Detection and discrimination of volatile organic compounds using a

May 27, 2019 - This paper describes the detection and discrimination of volatile organic compounds (VOCs) using an e-nose system based on a ...
0 downloads 0 Views 3MB Size
Download PDF
Article Cite This: ACS Sens. 2019, 4, 1524−1533

pubs.acs.org/acssensors

Detection and Discrimination of Volatile Organic Compounds using a Single Film Bulk Acoustic Wave Resonator with Temperature Modulation as a Multiparameter Virtual Sensor Array Guang Zeng,†,∥ Chen Wu,§,†,∥ Ye Chang,† Cheng Zhou,† Bingbin Chen,‡ Menglun Zhang,† Jiuyan Li,§ Xuexin Duan,† Qingrui Yang,*,† and Wei Pang*,†

Downloaded via UNIV OF SOUTHERN INDIANA on July 23, 2019 at 00:23:11 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

†

State Key Laboratory of Precision Measuring Technology and Instruments and ‡School of Electronic and Information Engineering, Tianjin University, Tianjin 300072, China § State Key Laboratory of Fine Chemicals, Dalian University of Technology, Dalian 116024, China S Supporting Information *

ABSTRACT: This paper describes the detection and discrimination of volatile organic compounds (VOCs) using an e-nose system based on a multiparameter virtual sensor array (VSA), which consists of a single-chip temperaturecompensated film bulk acoustic wave resonator (TC-FBAR) coated with 20-bilayer self-assembled poly(sodium 4-styrenesulfonate)/poly(diallyldimethylammonium chloride) thin films. The high-frequency and microscale FBAR multiparameter VSA was realized by temperature modulation, which can greatly reduce the cost and complexity compared to those of a traditional e-nose system and can allow it to operate at different temperatures. The discrimination effect depends on the synergy of temperature modulation and the sensing material. For proof-of-concept validation purposes, the TC-FBAR was exposed to six different VOC vapors at six different gas partial pressures by real-time VOC static detection and dynamic detection. The resulting frequency shifts and impedance responses were measured at different temperatures and evaluated using principal component analysis and linear discriminant analysis, which revealed that all analytes can be distinguished and classified with more than 97% accuracy. To the best of our knowledge, this report is the first on an FBAR multiparameter VSA based on temperature modulation, and the proposed novel VSA shows great potential as a compact and promising e-nose system integrated in commercial electronic products. KEYWORDS: gas sensing, single-chip film bulk acoustic wave resonator (FBAR), multiparameter virtual sensor array (VSA), temperature modulation, e-nose system

V

system,8−11 which consists of an array of gas sensors, each of which is functionalized with a special chemically or biologically sensitive layer for target analyte detection.12−18 Thus, extracting multidimensional features from signals generated by a multisensor array (MSA) enables the use of pattern recognition techniques19−23 to identify and discriminate unknown vapors. However, e-nose systems may face many issues, such as complicated sensing circuits, complex modification processes, and high breakdown possibilities, since the whole e-nose system does not work if any of the component devices fail,24 which makes reducing the cost, size, and power consumption of these sensors and increasing their stability difficult. To overcome the drawbacks of traditional MSAs, a new mechanism called the virtual sensor array (VSA) has been

olatile organic compounds (VOCs) are categorized as hazardous materials that have short-term and long-term negative effects on the environment and human health. Moreover, some exhaled VOCs are effective biomarkers that could be used for the simple detection of diseases; for instance, VOCs such as toluene, isoprene, and acetic acid can be used as biomarkers for detecting lung cancer.1−3 Thus, monitoring VOCs is extremely crucial in the fields of environmental monitoring,4 chemical warfare,5 explosive detection,6 and clinical diagnostics.7 Over the past few decades, many types of commercial portable devices that can quantitatively detect VOCs have been developed. Most of them are dependent on concentration detection, which leads to the problem of distinguishing an individual gas in a mixture of various VOCs. To meet the specific needs of gas detection systems, gas sensors need not only to sensitively detect the concentration of a single VOC but also to effectively distinguish different VOCs. One of the most useful methods for gas discrimination is the electronic nose (e-nose) © 2019 American Chemical Society

Received: December 27, 2018 Accepted: May 27, 2019 Published: May 27, 2019 1524

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors

work in the temperature range from 20 to 200 °C, which is promising for integration into mobile phones, watches, and other electronic products. This heating method would ensure the stability of the operating temperature of the FBAR. In the experiment, four different power cycles (0, 0.1, 0.2, 0.3 W) were simply used to form four different temperatures for the VSA, which was utilized to discriminate six different VOC vapors at six different gas partial pressures. And two parameters of the FBAR, the frequency and the impedance, were measured to provide more dimensional information about the analytes, which play an important role in the statistical data analysis. The change in temperature affects the adsorption and desorption of VOC molecules on the surface of the device, which can be reflected by the different frequency shifts and impedance change. Additionally, in consideration of a fixed period of VOC delivery system, we change the heating method from single power to multiple powers in a cycle, which makes the use of proposed VSA in the discrimination of VOCs more convenient and less power consuming. The results show that the temperature-modulated TC-FBAR VSA sensor exhibits an excellent capability to discriminate similar VOCs, making this VSA a promising candidate as a novel alternative e-nose system.

