[ieee 2014 37th isse international spring seminar in electronics technology (isse) - dresden,...

978-1-4799-4455-2/14/$31.00 ©2014 IEEE 427 37th Int. Spring Seminar on Electronics Technology

Optimal Parameters Determination for Nanostructure–Enhanced Surface Acoustic Waves Sensor

Oleksandr Bogdan1), Anatolii Orlov2), Gennady Pashkevich1), Veronika Ulianova2), Yurii Yakimenko2), Andrii Zazerin2)

1) Scientific and Research Institute of Applied Electronics, National Technical University of Ukraine «Kyiv Polytechnic Institute», Kyiv, Ukraine

2) Department of Microelectronics, National Technical University of Ukraine «Kyiv Polytechnic Institute», Ukraine [email protected]

Abstract: Various modifications of the ZnO nanostructures based sensitive element for the two-port surface acoustic wave sensor (SAW) design were considered. The influence of morphometric parameters (diameter and length) of ZnO nanostructures on output SAW sensor characteristics was investigated by finite element simulation method. Obtained versatile flexible multiparameter model allowed the evaluation of performance parameters. The optimal parameters for nanostructure-enhanced SAW sensor design could be estimated by the proposed approach.

1. INTRODUCTION

Nowadays acoustic wave devices are widely applied in many industrial and scientific fields ranging from mobile devices and wireless communication, pressure and viscosity sensors to novel biosensors for DNA detection. Major advantages of surface acoustic wave (SAW) sensors include: single sided planar structure, ability to interact directly with the sensing medium, high sensitivity, low hysteresis, small size, direct frequency output signal and low power consumption. Addition of mass affects not only frequency but also phase and magnitude. This feature provides more precise measurement of analyte concentration.

Investigation of novel sensitive materials, their synthesis methods for advanced sensors is an actual problem and continuously carried out [1]. Among complicated and expensive traditional fabrication techniques such low-temperature synthesis methods as hydrothermal technique is suitable for nanostructures synthesis almost on any substrates include single-crystal [2]. ZnO nanorods have been employed as bio- or gas sensitive element of SAW sensors strongly influencing on both acoustic and electric impedance of SAW structure, due to giant effective surface area and strong bonding sites and this way allows enhancing of sensitivity of such devices [3].

The analytical modeling of the plane harmonic surface wave propagation process in an isotropic elastic half-space with rod nanostructures on a surface (Fig. 1, a) for determining of the propagation velocity of surface waves at given geometric parameters of the rod nanostructures is presented in [4]. This model simplifies the development of ZnO nanorods SAW sensors and analysis of the results. The simulation of ZnO nanowire (Fig. 1, b) based gas sensor in COMSOL Multiphysics software platform is presented in [5]. Different thicknesses of ZnO intermediate layer show different sensing performance after being exposed to H2 gas.

a b

Fig. 1. SAW sensor models with nanowires as the sensing material.

This research is devoted to the determination of influence of the nanostructures’ morphometric parameters (diameter and length) on SAW sensor


characteristics with finite element modeling (FEM). The approach to estimate the optimal parameters for nanostructure-enhanced SAW sensor design is described.

2. MODEL CONSIDERATION FOR A SAW SENSOR

To provide the FEM simulation the structure of two port SAW resonator was chosen as basic structure of the gas sensor (Fig. 2). Thus, two interdigital transducers were formed on the piezoelectric substrate; between them ZnO nanorods as sensing element were placed to increase effective surface area.

Fig. 2. Schematic representation of a two port SAW sensor.

The dimension of the piezoelectric substrate was 320 μm in the X axis and 90 μm in the Y axis. The period and aperture of IDTs allowed resonance at the frequency of 120 MHz [6]. The distance between IDTs was chosen as 4 half-period of the IDT to form required sensing element and provide the SAW propagation. Lithium niobate (LiNbO3 128° XY) was chosen as substrate material and aluminium (Al) was used as electrodes material. On the top of the structure the air block was placed.

The SAW substrate was simulated using frequency domain analysis in 2D plain strain assumption. The proper boundary conditions were applied. Periodic boundary conditions were applied to both vertical edges of the substrate to model the continuous Rayleigh wave propagation at the boundaries of the structure. The top surface of the substrate was assumed stress free and the bottom boundary of the piezoelectric layer was zero charged. The specific perfectly matched layer was added at the bottom of the substrate to provide Rayleigh damping properties and to avoid reflection of the waves from the bottom edge. Such conditions prevented the appearance of parasitic perturbations and thus spurious thickness resonances, which degrade the sensing performance of the structure. The fixed property was applied to the bottom boundary of this layer to simulate the finite thickness of the substrate and its stiffness behavior.

The displacement in the lateral direction was constrained to zero. Thus, the periodic electrical potential of 5 V was applied to even fingers of input and output IDTs while ground terminal was applied to odd ones to generate the electro-magnetic perturbations.

