitrate heMi (pentahydrate) (Cu(NO3)2·2.5H2O, 98.0%) and 1,3,5-Tri(4carboxyphenyl) benzene (H3BTB, 98.0%) were obtained from Alfa Aesar. Zinc Acetate Dihydrate (Zn(OAc)2·2H2O , 99.0%), Magnesium nitrate hexahydrate 4

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(Mg(NO3)2·6H2O , 99.0%), benzene (99.0%), toluene (99.5%), xylene (99.0%) and N, N-dimethylformamide (DMF, 99.0%) were purchased from Shanghai Chemical Reagent Co., Ltd. Trimesic acid (H3BTC, 99.0%), p-Phthalic acid (98.0%), N, Ndiethylformamide (DEF) and 2,5-Dihydroxyterephthalic acid (99.0%) were obtained from Maclin. 2.2. Synthesis 2.2.1. Synthesis of MOF-14 First, 43.8 mg H3BTB (0.1 mmol) and 46.4 mg Cu(NO3)2·2.5H2O (0.2 mmol) were each dissolved into 25 mL mixture of ethanol and deionized water with volume ratio 4:1. Then, the acid solution was added to the copper salt solution under stirring over ten minutes at ambient temperature. After stirring for 24 hours, the precipitate was separated and washed with 25 mL ethanol and deionized water several times. Finally, the product was dried by Critical Point Dryers. 2.2.2. Synthesis of HKUST-1 Synthesis of HKUST-1 was performed following the reported procedures [29] with a few modifications. First, 42.0 mg H3BTC (0.2 mmol) and 69.6 mg Cu(NO3)2·2.5H2O (0.3 mmol) were each dissolved into 25 mL mixture of ethanol and deionized water with volume ratio 1:1. The later operation is same as 2.2.1. 2.2.3 Synthesis of MOF-177 65.6 mg H3BTB (0.143 mmol) and 251 mg Zn(OAc)2·2H2O (1.14 mmol) were each dissolved into 25 mL DEF. Then, the diacid solution was added to the zinc salt solution under stirring over ten minutes at ambient temperature. After stirring for 24 hours, the product was washed with 20 mL DEF several times, and dried by Critical Point Dryers. 2.2.4 Synthesis of MOF-74 Synthesis of MOF-74 and MOF-177 was performed following the reported methods [30] with a few modifications. First, 239 mg 2,5-Dihydroxyterephtalic acid (1.20 mmol) and 928 mg Mg(NO3)2·6H2O (3.62 mmol) were each dissolved into 30 mL dimethylformamide (DMF). The later operation is same as 2.2.3 except changing DEF to DMF. 2.3 Characterization Field emission scanning electron microscope (FE-SEM, JSM-6700F) and transmission electron microscope (TEM, JEM-200CX) were employed to observe the MOFs' morphologies and micro-structures. Powder X-ray diffraction patterns of samples were recorded at 0.02°/s and operated at 40 kV and 15 mA current with Cukα1 radiation (λ=0.15406nm) diffractometer (XRD, Dmax 2500V). The obtained N2 adsorption-desorption isotherms were evaluated by a Micromeritics ASAP 2020 system. The Fourier transform infrared (FT-IR) spectra was measured by the KBr window sheet material on a NICOLETIS 10. 2.4 Fabrication of QCM sensors and measuring equipment QCM resonators (f0=107 Hz) coated with silver electrodes were purchased from WestSensor Co., Chengdu, China. QCM adsorption measurements were performed on a modified setup we had reported previously [31-35]. QCM is first soaked respectively in acetone for 10 min and ethanol for half an hour. Then dried at 60oC to ensure the QCM is clean and free of impurities. Subsequently, the four as-synthesized samples 5

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were dispersed into distilled water to form the suspension (1 mg mL-1), respectively. Then, 2 μL of the suspension was drop-cast onto one side of the QCM electrode and the as-made sensors were put into a vacuum oven for 2 hours. The obtained QCM sensor was set in a sealed chamber with gas inlet/outlet and highpurity nitrogen flew as a carrier gas was flushed until a stable baseline was obtained. Then, the specific gas was introduced into the chamber and after tens of seconds a steady response could be obtained. When each measurement ended, the carrier gas was reintroduced again to make sure the baseline returns to its original level. All these measurements were conducted at room temperature (25.0 ±1.0 °C). The QCM sensor generated a frequency-decrease after benzene was absorbed on the surface of MOF sensing material. Fig. 1 gives a scheme of experimental setup. 2.5 Simulated calculations for adsorption thermodynamics Adsorption simulations for benzene and toluene in MOF-14 were performed with Accelrys Material Studio 7.0, using the universal force field method. Firstly benzene and toluene single molecule was set in a 10 × 10 × 10 Å crystal lattice, respectively, and was optimized in DMol3 [36, 37] module using generalized gradient approximation (GGA) with the Perdew-Burke-Ernzerof (PBE) exchange correlation, to get optimal conformations. The double numeric polarization (DNP) [38] basis set was used for describing atomic orbitals. A real-space orbital global cutoff of 4.5 Å was applied. The simulations of adsorption isotherms and energy distribution curves were carried out in the sorption module using the metropolis method, in the conditions of 104 equilibration steps, 105 production steps and 50 fugacity steps in 298 K. The pressure for benzene and toluene were both set up from 1 Pa to 100 Pa. The method used in the simulation calculation is based on the previous literature [39, 40].