developed using an individual sensor based on an e-nose system, in which the individual sensor can produce multidimensional sensing features similar to those achieved by an MSA. Single-chip VSA features a greatly reduced number of sensors, which is beneficial for minimizing the malfunction of the whole e-nose system and integrating it into a miniaturized platform. The key element for forming a VSA is achieving variant response modes in a single device. One way is to use the intrinsically different modes of special sensors, such as the multimode photonic vapor sensor inspired by Morpho butterflies25−27 and the quartz crystal microbalance (QCM) based on its multiple high-order resonances.28−31 In this method, the sensitivity of the device is limited by the lowest sensitivity of different modes; as a result, the sensitivity of this kind of device cannot be very high. Another way is to use a single mode of sensors to create a diversity of responses. The most extensively reported method is temperature modulation; for example, the response of field-effect transistor (FET) devices is different under different temperatures, which can be used to discriminate various analytes.32,33 However, these VSAs often require high-temperature operation, which far exceeds the tolerable temperature of commercial electronic products. To enable the use of the VSA in our daily life, we need to develop an easily obtainable VSA with good performance that is compatible with most electronic products. Considering that the film bulk acoustic resonator (FBAR) has been commercialized for many years, it offers excellent portability and compatibility with electronic products. In addition, FBAR sensors are known for providing a simple sensing method based on the measurements of resonator frequency shifts and have been widely used as portable electronic gas sensors.34,35 Hence, in this work, we are motivated to develop a singlechip VSA system based on the ultrahigh-frequency FBAR. To improve the gas-sensing characteristics of this system, selfassembled poly(sodium 4-styrenesulfonate) (PSS)/poly(diallyldimethylammonium chloride) (PDDA) thin films are adopted as a gas-sensitive layer.36 Since the physical adsorption properties of this sensing film would be affected by the temperature, the temperature modulation is chosen to enable a variety of responses by a single sensor. However, the conventional FBAR is also sensitive to the temperature, which is evaluated by the temperature coefficient of frequency (TCF). For the sake of diminishing the TCF of FBARs, the silicon dioxide (SiO2) thin film with a positive temperature coefficient of velocity is introduced as a temperaturecompensated layer to balance the negative temperature coefficient of conventional FBAR. Thus, a temperaturecompensated FBAR is designed to reduce the effect of temperature fluctuation on the sensor. Although zero-temperature drift FBAR is the most ideal device for our work, it is difficult to fabricate such a device in practice. As a compromise, the low-temperature drift FBAR is selected as the core device of this VSA system so as to minimize the interference to the effective sensing signal caused by the high TCF of conventional FBAR as much as possible. For proof-of-concept validation purposes, a prototype temperature-modulated VSA based on the single-chip temperature compensated film bulk acoustic resonator (TC-FBAR) is designed and fabricated in this study. The temperature modulation is realized by adding a programmable heater under the FBAR chip. And the temperature-cycled operation (TCO)37 is employed to control the heater to make the VSA

■

EXPERIMENTAL SECTION

Reagents and Materials. PSS (Mw = 70 000) and PDDA (Mw < 10 000) were purchased from Sigma-Aldrich. The VOCs (ethanol, methanol, isopropyl alcohol, acetone, toluene, cyclohexane) tested in this work were purchased from Tianjin Yuanhua, and the purity of all VOCs reached high-performance liquid chromatography (HPLC) grade. All chemicals were used without any further purification. Device Fabrication. The TC-FBAR developed in this work was fabricated on a silicon substrate through a standard micro-electromechanical systems (MEMS) fabrication process (Figure S1). It comprised a temperature compensation layer and piezoelectric layer sandwiched between a bottom electrode and top electrode. In brief, an air cavity was initially etched on an n-type low-resistivity silicon substrate by deep reactive ion etching (DRIE) and was subsequently filled with phosphosilicate glass (PSG) as a sacrificial layer by chemical vapor deposition (CVD). Then, a 0.25 μm molybdenum (Mo) layer was sputtered and patterned to generate the bottom electrode. Next, a 0.07 μm silica was deposited and patterned as a temperature compensation layer. Furthermore, a 0.39 μm piezoelectric layer (AlN), a 0.32 μm top electrode (Mo), and a 0.19 um passivation layer (AlN) were sequentially deposited. After the top electrode was patterned, the piezoelectric layer was dry etched to expose targeting areas of the ground electrodes. Then, the 0.01 μm/ 0.1 μm Cr/Au layers were evaporated and patterned by lift-off process, serving as electrical connections and pads. Finally, the device was immersed in dilute hydrofluoric acid (HF) to completely etch the PSG in the cavity. Device Functionalization. In this work, we applied PSS and PDDA as VOC gas-sensitive materials. The 2.45 GHz NH2functionalized FBAR developed in this work was exposed to PSS solution for 1.5 min before it was rinsed with ultrapure water for 30 s.36 Similarly, the PSS-coated FBAR was immersed in PDDA solution with the same step, resulting in the first PSS/PDDA bilayers. Afterward, the above procedure was repeated, until 20-bilayer selfassembled PSS/PDDA thin films were formed on the device (Figure S2). This procedure is the result of optimization to obtain excellent sensing performance, because different nanostructures resulted in different sensitivities to VOCs in many experiments. The functionalized FBAR was stored in a nitrogen environment (e.g., glovebox) at room temperature to protect the self-assembled multilayers (SAMs) from oxidation damage and hydrolysis damage. The device can be stored for half of a year without notable degradation. 1525

