A high-Q active substrate integrated waveguide based sensor for fully characterizing magneto-dielectric (MD) materials

Journal Pre-proof A high-Q active substrate integrated waveguide based sensor for fully characterizing magneto-dielectric (MD) materials Li-Chao Fan, Wen-Sheng Zhao, Hong-Yi Gan, Li He, Qi Liu, Linxi Dong, Gaofeng Wang

PII:

S0924-4247(19)31300-7

DOI:

https://doi.org/10.1016/j.sna.2019.111778

Reference:

SNA 111778

To appear in:

Sensors and Actuators: A. Physical

Received Date:

23 July 2019

Revised Date:

27 October 2019

Accepted Date:

3 December 2019

Please cite this article as: { doi: https://doi.org/ 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. © 2019 Published by Elsevier.

1

A High-Q Active Substrate Integrated Waveguide Based Sensor for Fully Characterizing Magneto-Dielectric (MD) Materials Li-Chao Fana, Wen-Sheng Zhaoa, *, Hong-Yi Gana, Li Heb, Qi Liuc, Linxi Donga, Gaofeng Wanga, * a

Key Lab of RF Circuits and Systems, Ministry of Education, School of Electronics & Information, Hangzhou

Dianzi University, Hangzhou 310018, China. b

School of Automation & Information Technology, Xi’an University of Technology, Xi’an 710048, China

c

of

School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.

Corresponding author: Tel. +86-150-8868-7701, Email: [email protected]

*

Corresponding author: Tel. +86-152-5712-6679, Email: [email protected]

-p

ro

*

lP

Port

re

Graphical Abstract

Vdd

ur na

Biasing Network

l1

S2

G

Lser

ATF 54143

Z0

Rneg<0

Rbias

S1

D

Jo

Active SIW-based sensor terminated with negative resistance circuit.

Highlights 

A microwave sensor based on SIW technology for characterization of MD materials is for the first time reported.



The proposed sensor has the ability for measuring both complex permittivity (𝜀𝑟 = 𝜀𝑟′ − 𝑗 tan 𝛿𝑒 ) and complex permeability (𝜇𝑟 = 𝜇𝑟′ − 𝑗 tan 𝛿𝑚 ).

2



By virtue of negative resistance circuit, the proposed sensor exhibits much higher quality factor than previous reported sensors.

Abstract: A high-Q sensor based on substrate integrated waveguide (SIW) technology is designed to fully characterize magneto-dielectric materials. By utilizing the negative resistance circuit, the quality factor is further increased to an ultrahigh value of 13399. By virtue of the improved complementary split ring resonator (CSRR), the complex permittivity, as well as the complex permeability, can be extracted from variations of the resonant frequency and magnitude. A prototype of the designed active SIW-based sensor is

of

fabricated and validated experimentally. A good agreement can be achieved between the measured values and the reference data.

ro

Keywords: Complementary split-ring resonator (CSRR), negative resistance, magneto-dielectric (MD)

-p

material, permittivity, permeability, substrate integrated waveguide (SIW), loss tangent, Q factor.

1. Introduction

re

Precise determination of material parameters plays an important role in a large variety of fields including health care, food industry, national defense, and medicine [1], [2]. The microwave resonance techniques have

lP

been widely applied for these aims due to their low cost, easy fabrication, high precision, and high sensitivity [3]-[6]. In these methods, the variation of resonant frequency with the material under test (MUT) loaded onto the resonator can be measured and utilized to extract the material parameters. By virtue of novel split-ring

ur na

resonators (SRR), the permittivity of unknown samples can be measured [7], [8]. In [9], a noncontact measurement technique was developed to linearly extract complex permittivity from the variation of the impedance by means of complementary SRR (CSRR). Recently, a microwave dielectric constant sensor for liquids was developed by using the substrate integrated waveguide (SIW) in [10]. However, most of the current researches focus on the extraction of the material permittivity only, and

Jo

cannot be used directly to extract the material permeability, not even to say the magnetic loss tangent [7][10]. As the magneto-dielectric (MD) materials can be used to reduce the sizes of antennas and microwave circuits [11], it is highly desirable to develop effective techniques to fully characterize such materials. This is, a technique should be developed to enable one to extract the material permittivity and permeability, as well as the loss tangents. For characterizing MD materials, an SRR-based sensor designed by loading the microstrip line with two SRRs, which resonant at different frequencies, was introduced in [12]. Furthermore, two sensors were developed to determine the permittivity and permeability, respectively [13]. However, these methods require