3. Results and discussion

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3.1 Synthesis of MOFs Fig. 2 displayed experimental and simulated XRD patterns of the four MOFs. It is found that the diffraction patterns of all the samples are all in good agreement with the simulated diffraction pattern according to the known crystal structures (four inserts in Fig. 2). Small changes in the diffraction patterns among these MOF samples should be attributed to variations in the guest molecules remaining inside the pores of MOFs. The central metal ions and corresponding ligands are shown in Table 1. SEM images of the MOF samples are shown in Fig. 3. MOF-14 and HKUST-1 are found to be irregularly rhombic dodecahedrons (Fig. 3a) and octahedron (Fig. 3b) with the mean particle size about 2-3 μm. MOF-177 presents irregular cube (Fig. 3c) with the size of about 10 μm, whereas MOF-74 was cauliflowers (Fig. 3d) with uniform particle size of about 6-8 μm. The FT-IR spectra of four MOFs were shown in Fig. 4, and the stretching vibrations peaks of the corresponding samples are in accordance with the four corresponding standard patterns that were previously reported [41-44]. From the HRTEM (High Resolution Transmission Electron Microscope) images, we observe the existence of nanopores within four MOFs and MOF-14 has the largest pore size. By using the N2 sorption experiment, the structural data for specific surface area and pore 6

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size of the four above MOFs were obtained and listed in Table 2. The four MOFs feature Langmuir surface areas are in the range of 1521-1892 m3/g which is close to the value reported in previous studies, and the pore sizes ranged within 2-3 nm. These data are important because the specific surface area and pore size are both two key factors for adsorption. 3.2 Sensing performance of MOF-based QCM sensors. Here, in order to build mass-frequency sensors, the four kinds of MOF samples prepared were coated on the surface of QCM chips. In addition, a self-made chemical sensing device in laboratory was introduced to measure the gas sensing performances. In order to compare the sensitivity of four kinds of MOFs toward benzene vapor, we exposed the four sensors to the benzene vapor with the same concentration of 80 ppm at room temperature (Fig. 6). The results indicating that MOF-14-coated QCM sensor performed the best sensitivity to benzene in four kinds of MOFs, which response up to 1200 Hz, whereas, frequency shifts of MOF-177, HKUST-1 and MOF-74 are just 743, 480 and 200 Hz, respectively. It is obvious that MOF-14-coated QCM is more sensitive to benzene vapor than the others. By contrast, it is easy to find that MOF-14 and HKUST-1 have similar structure and same central ion (copper), and the only difference of the two samples is their ligand. MOF-14 employed H3BTB as a ligand instead of H3BTC in HKUST-1. More benzene rings in H3BTB may result in larger aperture and stronger interactions (π-π stacking between conjugated electrons) between the MOFs and BTEXs than HKUST-1. Therefore, MOF-14 has a higher response than HKUST-1. We may find that these two MOFs have the same ligands and unlike central ions by comparing MOF-14 and MOF-177. The Cu2+ in MOF-14 has a bigger ionic diameter than the Zn2+ in MOF-177, implying better adsorption between MOF-14 and BTEX because Cu2+ is softer Lewis acid. It is consistent with the result of better response to benzene vapor by MOF-14-based QCM sensor. Neither the ligand nor the central ion is same between MOF-14 and MOF-74. For MOF-74, its response to benzene is the lowest among the four samples, not only because there are few benzene rings in the ligand but also on account of the central ion Mg2+ is hard Lewis acid. Hereto, we can make a conclusion. The contribution of benzene rings for gas sensing is far more than that of the central ions by contrasting MOF-177 and HKUST-1. Because most central ions have been coordinated by surrounded ligands, only leading to a weaker interaction between central ions and BTEX than that in the state of free ion. Overall, comparing with other three samples, the MOF-14-based QCM sensor has prime response to benzene vapor owing to the most benzene rings and soft Lewis acid of central ions. Its more sensing parameters, including sensitivity, selectivity, and stability, will be further evaluated as follows. Seven kinds of vapors are chosen to evaluate the gas selectivity of MOF-14 to benzene, including acetone, methanal, methanol, ethanol, toluene, xylene, ethylbenzene. As shown in Fig. 7a, MOF-14-based QCM sensor exhibits an excellent selectivity to benzene vapor. When MOF-14 coated sensor is exposed to various gases (all at 100 ppm), it shows the highest response to benzene, which can reach 1500 Hz. The 7