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors

Figure 1. Schematic illustrating the FBAR sensor based on four different TCOs. (a) Scheme of the temperature-modulated FBAR gas sensor with its surface chemically functionalized with PSS and PDDA. The heater between the FBAR and evaluation boards heats the FBAR through the programmable DC power supply module, changing the temperature of the FBAR. (b) The four different TCOs and the temperature at which the device is heated at each TCO. Surface Characterization. The amino-silanization monolayer coating on the AlN substrate was characterized by contact angle (CA) measurements (JC2000DM). PSS/PDDA bilayers were characterized by atomic force microscopy (AFM, Veeco, Nano Scope) in tapping mode and are summarized in Figure S2. For CA measurement, after being exposed to air plasma, the surface of the AlN substrate became super hydrophilic (CA ≈ 7.1°). Moreover, after deposition of 3(aminopropyl) triethoxysilane (APTES), the CA became 72.2°, indicating that the amino group monolayer shows weak hydrophilicity. The successful functionalization of the amino group monolayer is related to the formation of the PSS/PDDA selfassembled multilayers. On the basis of the alternating exposure of charged substrates to PSS and PDDA solutions with oppositely charged polyanions and polycations, we were able to obtain selfassembled PSS/PDDA films by electrostatic actuation.36,38 Additionally, Figure S2 shows the morphologies with and without 20-bilayer PSS/PDDA self-assembled thin films. The roughness (Rq and Ra) without PSS/PDDA bilayers are 1.09 and 0.861 nm, and those with PSS/PDDA bilayers are 12.1 and 8.22 nm, respectively. Besides, the thickness of the thin film is 12.7 nm. VOC Detection System. The VOC detection setup (Figure S3) utilized in this work consisted of three parts: a device heating system, a VOC delivery system, and a VOC testing system. In the device heating system, a single-chip microcomputer (SCM, HC6800EM V2.2) controlled the programmable direct-current (DC) power supply module (D6015A, Ming He), which controlled the power of the heater wire-bonded to evaluation boards to adjust the temperature of the FBAR. In the dual-channel VOC delivery system, the VOC channel and the dilution channel were implemented to adjust the partial pressure of the VOCs. Saturated VOC vapors were produced from one channel by bubbling 99.99% pure carrier nitrogen (N2) gas into VOC liquid, while the other channel, namely, the dilution channel, carried pure N2 to adjust the gas partial pressures corresponding to different VOC concentrations by changing the ratio of the two channel-flow velocities via a mass flow controller (MFC, 5850e, Brooks). Experiments were conducted at six different concentrations in terms of P/P0 from 0.1 to 0.6, where P0 stands for the saturated vapor pressure at 25 °C and P stands for the partial pressure of the VOCs. In the VOC testing system, a functionalized FBAR was stuck to the heater, wire-bonded to evaluation boards, sealed in a glass chamber, and then connected to a computercontrolled vector network analyzer (VNA, E5071C, Agilent). Sensing data were simultaneously recorded by a MATLAB program.

FBAR, the TC-FBAR that we designed and fabricated comprises an additional thin temperature compensation layer (silica, SiO2) sandwiched between the piezoelectric layer and the bottom electrode. Because of the temperature compensation layer, the effect of temperatures on the frequency of FBARs is significantly reduced. The thickness of each layer in the TC-FBAR is decided through the finite element analysis. The two-dimensional model and the simulation results are shown in Figure S4. The pentagonal sensing area is defined by the top electrode with a passivation layer (AlN), which prevents the top electrode from oxidizing and corroding and functions as an interface for PSS/PDDA coatings. The heater attached between the FBAR and the evaluation board is used to control the working temperatures of the FBAR. Figure 1b presents the TCO used in this work at four different powers of 0, 0.1, 0.2, and 0.3 W, which correspond to four different temperatures. In practice, the power could be dynamically adjusted according to the difference between the target temperature and the ambient temperature to eliminate the influence of ambient temperature fluctuation. A thermal shock chamber (4300X-STREAM) was used to determine the TCF of the TC-FBAR. At the same time, the relationship between the temperature and the impedance was also determined. As shown in Figure S5, both the frequency and the impedance exhibit a linear response to the temperature. In addition, the TCF values of the bare FBAR and the FBAR coated with 20-bilayer self-assembled PSS/PDDA thin films were measured to be 2.8798 and 10.5306 ppm/°C, respectively. It suggests that the self-assembled PSS/PDDA thin films also have a positive temperature coefficient of velocity like the SiO2 thin films, which should be taken into consideration in the future device optimization to realize the low-temperature drift FBAR sensors. Principle of VOC Discrimination by a Single-Chip TCFBAR VSA. When the frequency of stimulating alternating current equals the intrinsic resonant frequency of the FBAR, the top and bottom electrodes of the resonator move almost purely up and down in the opposite direction with respect to each other, which is called the thickness-extensional vibration mode (TE-mode). The frequency of TE-mode is sensitive to an extra mass layer loading on the surface of the FBAR, which is quantitatively described by the Sauerbrey equation.39

■

RESULTS AND DISCUSSION Design of the Single-Chip TC-FBAR VSA. As shown in Figure 1a, the single-chip TC-FBAR VSA contains a functionalized TC-FBAR and a heater. In contrast to the conventional

Δf = −2f0 2 (Δm)/(A ρq ) 1526

(1) DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors

Figure 2. Frequency responses of the TC-FBAR in two TCO modes. (a) The TCO mode with constant power (0.1 W) in each cycle and the corresponding frequency shifts of the TC-FBAR. The frequency responses of the TC-FBAR to the TCO mode with constant power of 0.2 and 0.3 W are shown in Figure S6. (b) The TCO mode with different power in each cycle and the corresponding frequency shifts of the TC-FBAR per cycle. The power used in the first cycle is 0.1 W; in the second cycle it is 0.2 W, and in the third cycle it is 0.3 W. Then these three cycles are repeated with a period of 59 s.