3

two discrete sensors or two different resonant frequencies. More importantly, they cannot extract the loss tangents, while both the relative permittivity and relative permeability of the MD material are complex, i.e., 𝜀𝑟 = 𝜀𝑟′ (1 − 𝑗 tan 𝛿𝑒 ) and 𝜇𝑟 = 𝜇𝑟′ (1 − 𝑗 tan 𝛿𝑚 ), where 𝜀𝑟′ and 𝜇𝑟′ are real parts of the relative permittivity and relative permeability, and tan 𝛿𝑒 and tan 𝛿𝑚 are the electric loss tangent and magnetic loss tangent, respectively. More recently, a novel sensor was designed in [14] by loading microstrip line with an improved CSRR. The proposed sensor in [14] can achieve a full characterization of MD materials by assigning two separate sensing areas to measure 𝜇𝑟′ , tan 𝛿𝑚 , 𝜀𝑟′ , and tan 𝛿𝑒 in sequence. To improve the sensor performance, the SIW technique, along with the negative resistance circuit, is

of

employed in this work. A SIW-sensor with high quality factor is designed, fabricated, and measured. The reminder of this paper is organized as follows: In Section II, the structure and operation principle of the proposed sensor are introduced briefly. The negative resistance circuit is presented in Section III, and the

ro

performance of the proposed SIW-based sensor is evaluated in Section IV. In Section V, the proposed sensor

2.1 Structure

re

2. Sensor Structure and Operation Principle

-p

is fabricated on a RT/Duroid substrate and tested. Some conclusions are finally drawn in Section VI.

lP

As shown in Fig. 1, the proposed sensor is composed of a SIW reflective resonator. A single-ended microstrip line is used to excite the resonator, and a modified CSRR is etched on the metal ground plane. Here, a 50 Ω resistor is in series with the microstrip line to produce a notch in their reflection coefficient.

ur na

Fig. 2 shows detailed structure of the proposed sensor, with geometrical parameters marked. Without loss of generality, the sensor is herein designed to resonant at around 2.2 GHz. Here, Rogers RT/Duroid 4350 substrate (𝜀𝑟′ = 3.66) is adopted, and its thickness is 1.575 mm. The optimized values of geometrical

Jo

parameters for the proposed sensor are given in Table 1.

50 Ω resistor

Port Fig. 1. Schematic of the proposed sensor.

4 S S1

g

t2

c

l

t1

w0

a L d

VP

e

b

W Fig. 2. Top and bottom views of the proposed sensor.

ro

0

0

-30

-10

re

-40

-20

-50

lP

-30 1.8

0.5

1.0

ur na

-70 0.0

-p

-20 S11 (dB)

S11 (dB)

-10

-60

of

D

2.0

2.2

2.4

Frequency (GHz)

SIW cavity CSRR-loaded SIW cavity 1.5

2.0

2.5

Frequency (GHz)

Fig. 3. Magnitude of 𝑆11 of the SIW cavity with and without CSRR.

Table 1. Geometrical Parameters of the Proposed Sensor (Unit: mm)

Value 23 0.5 5.855 0.3

Jo

Para. 𝑊 𝑡1 𝑎 𝑒

Para. 𝐿 𝑡2 𝑏 𝑔

Value 23.8 3.0 10 0.3

Para. 𝑆 𝑉𝑝 𝑐 𝑙

Value 3.23 2.0 0.3 2.7

Para. 𝑆1 𝐷 𝑑 𝑊0

Value 1.0 1.0 1.7 0.3

2.2 Operation Principle Fig. 3 shows the simulated magnitude of 𝑆11 of the SIW cavity with and without CSRR. The simulation is carried out using 3-D full-wave electromagnetic simulator ANSYS HFSS. For an SIW, the resonant frequency is determined by the effective width 𝑊eff and effective length 𝐿eff , i.e., [15]

5

𝑓TE𝑚0𝑛 =

1 2√𝜇𝜀

√(

𝑚

𝑊eff

2

𝑛

) +(

𝐿eff

2

)

(1)

where 𝑚 and 𝑛 are mode indices, 𝜀 is the permittivity, and 𝜇 is the permeability. 𝑊eff and 𝐿eff of the SIW cavity can be calculated as 𝑊eff = 𝑊 − 1.08 𝐿eff = 𝐿 − 1.08