frequency shift to methanol is the lowest, it has only 200 Hz. Based on Fig. 7a, calculated according to the equation (2) [45]: 𝒈𝒂𝒔

𝑹𝒊

𝝈 = ∑𝑵

𝒈𝒂𝒔 𝒊=𝟏 𝑹𝒊

𝑔𝑎𝑠

in the formula, the value of 𝑅𝑖

× 𝟏𝟎𝟎

(2)

is response of the sensor to a particular ith gas, where

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selectivity values, are plotted against the gas types at a concentration of 100 ppm and at 25°C, Fig. 7b is obtained. It can be observed that the MOF-14-based sensor has the highest selectivity to benzene gas at about 35%. And the selectivity improvements could be based on molecular imprinting [46]. This excellent selectivity to BTEX should be attributed to the strong π-π interaction and existence of Lewis acidity sites. However, considering the other three gas of toluene, ethylbenzene, and xylene, they have the same affinity as benzene, even toluene has a stronger electron-withdrawing group, but they also have greater steric hindrance. By comparing the maximum diameters of the four molecules (Fig. 8), it can be seen that the response is inversely related to their molecular size, namely the response decreases as the molecular diameter increases. It is worth noting that heat of adsorption of toluene[47] on MOF-14 is a slightly higher than that of benzene, but the frequency shift for toluene sensing is not larger owing to its greater steric effect, especially at high concentrations, and the result is further determined by computational simulations. Fig. 9a is a simulated adsorption isotherm of MOF-14 toward toluene and benzene. When the relative pressure is low, the adsorption amount of toluene is slightly larger than that of benzene. The results could be attributed to the higher adsorption heat of toluene than that of benzene. Because there is sufficient space in the pores, so the effect of steric hindrance is not very important. As the pressure increases, their adsorption capacity also increases. When the absolute pressure exceeds 10 Pa (at this point, the adsorption amount of benzene is same as that of toluene), the adsorption amount of benzene will be greater than toluene until saturation. It proves that only in an ultra-low pressure and without any adsorption state, toluene will be adsorbed easier than benzene. As the pressure increase, more molecules are adsorbed in the pores and cause the decrease of valid space. Therefore, the effect of steric hindrance becomes larger and this result is consistent with previous studies [41] which shown in Fig. 9b. The response curve of the MOF-14 to benzene vapors with various concentration is shown in Fig. 10. Fig. 10a displays the response curve of low concentration benzene from 1 ppm to 10 ppm. It can be found that the frequency shift for 1 ppm benzene vapor is 85 Hz. The response process is very fast with a response time of approximately 10 seconds and then reaches an equilibrium state of adsorption and desorption. When the benzene vapor is blown away, desorption of benzene vapor can complete very quickly and there is almost no drift in the baseline during continuous testing. The reason may be that the adsorption of benzene on MOF-14 is weak chemical adsorption. When a large amount of carrier gas is blown into the test chamber, the adsorption and desorption equilibrium proceeds to the reverse reaction direction, and the low-pressure benzene molecules in the pores are quickly replaced. To further investigate the sensing performance, the successive responses curve of MOF-14 toward 500-900 ppb benzene 8