Here, Δf is the measured frequency shift after adsorption of VOCs; f 0 is the intrinsic resonant frequency of the FBAR; Δm is the mass loaded; A is the effective sensing area; ρ is the density of the material; and q is the effective Young’s modulus of the resonator along the thickness direction of acoustic wave propagation. This equation manifests that the resonant frequency of the FBAR would decrease linearly with the mass loading due to physical adsorption of VOCs. Furthermore, according to the Sauerbrey equation, the sensitivity (Δf/Δm) is directly proportional to the square of f 0, which suggests that a higher working resonance frequency will produce a greater frequency shift and higher sensitivity with the same mass loaded on the device surface. Clearly, the sensitivity of the ultrahigh-frequency FBAR is orders of magnitude higher than that of the QCM and SAW devices. In addition, the adsorbed VOC molecules in the sensing film would consume part of the resonator’s energy due to the perturbation of the propagation properties of the thickness extensional wave mode in the FBAR, which results in the impedance change of the FBAR. Another necessary condition to realize VOC discrimination is the temperature (characterized by the power of the heater), which causes different adsorption properties of VOCs on the sensing film. At the same temperature, the adsorptions of different VOC molecules are not proportional due to their different affinity for the chemically modified FBAR surface. In different temperature modes, the adsorption of the same VOC molecule is also not proportional due to the different affinity affected by the temperature. Therefore, these two adsorption effects make the single-chip TC-FBAR equivalent to a sensor array, providing insight into the possibility of discriminating VOCs. Thus, the mass load theorem of the FBAR, together with the different temperature effects on the adsorption of VOC

molecules, forms the principle for the discrimination of VOCs with the individual FBAR sensor. Temperature Cycled Operation of the FBAR. The temperature modulation for our proposed VSA is realized by the temperature-cycled operation. It is a very flexible method to adjust the temperature by changing the applied power or the cycle time. A mesh heater wire-bonded to evaluation boards is sandwiched between the FBAR and evaluation boards, which can quickly raise the temperature through the programmable DC power supply module controlled by the single-chip microcomputer. There are two TCO modes to heat the TCFBAR. In the first TCO mode, the applied power in each cycle is constant, as shown in Figure 2a. The corresponding frequency shift reaches the maximum value for every 3 s of heating, and the frequency shift returns to the original value every time it is not heated for 10 s. According to the frequency shift and the TCF value of our device, the change of the temperature is calculated to be 15 °C. Similarly, when the power is 0.2 and 0.3 W, the temperature increases by 35 and 70 °C, respectively. In other words, the working temperatures of this VSA do not exceed 100 °C, which ensures that the sensor can be integrated into electronic products such as mobile phones without causing harm to them. In the second TCO mode, each heating period contains three different power cycles, as depicted in Figure 2b. We found that the frequency shift at each power cycle is equal to that in the first TCO mode with the same power, which suggests both TCO modes could achieve the same temperature-control effect. However, a series of temperatures could be obtained in a heating period by the second TCO mode, which is more convenient in practical applications. Furthermore, we can see that the times to reach temperature stability and heat dissipation time increase with the power. At 0.1 W, both of these times are relatively fast, 3 and 10 s, respectively. At 0.2 W, these times are 5 and 15 s, respectively. Finally, at 0.3 W, these times are 8 and 18 s, 1527

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors

Figure 3. Real-time sensing characteristics in static detection mode. (a) Real-time frequency shifts and (b) real-time impedance responses of the FBAR upon exposure to six different VOC vapors at six different gas partial pressures (p/p0) from 0.1 to 0.6. (c) Adsorption isotherms for the frequency shift and (d) impedance shift of six different VOC vapors. The dots represent the measured data, and the solid lines represent the results obtained by fitting the Langmuir equation to the data.

Figure 4. Real-time sensing characteristics in dynamic detection modes corresponding to the first TCO mode. (a) Adsorption isotherms for the frequency shift and (b) impedance shift of six different VOC vapors at the power of 0.1 W. (c) The frequency shift and (d) the impedance shift histogram of ethanol vapor at six different concentrations for different powers used in the TCO.

flushed with pure nitrogen at beginning to reach a stable baseline, followed by six sensing cycles with increasing concentrations of VOCs. Each sensing cycle consisted of VOC adsorption and desorption processes. Figure 3a,b shows the real-time frequency shifts and impedance responses of the FBAR sensor functionalized with 20-bilayer self-assembled PSS/PDDA thin films upon exposure to methanol, ethanol, acetone, isopropyl alcohol, cyclohexane, and toluene vapors at six different concentrations at room temperature (the real-time detection results not processed by MATLAB for different

respectively. From the above results, the maximum and initial values for each power cycle are close to each other, which indicates that the frequency response of TC-FBAR to the temperature is stable, when the ambient temperature does not change much. Real-Time VOC Static Detection by the FBAR Multiparameter VSA. We define the detection process at room temperature as static detection; in other words, static detection means that the heating power is always 0 W. Before VOC injection, the single TC-FBAR sensor in the glass chamber was 1528

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors Table 1. Limit of Detection (LOD) and Sensitivity of Six Different VOCs at Different TCO Powers P (W)

0

0.1

0.2

0.3

VOCs

LOD (ppm)

S (kHz/ppm)

LOD (ppm)

S (kHz/ppm)

LOD (ppm)

S (kHz/ppm)

LOD (ppm)

S (kHz/ppm)