𝐷2 𝑉𝑝

𝐷2 𝑉𝑝

+ 0.1

+ 0.1

𝐷2

𝐷2 𝐿

(2)

𝑊

(3)

where 𝑊 and 𝐿 are the width and length of the SIW cavity, respectively. 𝐷 is the via diameter, and 𝑉𝑝 is the via spacing. It is worth noting that the radiation loss of the SIW cavity appears as 𝑉𝑝 is too large, and the

of

return loss may be affected by 𝐷. To minimize these losses, two design rules are formulated as 𝐷 < 𝜆𝑔 ⁄5

(4)

ro

𝑉𝑝 ≤ 2𝐷(5)

-p

where 𝜆𝑔 is the guided wavelength. To comply with these rules, 𝐷 and 𝑉𝑝 are set as 1 mm and 2 mm, respectively. It is calculated that the resonant frequency of the SIW cavity is about 0.6 GHz, which is in

50Ω TL1

TL2

ur na

lP

Port

re

accordance with the simulated result in Fig. 3.

Cc

L1

L2 Ls

Cs

Rs

Fig. 4. ECM of the proposed sensor.

Table 2. Circuit Parameters

𝐿1 (nH) 4.0

Jo

Para. Value

𝐿2 (nH) 4.0

𝐶𝑐 (pF) 0.787

𝑅𝑠 (Ω) 3731.6

𝐿𝑠 (nH) 1.75

𝐶𝑠 (pF) 2.0968

As shown in Fig. 3, the proposed sensor exhibits a resonance of −27 dB depth at 2.205 GHz by loading an CSRR. To explain the sensing mechanism, the equivalent circuit model (ECM) of the proposed sensor is established in Fig. 4, and the circuit parameters are summarized in Table 2 [16]. The resonant frequency of the CSRR is calculated as 𝑓r =

1 2𝜋√𝐿𝑠 (𝐶𝑠 +𝐶𝑐 )

(6)

where 𝐿𝑠 and 𝐶𝑠 are equivalent inductance and capacitance of the CSRR, respectively, and 𝐶𝑐 is the coupling

6

capacitance between the terminal patch and CSRR. The responses of unloaded sensor obtained by ANSYS HFSS and ECM are both plotted in Fig. 5. The results present good agreement in both magnitude and phase of 𝑆11 . The quality factor is defined as the ratio of resonant frequency 𝑓r and 3-dB bandwidth ∆𝑓3dB , i.e., 𝑄 = 𝑓r ⁄∆𝑓3dB . It is found that the proposed SIW-based sensor has a quality factor of 183. Moreover, to achieve compact size and reduce the fabrication and measurement complexity, the operating frequency of the proposed sensor is designed around 2 GHz. Note that the magnetic self-resonance of the MD material is neglected as it has negligible influence over the frequency range of interest in this study [17]. In order to increase the field intensity as much as possible, two sensing areas with different dimensions

of

are developed to realize the CSRR structure (see Fig. 1). This is, the meandered slot is employed for retrieving permittivity, while parallel slots are used for permeability characterization. The working principle is explained as follows. As is well known, the meandered line provides large inductance, while the parallel lines

ro

can be viewed as a capacitor. They can confine the magnetic field and electric field, respectively [12]. As their complementary structures, the meandered slot and the parallel slots in the designed CSRR can

-p

concentrate the electric and magnetic fields, respectively. Moreover, these two sensing areas should be compact to improve the field confinement. Fig. 6 shows the magnitude distributions of the magnetic field

re

and the electric field on the metal ground plane of the proposed sensor at the resonant frequency. In the figures, the white boxes in the figures indicate the permittivity sensing area (left) and permeability sensing

lP

area (right). It can be seen from Fig. 6 that the magnetic field and the electric field can be separated using the proposed CSRR structure. The magnetic field concentrates at the right sensing area (i.e., permeability sensing area) but vanishes at the left sensing area (i.e., permittivity sensing area), while the electric field shows an

ur na

opposite distribution, implying that the magnetic and electric parameters of the MD material can be obtained using these sensing areas, respectively. 0

-5

S11 (dB)

Jo

-10 -15 -20 -25

-30 1.8

EM Sim. Circuit Model 1.9

2.0

2.1

2.2

Frequency (GHz)