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vapor is shown in Fig. 10b. As the gas concentration increases, the response increases, but the frequency shift caused by the same concentration (100 ppb) of benzene vapor is continuously reduced, meaning the valid pore volume and available adsorption sites of MOF-14 are decreasing with the amount of adsorption increases. The response of sensor toward 500 ppb benzene vapors is 45 Hz and it is much higher than the inherent noise of about ± 0.6 Hz. By combining the data of Fig. 10a and Fig. 10b, the relation between frequency shift and benzene concentration is obtained and plotted in Fig. 10c. When MOF-14 exposed to benzene vapor in the concentration range of ≤ 10 ppm (adjusted R-square is 94.03%), the relationship is very good in line with the Langmuir equation as 𝒂𝑲𝒑 𝑸 = 𝒂𝜽 = (𝟑) 𝟏 + 𝑲𝒑 Where Q is the quantity of the adsorbed benzene molecules (herein represented by the mass sensing response), θ is the fractional coverage that is proportional to the quantity of adsorbed benzene molecules, p is the gas partial pressure (i.e., molecule concentration), K is the equilibrium constant, and a is a proportional coefficient. Based on Langmuir sorption theory, at the very low concentration range, the fractional coverage θ ≪ 1 (i.e., Kp ≪ 1), there exists the following linear relationship 𝑸 = 𝒂𝑲𝒑 (𝟒) Fig. 10d shows that when the concentration is lower than 1 ppm, the response of the sensor vs benzene vapor concentration is a distinct linear relationship which can be well fitting into the equation (3). Thus, the limit of detection (LOD) of MOF-14 modified QCM sensor toward benzene was calculated by using the calibration curve (y = 77.14x + 8.14, R2 = 0.992) with data of Fig. 10a and Fig. 10b by the equation [48, 49]: 𝟑𝝈 𝑳𝑶𝑫 = (𝟓) 𝑺 Where σ is the standard deviation of the response (3.8), S is the slope of the calibration curve (77.14). The logical detection limit of QCM sensor coated MOF-14 for benzene vapor was found to be 150 ppb, which is lower than the human olfactory threshold of 470 ppb. Reproducibility is a critically important factor for assessing gas sensor. In our research work, four repeated cycles were tested on the gas sensor to 10 ppm benzene vapor (Fig. 11a). The results of cycling tests show the superior reproducibility of the MOF-14-based QCM sensing platform. Long-term stability is another key factor of gas sensor. The sensing response of MOF-14-based QCM to 60 ppm benzene was carried out for 6 months (Fig. 11b). The result shows that the deviation of our sensor is just 1.48%, demonstrating its exceptional long-term stability. The effect of humidity on benzene vapor sensing is not neglected when the sensors work at the room environment. Therefore, humidity interference test is necessary. Fig. 12a shows the humidity interference tests to 500 ppb benzene vapor while the relative humidity is ranged from 0% to 80%, and Fig. 12b is the same test to 10 ppm. From Fig. 12, it’s obvious that the effect of humidity on the sensor is almost same whether in high or low concentration of benzene. This result indicating that in spite of the humidity in the air may cause interference, the interferential signal is really slight compared with 9

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the response to benzene vapor. Since MOF is a microporous material with an ultra-high specific surface, it inevitably adsorbs some small molecules like CO2, H2O. However, the effect of this simple physical adsorption is very weak, and that is why the humidity increases by 80% the response is increased by only about 20 Hz. But we have to admit water does interfere slight with this sensor, and in the next research, we will reduce the interference of humidity by conforming to hydrophobic materials or optimizing the experimental devices. For exploring whether the other components of air interfere the QCM sensor based on MOF-14, we changed the test condition of carrier gas from pure nitrogen to air. At the same conditions, we used air as carrier gas to test the sensor’s signal when it was exposed to different concentrations of benzene vapor (1-10 ppm). As shown in Fig.13, there are only a few deviations of baseline, indicating that the sensor is not highly sensitive to air. In summary, the QCM sensor based on MOF-14 is highly reliable for detecting benzene when it exposes in the air regardless of the interfering components. Hence, it may be less radical to say that this benzene sensor has a market potential in the future.

Conclusion

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In summary, the microporous MOF-14 modified QCM sensor with high sensing performance toward trace benzene vapor had been comprehensively investigated. The excellent sensing performance should be attributed to the special host-guest interaction between BTEXs and MOF-14. The large specific surface and pore volume also provides higher adsorption capacity, further enhances the response of benzene vapor than other BTEXs. The MOF-14 modified QCM sensor exhibited a typical Langmuir-type response to 0.5-10 ppm benzene vapor. According to the linear equation, the LOD of MOF-14 sensor was calculated to be 150 ppb, which was lower than the human olfactory threshold of 470 ppb. The stability of MOF-14-coated sensor had been confirmed by comparing the two responses interval of six months. Our work explains in detail how to design QCM benzene sensor, which has in-depth scientific research and application prospects. However, as nothing is perfect, there is still a little defect of the interfere of humidity although the response of water is much smaller than the response of benzene, therefore, in the future research, we will focus on reducing the influence of humidity on the sensor by compounding with other materials or optimizing the testing period in practical application.

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Acknowledgements

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This work is supported by the National Natural Science Foundation of China (Grant 61527818 and U1704255). The authors also acknowledge the support of the Shanghai Municipal Education Commission (Peak Discipline Construction program).