acetone ethanol cyclohexane isopropanol methanol toluene

40 40 40 40 40 40

0.050 45 0.1195 0.002 0.047 97 0.1305 0.003 05

60 60 60 60 60 60

0.047 02 0.11 0.002 01 0.045 01 0.120 03 0.003 04

100 100 100 100 100 100

0.037 03 0.104 01 0.002 01 0.032 99 0.108 01 0.001 79

180 180 180 180 180 180

0.032 02 0.098 37 0.0019 0.031 04 0.103 03 0.001 71

different temperatures, indicating that four different temperatures make the single-chip FBAR senor correspond to a virtual sensor array consisting of four different sensors. This principle is the key to temperature modulation. For the second dynamic detection mode, the real-time detection results are shown in Figure S12. Obviously, the total working time for the second mode is three times shorter than that for the first mode, which can remarkably shorten the working time and reduce the power consumption. To obtain more data for statistical analysis, all the above experiments were repeated three times at each temperature. The sensing data of six different VOC vapors at 0, 0.2, and 0.3 W are shown in Tables S2−S25. Relative standard deviations of less than 4% were achieved, which indicated that the FBAR multiparameter VSA has good reproducibility and high accuracy at each temperature. To investigate the limit of detection (LOD) of the FBAR at different temperatures, low-concentration VOCs were injected into the chamber of VSA to get the frequency and impedance responses. The VOC at lower concentrations ranging from 40 to 260 ppm was produced by a commercial vapor generator system (MF-3D, NIM). The linear relationship between the concentration and the frequency change for these VOCs in each temperature is obtained in Figure S14. According to Figure S14, the LOD and the sensitivity of six different VOCs at different temperatures were calculated as shown in Table 1. Adsorption Isotherms of VOCs in Static and Dynamic Modes. On the basis of the frequency and impedance shifts at different gas partial pressures, adsorption isotherm of each VOC vapor at room temperature can be obtained,41 as shown in Figure 3c,d. Adsorption isotherms of the six VOC vapors on different temperature modulation profiles are shown in Figure S10. According to the shape of the curve, the gas−solid interaction of VOCs on the PSS/PDDA assembled bilayers is monolayer adsorption. All adsorption isotherms can be fitted well with the Langmuir equation,40 which is the typical mode of monolayer gas physisorption.

VOCs are shown in Figure S8). In the adsorption process, negative frequency shifts and impedance shifts of FBAR were observed due to the quick molecular adsorption on the surface of the sensor. When the gas flow changed from VOCs to N2, positive frequency shifts and impedance shifts were observed due to molecular desorption. Additionally, as the gas partial pressure increased, the amount of absorbed VOCs gradually increased. The adsorption isotherms of the six different VOC vapors extracted from the frequency and impedance responses are, respectively, drawn in Figure 3c,d. We can see that the adsorptions of different VOC molecules are quite different at the same concentration. Real-Time VOC Dynamic Detection by the FBAR Multiparameter VSA. As shown in Figure 2, we define the detection process under the regular pulse mode of TCO as dynamic detection. There are two different dynamic detection modes corresponding to two TCO modes. Both modes can achieve the discrimination of different VOC gases, but the second is more convenient and simpler to operate. For a specific VOC detection, the first detection mode needs four times detection at different powers of TCO, while the second detection mode only needs once detection. The details of realtime detection results under these two detection modes are compared in Figure S7. As you can see from the figure, four sets of data at different temperatures can be obtained at once under the second detection mode. Since our VOC delivery system has a fixed period to generate different gas partial pressures, the second detection mode could save more time and power. Here, the results from the first dynamic detection mode are used to illustrate how to realize the discrimination of VOCs with this VSA. Through the data processing method shown in Figure S7, we can extract the frequency shift and impedance change at six different gas partial pressures under the different TCO powers. Figure 4a,b presents the adsorption isotherms for the frequency shift and impedance change of six different VOC vapors at the power of 0.1 W. The real-time frequency and impedance responses of the FBAR sensor upon exposure to six different vapors at six different concentrations at TCO with the power of 0.1, 0.2, and 0.3 W are shown in Figure S9. The histogram of the frequency shift and impedance change at different TCO powers for the ethanol vapor are shown in Figure 4c,d (the results for other vapors are shown in Figure S11). Different frequency shifts and impedance shifts of the FBAR were observed, because the temperature affects the adsorption and desorption of gas molecules. In addition, we can see that the adsorption amount of the same VOC at the same concentration is different at different temperatures, because increasing the temperature within a certain range would inhibit the adsorption of VOC vapors and promote the desorption of VOC vapors. Additionally, by comparing Figure 4c,d and Figure S11, it is shown that the frequency and impedance responses of the VOCs are nonlinear at the

v = kb(p /p0 )/[1 + b(p /p0 )]

(2)

Here, v is the frequency shift or impedance change of an FBAR sensor, which is linearly proportional to the total number of adsorbed gas molecules, k is the monolayer molecular volume adsorbed per unit surface area, and b is the affinity constant. Adsorption isotherms of the six VOC vapors based on different temperature modulation profiles were fitted using the same equation. This fitting reveals a two-step adsorption process. In the low-concentration range (p/p0 below 0.5), the number of adsorbed gas molecules increased quickly with increasing gas concentration, while in the second process, the adsorbed molecules increased slowly. This difference may be because the adsorption capacity of the surface of the selfassembled film is close to saturation at higher concentrations. 1529

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors

Figure 5. Fitting results of adsorption isotherms for different VOCs at different TCO powers. Histograms of (a) constant k and (b) constant b by fitting the frequency shift adsorption isotherms. Histograms of (c) constant k and (d) constant b by fitting the impedance shift adsorption isotherms.

Figure 6. Discrimination of VOCs using PCA and LDA. (a) The PCA plot and (b) the LDA plot for six different VOCs at six gas partial pressures under the static detection and the first type of dynamic detection. (c) The PCA plot and (d) the LDA plot for six different VOCs at six gas partial pressures under the second type of dynamic detection.