(a)

2.3

2.4

7

Phase of S11 (deg)

60 30 0

-30 -60

EM Sim. Circuit Model

-90 1.8

1.9

2.0

2.1

2.2

2.3

2.4

Frequency (GHz)

(b)

of

Fig. 5. Comparison of (a) magnitudes and (b) phases of 𝑆11 obtained by ANSYS HFSS and ECM.

ro

H-field (A/m)

-p

2 mm

5.705 mm

2.701 mm 0.9 mm

lP

Permittivity sensing area

re

Permeability sensing area

22.28 20.79 19.31 17.82 16.34 14.85 13.37 11.88 10.40 8.911 7.426 5.941 4.457 2.972 1.487 0.002

ur na

(a)

E-field (kV/m)

Jo

5.705 mm

2 mm

2.071 mm 0.9 mm

Permeability sensing area

1.905 1.778 1.651 1.524 1.397 1.270 1.143 1.016 8.890 7.620 6.350 5.080 3.810 2.540 1.270 0.000

Permittivity sensing area

(b) Fig. 6. Magnitude distributions of (a) magnetic field and (b) electric field on the metal ground plane at resonant frequency. In the simulation, the sensor is unloaded.

8

SIW cavity Cr Rr>0

Lr 1:k1

Port 1:k2

Rneg<0

of

Fig. 7. Simplified circuit model of the proposed active SIW-based sensor.

3. Negative Resistance Circuit

ro

To further enhance the resonator performance, two methodologies can be explored: 1) providing feedback loops to the passive device [18]-[22]; 2) adding negative resistance to the passive device [23], [24].

-p

Here, the second methodology is employed due to its simple circuit configuration. As can be seen in Fig. 7, the series resonance circuit (i.e., SIW cavity) is connected to a negative resistance. In Fig. 7, 𝑘1 is the

re

coupling coefficient between the SIW cavity and input 50 Ω impedance, and 𝑘2 is the coupling coefficient between the SIW cavity and negative resistance 𝑅neg . As shown in Fig. 8, the negative resistance is realized

lP

by the circuit shown in the dashed box, and an active device, i.e., E-PHEMT ATF54143 from Avago corporation is used. In Fig. 8, 𝐿ser is the series feedback inductor, and 𝑅bias is the biasing resistor providing 𝑉bias for E-PHEMT. By adjusting the biasing network and 𝐿ser at the S2 end, a negative resistance 𝑅neg can

ur na

be generated at G end of transistor. 𝑅neg is coupled to the SIW cavity through the microstrip line of length 𝑙1 . By adjusting 𝑙1 and 𝐿ser , oscillation condition can be achieved at the designed resonant frequency [18]. All the network elements are optimized with Keysight ADS 2017.

Jo

Port

Vdd Biasing Network

S2

G l1

Rneg<0

Rbias

ATF 54143

Z0 S1

D

Fig. 8. Active SIW-based resonator terminated with negative resistance circuit.

Lser

9

5 -5

S11(dB)

-15 -25 -35 -45

Passive SIW sensor Active SIW Sensor 2.0

2.2

2.4

of

-55 1.8

Frequency (GHz)

ro

Fig. 9. Magnitude of 𝑆11 of the proposed sensors with and without negative resistance circuit.

For the active SIW-based sensor shown in Fig. 8, a resonance appears if the power provided by the

-p

negative resistance is greater than the power consumed by the positive resistance of the external circuit. Fig. 9 shows the magnitude of 𝑆11 of the SIW-based sensors with and without the negative resistance circuit.

re

Here, the simulated results obtained by the full-wave electromagnetic solver are imported into Keysight ADS 2017 for simulation of the whole system. It is found that a new resonance of −47 dB appears at the resonant

lP

frequency of 2.154 GHz, and the quality factor is dramatically increased from 183 to 13399. 5 -5

ur na

0

-25 -35

Jo

-45

S11 (dB)

S11 (dB)

-15

-20

'r=1, tanm=0

'r=1, tane=0

-40

'r=10, tane=0 'r=1, tane=0.1

2.13 2.14 2.15 2.16 2.17 2.18

'r=10, tane=0.1

Frequency (GHz)

-55 1.8

2.0

2.2

2.4

Frequency (GHz)

Fig. 10. Magnitude of 𝑆11 of proposed sensor when the MUTs with different 𝜀𝑟 are loaded on the permeability sensing area.