The figure 3 was obtained in MEMS module of COMSOL Multiphysics software platform and shows periodic stress concentrations on the LiNbO3 128° XY surface substrate with IDTs demonstrating the eigenmode SAW generation at 120 MHz. In this case the thickness displacements are effectively damped and are practically unnoticeable.

Fig. 3. The scaled total displacement surface of simulated SAW resonator at 120 MHz.

The performance of of such structures was analyzed using the input impedance characteristics and input impedance phase (Fig. 4).

a b

Fig. 4. Input impedance (a) and phase (b) versus frequency of simulated SAW resonator.

The input impedance has two distinctive peaks defining the resonant properties of the structure: the series resonance where the impedance is minimum and parallel resonant frequency where the impedance is maximum. The absence of spurious resonances and phase response smoothness became the results of properly designed geometry and correctly specified model definitions.

Additional simulations showed the increasing of signal damping with gap length extending. This leads


to sensing area gap length optimization to provide both high sensitivity (due to larger effective surface) and signal power with noise immunity.

The presented characteristics demonstrated the model suitability for sensor parameters determination.

3. SENSING AREA INPUT VARIABLES DETERMINATION

To estimate the input parameters of nanostructures modified sensing area of SAW sensor and limit of its variations the ZnO nanorods were synthesized by nanotechnological approach "bottom-up" which provides the formation of nanostructures with different morphologies and structures by self-organization at the low-temperature chemical processes without expensive vacuum and other microelectronic technologies at different conditions. Process parameters of chemical methods materials synthesis, substrate preconditioning and seed-layer growth significantly affect the quality and the shape of the obtained structures.

Two groups of samples were prepared. For both groups LiNbO3 128° XY with seed-layer formed by sol-gel method was used as the substrate. Zinc acetate dihydrate with the concentration of 0.3 mol/l dissolved in isopropanol and added monoethanolamine were used for the preparation of sol-gel. The mixture was stirred by a magnetic agitator at 65°C until the clear and homogeneous solution was formed. Spin coating of the sol-gel on cleaned substrate at 3000 rpm for 30 s was carried out. After the deposition of the fifth layer, the resulting thin films were annealed at 400°C in air for 1 h to obtain the homogeneous and stable seed-layer. The seed layer deposition was carried out to provide the growing centers and bonding interface with substrates.

The preparation of the first group of samples was carried out in zinc nitrate based solution with the concentration of 0.05 mol/l at 95°C during 120 min. ZnO nanorods synthesis from the second group was carried out in zinc acetate with the concentration of 0.3 mol/l based solution at 90°C during 90 min.

Scanning electron microscope SEM (Hitachi S4800) was used to define morphometric characteristics of the nanostructures. The top-view SEM images of the synthesized ZnO nanorods on LiNbO3 substrate were obtained (Fig. 5, 6).

From SEM images it could be noticed that the patterns demonstrated good regularity overall observed surface. From the observations, the diameter of ZnO nanorods from the first group is 35-65 nm and about 70 nm for nanorods from the second group. The density of nanorods is about 100 µm-2 and 150 µm-2 for the first and second group respectively.

Fig. 5. SEM images of the ZnO nanorods from the first group.

Fig. 6. SEM images of the ZnO nanorods from the second group.

It is promising to modify the sensing element of the SAW sensor with ZnO nanostructures with certain parameters which could be matched by the process temperature, growing time, solution concentration and composition.

4. INFLUENCE OF ZNO NANORODS’ MORPHOMETRIC PARAMETERS ON SENSOR CHARACTERISTICS

Absorption of gas molecules onto the sensing layer between IDTs causes changes in the propagation velocity and attenuation of the surface acoustic wave. These changes can be detected with great accuracy by a SAW device as a frequency shift [7].


The application of ZnO nanorods as sensing layers could improve sensing performance due to increased surface area. To study the influence of nanorods’ morphometric parameters on such sensor characteristics as mass responsivity and mass responsivity per area we used the morphometric parameters of synthesized rods and described FEM model.

The mass loading causes frequency shifts, depends on the effective surface area of the sensitive material S and the concentration of the analyte per square c. For consideration of such nanorods’ parameters as radius R, height h, amount in sensing area N, mass loading Δm can be calculated as:

πΔm= S c = 2 RhN +4aw (1)

where: a – is IDT half-period and w – is aperture. The simulation was carried out in unperturbed mode and under analyte introduction (50 ng/mm2). The condition of added mass was applied on area between IDTs. Input parameters and obtained results are presented in the table 1.

Table 1. Input parameters and obtained sensor characteristics.