During the fitting, two concentration-independent constants k and b (listed in Table S1) were obtained; these constants are intimately connected to the properties of interactions between the PSS/PDDA assembled bilayers and different VOCs. Figure 5 shows the fitting results of adsorption isotherms based on different TCO powers, which show that k and b can be used as two parameters for the discrimination of VOCs. It reveals that each VOC vapor has a different k and b for frequency shift fitting and impedance shift fitting at different TCO powers, which indicates that k and b can be affected by temperature

modulation to affect the adsorptions of different VOCs. Additionally, as the temperature increases, the PSS/PDDA self-assembled film gradually decreases the monolayer molecular volume (k) while gradually increasing the affinity constant (b), which may be due to the combination of the physical properties of the PSS/PDDA self-assembled film itself and the kinetic energy of the VOCs. In summary, it is clear that VOC discrimination can be realized with this proposed VSA. Discrimination of VOCs by Single-Chip TC-FBAR Multiparameter VSA. To assess the capability of the 1530

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors

mode is preferred due to its advantages on the time and power consumption. The proposed single-chip TC-FBAR VSA based on temperature modulation provides a simple mass-based electronic method to detect VOC vapors. With the TCO to realize the temperature modulation, it is possible to reach a stable working temperature without being affected by the fluctuation of ambient temperature. Moreover, owing to the low heating temperature, high sensitivity, miniaturized size, and ultrahigh operating frequency, the single-chip FBAR VSA has the potential to be integrated into electronics such as mobile phones. We believe that this single-chip TC-FBAR VSA would represent a novel generation of e-nose systems for VOC detection and discrimination.

single-chip FBAR VSA based on temperature modulation to discriminate the six different VOCs, principal component analysis (PCA) and linear discriminant analysis (LDA) were employed for multivariate statistical analysis. We performed PCA and LDA on the primary matrix, which is composed of frequency shifts and impedance changes with 36 rows (representing six partial pressures for six different VOC samples) and 8 columns (including four frequency shifts and four impedance changes under four different temperatures). It is easy to identify that each VOC sample is well-classified by a quick visual assessment of PCA and LDA plots as depicted in Figure 6a,b. From the PCA results, the cyclohexane and toluene cannot be classified. From the LDA results, almost all the analytes can be separated completely. To make the application of sensors to the discrimination of VOCs more convenient, faster, and less power-consuming, different VOCs can be discriminated by the second type of dynamic detection developed in our work. Figure 6c,d presents PCA and LDA plots for discriminating methanol, ethanol, acetone, isopropyl alcohol, toluene, and cyclohexane vapors by using the data from the second type of dynamic detection. The results are similar to that from the first type of dynamic detection, indicating that the second dynamic detection method is also reliable. We use the same VSA to independently detect six different VOCs at a concentration from 0.1 to 0.6 p/p0 for three times at each temperature under two TCO modes. The PCA and LDA results obtained from the other two sets of data under two TCO modes are shown in Figure S13. Through statistical analysis, it could be concluded that the single-chip FBAR VSA was able to distinguish successfully these six different VOCs, and the correct discrimination rate of each VOC sample by our method is higher than 97%.

■

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssensors.8b01678. The fabrication process of the TC-FBAR; device functionalization and surface characterization; experimental setup; the finite element simulation of the TCFBAR; the frequency and impedance responses of the TC-FBAR to the temperature; the frequency shifts of the device under the TCO with constant power; the schematic diagram of data-processing for two dynamic detection modes; real-time static and dynamic detection results at different temperatures; static and dynamic adsorption isotherms for six different VOCs; the PCA and LDA results; sensitivity analysis for the TC-FBAR; reproducibility study of the proposed VSA (PDF)

■

■

CONCLUSION In this work, we developed a novel single-chip e-nose system based on a TC-FBAR functionalized with 20-bilayer selfassembled PSS/PDDA thin films. By optimizing the number of bilayers of PSS/PDDA thin films, we found that 20 bilayers are ideal for improving VOC molecule absorption efficiency. Six different concentrations of VOCs (methanol, ethanol, acetone, isopropyl alcohol, toluene, and cyclohexane) under the original conditions were selected to research the ability of this individual sensor VSA to distinguish VOCs. The different frequency and impedance responses to the different adsorption of different VOCs under different temperatures are responsible for its capability to discriminate VOCs. Two concentrationindependent constants (k, b) obtained by fitting the data with the Langmuir equation reveal why temperature modulation affects the adsorption and desorption of different VOCs on the sensor surface. To our knowledge, this experiment is the first to demonstrate that a microfabricated single-chip TC-FBAR VSA based on temperature modulation can be used as a highthroughput sensor to quantify the interactions between gas molecules and PSS/PDDA bilayers. The static detection and two types of dynamic detections were used to directly measure frequency shifts and impedance responses of the TC-FBAR to six different VOCs. After parameters from the adsorption isotherms were extracted, the PCA and LDA were performed on the corresponding primary matrix to reduce the dimensionality of the raw data, which allows the visualization of relations between the VOC samples. Since all VOC samples can be discriminated with more than 97% accuracy under two types of dynamic detections, the second dynamic detection

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. (Q-r.Y.) *E-mail: [email protected]. (W.P.) ORCID

Guang Zeng: 0000-0003-4109-9580 Menglun Zhang: 0000-0002-5174-7812 Jiuyan Li: 0000-0002-3979-5459 Xuexin Duan: 0000-0002-7550-3951 Qingrui Yang: 0000-0003-0463-8549 Author Contributions ∥

These authors contributed equally.

Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (NSFC Nos. 61674114, 91743110, and 21861132001), National Key R&D Program of China (2017YFF0204600), Tianjin Applied Basic Research and Advanced Technology (17JCJQJC43600), the Foundation for Talent Scientists of Nanchang Institute for Microtechnology of Tianjin University, and the 111 Project (B07014) .