10 5

S11 (dB)

-5 -15

tanm=0

-25

'r=1.2

'r=1 'r=1.4

-35

'r=1.6

2

'r=1.8 'r=1

-45 'r=1 -55 1.8

1.9

2.0

2.1

2.2

2.3

of

Frequency (GHz) (a)

ro

10 0.5 0

-30 -40

-p

-20

'r=1 tanm=0

tanm=0

tanm=0.1 tanm=0.2

re

S11 (dB)

-10

2.4

tanm=0.3 tanm=0.4

-50 1.8

lP

tanm=0.5

2.0

2.2

2.4

ur na

Frequency (GHz)

(b)

Fig. 11. Magnitude of 𝑆11 of the proposed sensor when the MUTs with different (a) 𝜇𝑟′ (tan 𝛿𝑚 = 0) and (b) tan 𝛿𝑚 (𝜇𝑟′ = 1) are loaded on the permeability sensing area.

4. Results and Discussions

Jo

4.1 Approach of Retracting Magnetic Parameters To evaluate the dielectric properties, a sample of MUT is placed on the permeability sensing area at first. It can be expected that the measurements of the electric and magnetic parameters are independent with each other. To illustrate this effect, one can do an experiment in which the electric parameters of the sample may vary whereas the magnetic parameters are kept unchanged. It is assumed that 𝜇𝑟′ = 1 and tan 𝛿𝑚 = 0, while 𝜀𝑟′ and tan 𝛿𝑒 increase from 1 to 10 and from 0 to 0.1, respectively. Since the electric field intensity is close to zero in the permeability sensing area, the variations of the electrical parameters have negligible influence on the resonant frequency and magnitude (see Fig. 10). Furthermore, Fig. 11 depicts the magnitude of 𝑆11 of the proposed sensor when the MUTs with different

11

𝜇𝑟 are placed onto the permeability sensing area. As 𝜇𝑟′ increases from 1 to 2, the resonant frequency moves downward from 2.154 to 2.018 GHz. As shown in Fig. 11(b), the increase in the tan 𝛿𝑚 does not affect resonant frequency but reduces magnitude. The relationship between 𝜇𝑟′ and relative shift of resonant frequency ∆𝑓 is plotted in Fig. 12, in which the fitting polynomial can be expressed as 𝜇𝑟′ = 1 + 9.725∆𝑓 + 97.235∆𝑓 2

(7)

∆𝑓 = (𝑓ref − 𝑓)⁄𝑓ref , where 𝑓 and 𝑓ref are the resonant frequencies of the proposed sensors with and without loading the MUT, respectively. 2.0

of

EM sim. Curve fitting

1.8

Weight

Residual Sum of Squares

ro

1.6

Adj. R-Square

permeability

-p

1.4 1.2

re

Real part of r

Equation

1.0 0.00

0.02

0.04

0.06

lP

Relative frequency shift (GHz)

Fig. 12. 𝜇𝑟′ of the MUT versus ∆𝑓.

0.5

ur na

Symbols: EM sim. Solid lines: Curve fitting

Jo

tan m

0.4

Equation

y = Intercept + B1*x^1 + B2*x^ 2 + B3*x^3

Weight

No Weighting

0.99865

Adj. R-Square

0.3

Intercept B

B1 B2 B3 Intercept

0.2

D

B1 B2 B3

'r=1

Intercept F

'r=1.5

0.1

'r=2 0.0

9.41545E-5

Residual Sum of Squares

0

5

10

15

20

25

30

QU/QMUT Fig. 13. tan 𝛿𝑚 of the MUT versus 𝑄𝑛 . Table 3. Coefficients for Magnetic Loss Tangent

35

B1 B2 B3

12 𝒊 0 1 2 3

𝒂𝒊𝟏 4.2×10−4 −7.04×10−3 8.01×10−4 −1.98×10−5

𝒂𝒊𝟐 −5.7×10−4 1.15×10−2 −1.96×10−3 5.24×10−5

𝒂𝒊𝟑 −2.68×10−2 2.58×10−2 5.21×10−4 −2.44×10−5

Once 𝜇𝑟′ of the MUT is determined, the magnetic loss tangent tan 𝛿𝑚 can be measured as it affects only the magnitude. Here, the relationship between tan 𝛿𝑚 and the inverse normalized quality factor 𝑄𝑛 (i.e., the ratio of quality factors of the sensors without and with loading the MUT, 𝑄𝑛 = 𝑄U ⁄𝑄MUT ) is obtained and depicted in Fig. 13. By virtue of the curve fitting technique, tan 𝛿𝑚 of the MUT can be given in the following expression: tan 𝛿𝑚 = 𝑎0 + 𝑎1 𝑄𝑛 + 𝑎2 𝑄𝑛2 + 𝑎3 𝑄𝑛3

of

(8)