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Captions Table captions

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Figure captions Figure 1. QCM schematic diagram. Figure 2. XRD patterns and simulated structures of (a) MOF-14, (b) HKUST-1, (c) MOF-177 and (d) MOF-74. Figure 3. SEM images of (a) MOF-14, (b) HKUST-1, (c) MOF-177 and (d) MOF-74. Figure 4. FT-IR spectra of MOF-14, HKUST-1, MOF-177 and MOF-74. Figure 5. HRTEM images of (a) MOF-14, (b) MOF-177,(c) HKUST-1 and (d) MOF74. Figure 6. The frequency change when QCMs exposed to 80 ppm benzene vapor (25°C). Figure 7. (a) Response of MOF-14-based QCM to different vapors in 100 ppm (25°C), (b) Selectivity values for the MOF-14-based sensor different vapors in 100 ppm (25°C). Figure 8. Response of MOF-14-based QCM vs maximum diameter of different BTEX and the inset picture is the sizes of BETX molecules. Figure 9. (a) The simulated adsorption molecules per cell of MOF-14 to toluene and benzene, (b) Schematic diagram of the actual adsorption difference between benzene and toluene by MOF-14. Figure 10. (a) Response and recovery curves of MOF-14-based QCM to benzene vapor from 1 to 10 ppm, (b) Dynamic responses of MOF-14-based QCM to sub-1 ppm benzene vapor, (c) Corresponding Langmuir adsorption fitting, (d) Linear fitting of low-concentration benzene vapor. Figure 11. (a) Cycling stability of MOF-14-based QCM to 10 ppm benzene vapor, (b) Long-term stability test of MOF-14-based QCM to 60 ppm benzene vapor. Figure 12. (a) The humidity interference tests to 500 ppb benzene vapor while the relative humidity is ranged from 0% to 80%, (b) The humidity interference tests to 10 ppm benzene vapor while the relative humidity is ranged from 0% to 80%. Figure 13. Response and recovery curves of MOF-14-based QCM to benzene vapor from 1 to 10 ppm with air as carrier gas.

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Table 1: Central metal ions and corresponding ligands of the four MOFs. . MOFs

Central metal ion

Ligand

MOF-14

Cu2+

1,3,5-benzenetribenzoate

HKUST-1

Cu2+

1,3,5-benzenetricarboxylate

MOF-177

Zn2+

1,3,5-benzenetribenzoate

MOF-74

Mg2+

2,5-dihydroxyterephthalate

Table 2: Summary of the tested physical parameters of the four MOFs SLangmuir (m2/g) (This work)

SLangmuir(m2/g) (References)

Pore size (nm)

MOF-14 HKUST-1 MOF-177 MOF-74

1755 1698 1892 1521

1617[42] 2245[24] 2156[24] 1525[50]

2.43 1.96 2.35 2.15

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Biographies Zhiheng Ma received his B.S. degree in computer science from Shenyang University of Chemical Technology in 2015. He is pursuing the M.S. degree of chemistry in Shanghai University now. Currently his main efforts are taken to QCM gas sensors and computational chemistry. Tongwei Yuan received his B.S. degree in applied chemistry from Beijing University of Chemical Technology in 2013. He is pursuing the M.S. degree of chemistry in Shanghai University now. Currently his main efforts are taken to semiconductor gas sensors.

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Yu Fan received his M.S. degree in chemistry from Shanghai University in 2017. Currently he is pursuing his Ph.D. degree and working toward chemical organic frameworks (COFs) in sensing and computational chemistry.

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Zhiming Duan received his Ph.D. degree in Institute of Chemistry, Chinese Academy of Sciences. Now, he is a lecturer in Department of Chemistry in Shanghai University. His interests include coordination chemistry and its applications.

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Wei Du received her M.S. degree in chemistry from Shanghai University in 2017. Currently she is pursuing her Ph.D. degree and working toward QCM gas sensors.

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Dan Zhang obtained her B.S. degree in College of Chemical and Environmental Engineering in 2016 from Shanxi Da Tong University. Now she is pursuing her Ph. D degree in Shanghai University. Currently her main efforts are taken to synthesize semiconductor sensing materials and QCM and study their gas-sensing properties.

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Jiaqiang Xu received his M.S. degree in inorganic chemistry from University of Science and Technology of China in 1988. And he received the Ph.D. degree in material science from Shanghai University in 2005. He is the chairman of the Special Committee of Gas and Humidity Sensor Technology now. Currently his research interests include the synthesis of sensing materials and the investigations of sensing mechanism.

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