■

REFERENCES

(1) Hakim, M.; Broza, Y. Y.; Barash, O.; Peled, N.; Phillips, M.; Amann, A.; Haick, H. Volatile Organic Compounds of Lung Cancer

1531

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors and Possible Biochemical Pathways. Chem. Rev. 2012, 112 (11), 5949−5966. (2) Adiguzel, Y.; Kulah, H. Breath Sensors for Lung Cancer Diagnosis. Biosens. Bioelectron. 2015, 65, 121−138. (3) Suematsu, K.; Harano, W.; Oyama, T.; Shin, Y.; Watanabe, K.; Shimanoe, K. Anal. Chem. 2018, 90, 11219. (4) Paska, Y.; Stelzner, T.; Assad, O.; Tisch, U.; Christiansen, S.; Haick, H. Molecular Gating of Silicon Nanowire Field-Effect Transistors with Nonpolar Analytes. ACS Nano 2012, 6 (1), 1−3. (5) Lichtenstein, A.; Havivi, E.; Shacham, R.; Hahamy, E.; Leibovich, R.; Pevzner, A.; Krivitsky, V.; Davivi, G.; Presman, I.; Elnathan, R.; et al. Supersensitive Fingerprinting of Explosives by Chemically Modified Nanosensors Arrays. Nat. Commun. 2014, 5 (1), 1−12. (6) Wang, B.; Haick, H. Effect of Chain Length on the Sensing of Volatile Organic Compounds by Means of Silicon Nanowires. ACS Appl. Mater. Interfaces 2013, 5 (12), 5748−5756. (7) Konvalina, G.; Haick, H. Sensors for Breath Testing: From Nanomaterials to Comprehensive Disease Detection. Acc. Chem. Res. 2014, 47 (1), 66−76. (8) Persaud, K.; Dodd, G. Analysis of Discrimination Mechanisms in the Mammalian Olfactory System Using a Model Nose. Nature 1982, 299 (5881), 352−355. (9) Röck, F.; Barsan, N.; Weimar, U. Electronic Nose: Current Status and Future Trends. Chem. Rev. 2008, 108 (2), 705−725. (10) Gardner, J. W.; Bartlett, P. N. A Brief History of Electronic Noses. Sens. Actuators, B 1994, 19, 18−19. (11) Rehman, A.; Hamilton, A.; Chung, A.; Baker, G. A.; Wang, Z.; Zeng, X. Differential Solute Gas Response in Ionic-Liquid-Based QCM Arrays: Elucidating Design Factors Responsible for Discriminative Explosive Gas Sensing. Anal. Chem. 2011, 83 (20), 7823− 7833. (12) Wang, B.; Cancilla, J. C.; Torrecilla, J. S.; Haick, H. Artificial Sensing Intelligence with Silicon Nanowires for Ultraselective Detection in the Gas Phase. Nano Lett. 2014, No. No. 10, 1−13, DOI: 10.1021/nl404335p. (13) Lange, D.; Hagleitner, C.; Hierlemann, A.; Brand, O.; Baltes, H. Complementary Metal Oxide Semiconductor Cantilever Arrays on a Single Chip: Mass-Sensitive Detection of Volatile Organic Compounds. Anal. Chem. 2002, 74 (13), 3084−3095. (14) Kolmakov, A.; Klenov, D. O.; Lilach, Y.; Stemmer, S.; Moskovits, M. Enhanced Gas Sensing by Individual SnO2 Nanowires and Nanobelts Functionalized with Pd Catalyst Particles. Nano Lett. 2005, 5 (4), 667−673. (15) Lao, C.; Li, Y.; Wong, C. P.; Wang, Z. L. Enhancing the Electrical and Optoelectronic Performance of Nanobelt Devices by Molecular Surface Functionalization. Nano Lett. 2007, 7 (5), 1323− 1328. (16) Star, A.; Han, T. R.; Joshi, V.; Gabriel, J. C. P.; Grüner, G. Nanoelectronic Carbon Dioxide Sensors. Adv. Mater. 2004, 16 (22), 2049−2052. (17) Yamamoto, M. Surface Plasmon Resonance (SPR) Theory: Tutorial. Rev. Polarogr. 2008, 48, 1−32. (18) Schutze, A.; Gramm, A.; Ruhl, T. 39. 3: Identification of Organic Solvents by a Virtual Multisensor System with Hierarchical Classification. Ieee 2002, 4 (6), 382−387. (19) Baumbach, M.; et al.Preparation of Microstructured Pellistors and Their Application for Fast Fuel Vapor Discrimination. 17th IEEE International Conference on Micro Electro Mechanical Systems. Maastricht MEMS 2004 Technical Digest; IEEE, 2004; pp 268−271 DOI: 10.1109/MEMS.2004.1290574. (20) Speller, N. C.; Siraj, N.; Vaughan, S.; Speller, L. N.; Warner, I. M. QCM Virtual Multisensor Array for Fuel Discrimination and Detection of Gasoline Adulteration. Fuel 2017, 199, 38−46. (21) Ankara, Z.; Kammerer, T.; Gramm, A.; Schütze, A. Low Power Virtual Sensor Array Based on a Micromachined Gas Sensor for Fast Discrimination between H2, CO and Relative Humidity. Sens. Actuators, B 2004, 100 (1−2), 240−245.