𝑄U and 𝑄MUT represent the quality factors of the sensors without and with loading the, respectively. The

ro

fitting coefficients 𝑎𝑖 (𝑖 = 0, 1, 2, and 3) are functions of 𝜇𝑟′ : 2

𝑎𝑖 = 𝑎𝑖1 𝜇𝑟′ + 𝑎𝑖2 𝜇𝑟′ + 𝑎𝑖3

-p

with 𝑎𝑖𝑗 (𝑗 = 1, 2, and 3) listed in Table 3.

re

5 -5 0

lP -20

-45

2.14

2.15

2.16

2.17

1.8

tane=0

'r=1 'r=2 tanm=0

'r=1 tanm=0.5

'r=2

2.18

Frequency (GHz)

-55 1.6

'r=1

tanm=0

-40

ur na

-35

S11 (dB)

S11(dB)

-15 -25

(9)

2.0

tanm=0.5

2.2

2.4

Frequency (GHz)

Jo

Fig. 14. Magnitude of 𝑆11 of the proposed sensor when the MUTs with different 𝜇𝑟 are loaded on the permittivity sensing area.

13 5 -5

S11 (dB)

-15 10 -25 -35 -45 'r=1

'r=1, tanm=0, tane=0 -55 1.6

1.8

2.0

2.2

2.4

of

Frequency (GHz)

(a) 0.1

0.1

ro

5 -5

tane=0

tane=0

-p

-25

'r=10

-35

'r=1, tanm=0 tane=0

tane=0.06

-45

tane=0.02

tane=0.08

-55 1.6

tane=0.1

lP

tane=0.04

re

S11 (dB)

-15

1.8

'r=1

2.0

2.2

2.4

Frequency (GHz)

(b)

ur na

Fig. 15. Magnitude of 𝑆11 of the proposed sensor when the MUTs with different (a) 𝜀𝑟′ (tan 𝛿𝑒 = 0) and (b) tan 𝛿𝑒 (𝜀𝑟′ = 1) are loaded on the permittivity sensing area.

4.2 Approach of Retracting Electric Parameters The capability of the proposed sensor in extracting 𝜀𝑟 of the MUT is illustrated in this subsection. A

Jo

sample is placed onto the permittivity sensing area, which is indicated in the white box of Fig. 6(b). It is worth noting that there is a little magnetic field in the permittivity sensing area. The influence of complex permeability of the sample on the permittivity characterization should be investigated at firstly. Therefore, in the permittivity measurement, 𝜀𝑟 is initially kept unchanged, while 𝜇𝑟′ and tan 𝛿𝑚 of the MUTs are increased from 1 to 2 and from 0 to 0.5, respectively. As shown in Fig. 14, as the real part of the permeability varies, the resonant frequency is almost unchanged. However, the magnitude, as well as the quality factor, exhibits a moderate drop from 13399 to 2460 with the increasing magnetic loss tangent. This implies that the magnetic loss tangent of the sample must be taken into account in the retrieval of electric loss tangent.

14 10

Real part of r

EM sim. Curve fitting 7

4

1 0.00

0.05

0.10

0.15

0.20

of

Relative frequency shift (GHz)

Table 4. Fitting Coefficients for Electric Loss Tangent 𝒃𝒊𝟑 𝒃𝒊𝟒 𝒃𝒊𝟓 𝒃𝒊𝟔 𝒃𝒊𝟕 −5.34×10−4 −1.03×10−2 −1.34×10−2 −2.01×10−3 −0.232 5.37×10−4 −5.97×10−5 2.47×10−3 1.10×10−4 1.73×10−2 −6.80×10−6 6.34×10−5 −1.65×10−4 4.69×10−6 −5.31×10−4 −3.19×10−7 0 0 0 0

-p

𝒃𝒊𝟐 6.42×10−3 −6.99×10−3 1.25×10−4 2.11×10−6

re

𝒃𝒊𝟏 −2.27×10−2 2.45×10−2 −9.61×10−4 1.92×10−5

0.10

Symbols: EM sim. Solid lines: Curve fitting

tane

0.06

ur na

0.04

lP

0.08

tanm=0

0.02

0.00

Jo

𝒊 0 1 2 3

ro

Fig. 16. 𝜀𝑟′ of the MUT versus ∆𝑓.