Parameter Sample 1 Sample 2

Concentration of analyte, 50 ng/mm2

50 50

Radius of rods, nm 25 35

Length of rods, µm 1 1

Density of rods, µm-2 100 150

Frequency shift, kHz 15.4 31.6

Frequency shift, % 0.013 0.0262

Real part of Y21 amplitude shift, %

0.86 1.86

Mass responsivity, kg/Hz

9.8830e-16 9.6907e-16

Mass responsivity per area, kg/Hz/m2

5.4906e-08 5.3837e-08

Figures 7 and 8 show the frequency and amplitude shifts of the simulated SAW sensor in consideration of nanorods with morphometric parameters from the first group of samples and the second group respectively.

With the increasing of radius and length of the rods the effective surface sensing area increased and mass loading increased in turn. It leaded to changing of resonance conditions of the structure including eigenmode frequency displacement and increasing of

signal attenuation due to mass loading. In terms of forward signal transfer characteristic this means the peak shift as shown.

Fig. 7. Forward transfer admittance versus frequency of simulated SAW sensor with nanorods as sensing element

(rods parameters were taken from the first group).

Fig. 8. Forward transfer admittance versus frequency of simulated SAW sensor with nanorods as sensing element

(rods parameters were taken from the second group).

Others values of radius and length were used to study the frequency shift as the main parameter of the SAW sensor (Fig. 9).

Fig. 9. Influence of radius and length of the rods on frequency shift.


The simulation was carried out at the same concentration of analyte. Calculated parameters are presented in the tables 2 and 3.

Table 2. Obtained SAW sensor output parameters for the various radii of ZnO nanorods (the length of rods is equal to

1 µm, and the density of the rods is 100 µm-2).

Radius of rods, nm

10 25 50 75

Frequency shift, kHz

6.52 15.25 29.91 44.87

Frequency shift, %

0.0054 0.0126 0.0248 0.0372


0.3604 0.8561 1.7579 2.7514


1.0052 e-15

9.8830 e-16

9.7511 e-16

9.6511 e-16


5.5847 e-08

5.4906 e-08

5.4173e-08

5.3617e-08

Table 3. Obtained SAW sensor output parameters for the various lengths of ZnO nanorods (the radius of rods is equal

to 25 nm, and the density of the rods is 100 µm-2).

Length of rods, µm

0.5 1 1.5 2 2.5

Frequency shift, kHz

8.15 15.21 22.73 30.06 37.48

Frequency shift, %

0.007 0.013 0.019 0.025 0.031


0.441 0.856 1.297 1.761 2.248


3.579 e-15

9.883 e-16

9.725 e-16

9.705 e-16

9.670 e-16


1.988 e-07

5.491 e-08

5.403 e-08

5.392 e-08

5.372 e-08

Due to the flexibility of the model others

parameters of the nanostructures could be successfully introduced.

5. CONCLUSION

To determine the optimal parameters of the ZnO nanostructures for application in high-sensitive modification of dual-port SAW sensor on the LiNbO3 substrate with two interdigital transducers, the approach based on finite element simulation was performed. Sensing area parameters were taken from the results of ZnO nanorods low-temperature chemical synthesis. The dependence of ZnO nanorods diameter in the range of 10-75 nm and length in the range of 0.5-2.5 µm on such output characteristics as frequency and amplitude shift was established. Mass responsivity and mass responsivity per area were calculated. The obtained dependencies confirm applicability of the model within varied ranges of parameters.

REFERENCES

[1] Lu Yicheng, “Multifunctional Biosensor Based on Zno Nanostructures”, The Journal of the Acoustical Society of America, Vol. 131, Issue 2, 2012, pp. 1667-1667.

[2] V. A. Ulianova, A. T. Orlov, A. V. Bogdan, G. A. Pashkevich, Yu. I. Yakimenko, “Morphology and Structure of ZnO Nanorods for SAW Sensors Applications”, 2013 23rd International Crimean Conference «Microwave & Telecommunication Technology» (CriMiCo’2013). Conference Proceedings. September 8–13, 2013, pp. 830-831.

[3] Umit Ozgur, “ZnO devices and applications: a review of current status and future prospects”, Proceedings of the IEEE 98, 7, 2010, pp. 1255-1268.

[4] O. Bogdan, A. Orlov, O. Petrischev, V. Ulianova, “ZnO nanostructures as sensing element of acoustic wave sensor”, Eastern-European Journal of Enterprise Technologies, Vol. 6, № 12 (60), 2012, pp. 16-22.

[5] N. Gouthami, D. Parthiban, M. Alagappan, G. Anju, “Design and simulation of 3D ZnO nanowire based gas sensor for conductivity studies”, The COMSOL Conference, October 13-15, 2011, 5 p.

[6] David Morgan, “Surface Acoustic Wave Filters with Applications to Electronic Communications and Signal Processing”, Elsevier, UK, 2007.

[7] Y. J. Lee, H. B. Kim, Y. R. Roh, H. M. Cho, S. Baik, “Development of a SAW gas sensor for monitoring SO2 gas”, Sensors and Actuators A: Physical, Vol. 64, no. 2, 1998, pp. 173–178.

[ieee 2014 37th isse international spring seminar in electronics technology (isse) - dresden,...

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