(22) Tang, N.; Jiang, Y.; Qu, H.; Duan, X. Graphene Oxide Doped Conducting Polymer Nanowires Fabricated by Soft Lithography for Gas Sensing Applications. IEEE Sens. J. 2018, 18, 1748. (23) Larkin, J. E.; Frank, B. C.; Gavras, H.; Sultana, R.; Quackenbush, J. Independence and Reproducibility across Microarry Platforms. Nat. Methods 2005, 2 (5), 337−343. (24) Speller, N. C.; Siraj, N.; Regmi, B. P.; Marzoughi, H.; Neal, C.; Warner, I. M. Rational Design of QCM-D Virtual Sensor Arrays Based on Film Thickness, Viscoelasticity, and Harmonics for Vapor Discrimination. Anal. Chem. 2015, 87 (10), 5156−5166. (25) Potyrailo, R. A.; Bonam, R. K.; Hartley, J. G.; Starkey, T. A.; Vukusic, P.; Vasudev, M.; Bunning, T.; Naik, R. R.; Tang, Z.; Palacios, M. A.; et al. Towards Outperforming Conventional Sensor Arrays with Fabricated Individual Photonic Vapour Sensors Inspired by Morpho Butterflies. Nat. Commun. 2015, 6, 1−12. (26) Potyrailo, R. A.; Starkey, T. A.; Vukusic, P.; Ghiradella, H.; Vasudev, M.; Bunning, T.; Naik, R. R.; Tang, Z.; Larsen, M.; Deng, T.; et al. Discovery of the Surface Polarity Gradient on Iridescent Morpho Butterfly Scales Reveals a Mechanism of Their Selective Vapor Response. Proc. Natl. Acad. Sci. U. S. A. 2013, 110 (39), 15567−15572. (27) Potyrailo, R. A.; Ghiradella, H.; Vertiatchikh, A.; Dovidenko, K.; Cournoyer, J. R.; Olson, E. Morpho Butterfly Wing Scales Demonstrate Highly Selective Vapour Response. Nat. Photonics 2007, 1 (2), 123−128. (28) Regmi, B. P.; Speller, N. C.; Anderson, M. J.; Brutus, J. O.; Merid, Y.; Das, S.; El-Zahab, B.; Hayes, D. J.; Murray, K. K.; Warner, I. M. Molecular Weight Sensing Properties of Ionic Liquid-Polymer Composite Films: Theory and Experiment. J. Mater. Chem. C 2014, 2 (24), 4867−4878. (29) Regmi, B. P.; Monk, J.; El-Zahab, B.; Das, S.; Hung, F. R.; Hayes, D. J.; Warner, I. M. A Novel Composite Film for Detection and Molecular Weight Determination of Organic Vapors. J. Mater. Chem. 2012, 22 (27), 13732−13741. (30) Ding, B.; Kim, J.; Miyazaki, Y.; Shiratori, S. Electrospun Nanofibrous Membranes Coated Quartz Crystal Microbalance as Gas Sensor for NH3detection. Sens. Actuators, B 2004, 101 (3), 373−380. (31) Liang, C.; Yuan, C. Y.; Warmack, R. J.; Barnes, C. E.; Dai, S. Ionic Liquids: A New Class of Sensing Materials for Detection of Organic Vapors Based on the Use of a Quartz Crystal Microbalance. Anal. Chem. 2002, 74 (9), 2172−2176. (32) Bur, C.; Reimann, P.; Andersson, M.; Lloyd Spetz, A.; Schütze, A. New Method for Selectivity Enhancement of SiC Field Effect Gas Sensors for Quantification of NOx. Microsyst. Technol. 2012, 18 (7− 8), 1015−1025. (33) Bur, C.; Bastuck, M.; Puglisi, D.; Schütze, A.; Spetz, A. L.; Andersson, M. Discrimination and Quantification of Volatile Organic Compounds in the Ppb-Range with Gas Sensitive SiC-Field Effect Transistors. Procedia Eng. 2014, 87 (9), 604−607. (34) Lu, Y.; Chang, Y.; Tang, N.; Qu, H.; Liu, J.; Pang, W.; Zhang, H.; Zhang, D.; Duan, X. Detection of Volatile Organic Compounds Using Microfabricated Resonator Array Functionalized with Supramolecular Monolayers. ACS Appl. Mater. Interfaces 2015, 7 (32), 17893−17903. (35) Chang, Y.; Tang, N.; Qu, H.; Liu, J.; Zhang, D.; Zhang, H.; Pang, W.; Duan, X. Detection of Volatile Organic Compounds by Self-Assembled Monolayer Coated Sensor Array with ConcentrationIndependent Fingerprints. Sci. Rep. 2016, 6, 1−12. (36) Liu, W.; Qu, H.; Hu, J.; Pang, W.; Zhang, H.; Duan, X. A Highly Sensitive Humidity Sensor Based on Ultrahigh-Frequency Microelectromechanical Resonator Coated with Nano-Assembled Polyelectrolyte Thin Films. Micromachines 2017, 8 (4), 1 DOI: 10.3390/mi8060178. (37) Bur, C.; Bastuck, M.; Andersson, M.; Schütze, A.; Spetz, A. L. Influence of a Changing Gate Bias on the Sensing Properties of SiC Field Effect Gas Sensors. 14th Int. Meet. Chem. Sensors - IMCS 2012 2012, 140−143. (38) Decher, G. Fuzzy Nanoassemblies: Toward Layered Polymeric Multicomposites. Science 1997, 277 (5330), 1232−1237. 1532

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533

Article

ACS Sensors (39) Zhao, Y.; Yang, Q.; Chang, Y.; Qu, H.; Pang, W.; Zhang, H.; Duan, X. Detection and Discrimination of Volatile Organic Compounds Using a Single Multi-Resonance Mode Piezotransduced Silicon Bulk Acoustic Wave Resonator (PSBAR) as Virtual Sensor Array. Sens. Actuators, B 2018, 254, 1191−1199. (40) Zhang, C.; Kaluvan, S.; Zhang, H.; Wang, G.; Zuo, L. A Study on the Langmuir Adsorption for Quartz Crystal Resonator Based Low Pres-sure CO 2 Gas Sensor. Measurement 2018, 124 (April), 286− 290. (41) Zhang, H.; Wang, J.; Ye, S.; Chang, M. Application of Electronic Nose and Statistical Analysis to Predict Quality Indices of Peach. Food Bioprocess Technol. 2012, 5 (1), 65−72.

1533

DOI: 10.1021/acssensors.8b01678 ACS Sens. 2019, 4, 1524−1533