2

tanm=0.1 tanm=0.5 4

6

8

QU/QMUT

(a)

10

12

𝒃𝒊𝟖 0.107 −5.32×10−3 1.21×10−4 0

𝒃𝒊𝟗 −1.89×10−2 7.74×10−4 −5.78×10−6 0

15 0.10 Symbols: EM sim. Solid lines: Curve fitting 0.08

tane

0.06

0.04 tanm=0

0.02

tanm=0.1 tanm=0.5

0.00

1

3

5

7

9

11

13

15

17

19

21

QU/QMUT

of

(b) 0.10

ro

Symbols: EM sim. Solid lines: Curve fitting 0.08

-p

tane

0.06

0.02

0

10

20

lP

0.00

re

0.04

30

tanm=0

tanm=0.1 tanm=0.5

40

50

QU/QMUT

(c)

ur na

Fig. 17. tan 𝛿𝑒 of the MUT versus 𝑄𝑛 . (a) 𝜀𝑟′ = 1, (b) 𝜀𝑟′ = 2, and (c) 𝜀𝑟′ = 10.

Figs. 15(a) and 15(b) show the magnitude of 𝑆11 the proposed sensor for various values of complex permittivity. The complex permeability is set as a unit, i.e., 𝜇𝑟′ = 1 and tan 𝛿𝑚 = 0. It is evident that the increase in the permittivity leads to a red shift of the resonant frequency. As 𝜀𝑟′ increases from 1 to 10, the

Jo

resonant frequency is reduced from 2.154 to 1.739 GHz, while it is kept unchanged with the varying tan 𝛿𝑒 . Fig. 16 shows the relationship between 𝜀𝑟′ of the MUT and ∆𝑓. The fitting polynomial expression can be given as

𝜀𝑟′ = 1 + 32.306∆𝑓 + 79.901∆𝑓 2

(10)

As shown in Fig. 15(b), with the increasing tan 𝛿𝑒 , the resonant frequency is unchanged, while the magnitude decreases significantly. Fig. 17 shows tan 𝛿𝑒 of the MUT as a function of 𝑄𝑛 for different tan 𝛿𝑚 and 𝜀𝑟′ . The curve fitting is applied to obtain the expression of tan 𝛿𝑒 as follows: tan 𝛿𝑒 = 𝑏0 + 𝑏1 𝑄𝑛 + 𝑏2 𝑄𝑛2 + 𝑏3 𝑄𝑛3

(11)

16

where 𝑏𝑖 (𝑖 = 0, 1, …, and 4) is the fitting coefficient: 2

2

𝑏𝑖 = (𝑏𝑖1 + 𝑏𝑖2 𝜀𝑟′ + 𝑏𝑖3 𝜀𝑟′ ) + (𝑏𝑖4 + 𝑏𝑖5 𝜀𝑟′ + 𝑏𝑖6 𝜀𝑟′ ) 2

⋅ tan 𝛿𝑚 + (𝑏𝑖7 + 𝑏𝑖8 𝜀𝑟′ + 𝑏𝑖9 𝜀𝑟′ ) tan2 𝛿𝑚

(12)

with 𝑏𝑖𝑗 (𝑗 = 1, 2, …, 6) listed in Table 4. The characterization of the MD materials using the proposed sensor is summarized as follows: Step 1: Place the sample on the permeability sensing area and record the relative shift ∆𝑓 in the resonant frequency and the normalized quality factor 𝑄𝑛 ; Step 2: Calculate 𝜇𝑟′ by substituting ∆𝑓 into (7);

of

Step 3: Calculate tan 𝛿𝑚 by substituting 𝜇𝑟′ and 𝑄𝑛 into (8);

Step 4: Place the sample on the permittivity sensing area and record ∆𝑓 and 𝑄𝑛 again;

ro

Step 5: Calculate 𝜀𝑟′ by substituting ∆𝑓 into (10);

Step 6: Calculate tan 𝛿𝑒 by substituting tan 𝛿𝑚 , 𝜀𝑟′ , and 𝑄𝑛 into (11).

-p

Moreover, it is worth noting that as the sample size is equal to or smaller than the permeability sensing area, the above retrieval procedure can be applied for fully characterization of the MD materials. However,

re

the measurement accuracy, repeatability, and sensitivity may be affected to some extent.

4.3 Sensor Performance Comparison

lP

Table 5 presents a comparison between the state-of-the-art sensors based on SRR, CSRR, and SIW in terms of their capabilities in determination of the complex permittivity and permeability and the unloaded

ur na

quality factor. Although a high-Q sensor was designed in [6], it cannot be used for characterizing MD materials. Moreover, the proposed sensor can realize the same functionality as the CSRR-based sensor proposed in [14] but exhibits a higher quality factor, which can be dramatically improved to 13399 with the help of the negative resistance circuit. In real-world applications, the shift in resonant frequency of the resonator-type sensor is converted to voltage information through the processing circuit [10], [25]. More

Jo

accurate resonant frequency can be measured with higher quality factor. Moreover, for measuring MUT with high loss, the notch magnitude would be degraded significantly and hardly distinguished, thereby limiting the detection capability. Therefore, high quality factor of the sensor would be always beneficial for improving the system accuracy and applicability.

Table 5. Comparison between the proposed sensor and previous sensors Ref. [3] [6] [12] [13]

Resonant type CSRR SIW SRR SRR

𝒇𝒓 (GHz) 2.65 10.5 2.45 2.74

𝜺′𝒓    

𝐭𝐚𝐧 𝜹𝒆    

𝝁′𝒓    

𝐭𝐚𝐧 𝜹𝒎    

𝑸𝑼 80 520 260 260

17 [14] This work

CSRR Passive SIW Active SIW

  

2.47 2.205 2.154

  

  

  

145 183 13399

On the other hand, for retrieving the loss tangents of the MD materials, the higher the quality factor is, the higher sensitivity it can be achieved. For a clear illustration, the sensitivities of the proposed sensor are acquired and compared. The sensitivities of the sensor in measuring the relative permeability and permittivity are defined as 𝑆𝑚 = ∆𝑓⁄(𝜇𝑟′ − 1) and 𝑆𝑒 = ∆𝑓⁄(𝜀𝑟′ − 1), respectively. The proposed sensors, in spite of passive and active type, exhibit comparable sensitivities in measuring permeability and permittivity to the

11

[14] This work (passive) This work (active)

ro

9 8

-p

-2

Sm (10 )

10

1.2

1.4

re

7 6

of

sensor in [14].

1.6

1.8

2.0

lP

r

(a)

[14] This work (passive) This work (active)

3

-2

Se (10 )

ur na

4

Jo

2

1

2

4

6

r

8

10

(b) Fig. 18. Sensitivities of the proposed sensors in measuring (a) 𝜇𝑟′ and (b) 𝜀𝑟′ .

18

[14] This work (passive) This work (active) r = 1

3

Sml (10 )

60

40

1.7 1.3 0.9

20 0.5 0.1

0.1

0.2

0.3

0.4

0.5

0

0.1

0.2

0.3

0.4

of

tan m (a)

ro

[14] This work (passive) This work (active) r = 1

-p

2.5

2.0

1.5

100 1.0

0

0.02

0.04

0.06

0.08

0.10

lP

0.5

re

3

Sel (10 )

300

200

0.5

0.02

0.04

0.06

0.08

0.10

ur na

tan e

(b)

Fig. 19. Sensitivities of the proposed sensors in measuring (a) tan 𝛿𝑚 and (b) tan 𝛿𝑒 .

Furthermore, Fig. 19 plots the sensitivities of the proposed sensors in retrieving the magnetic and electric loss tangents, which are defined as 𝑆𝑚𝑙 = (𝑄𝑛 − 1)⁄tan 𝛿𝑚 and 𝑆𝑒𝑙 = (𝑄𝑛 − 1)⁄tan 𝛿𝑒 , respectively. As

Jo

shown in Fig. 19, the proposed passive sensor exhibits slightly higher sensitivity in measuring loss tangents than the sensor in [14], which is due to higher quality factor of the SIW structure. By employing the negative resistance circuit, the sensor quality factor, as well as 𝑆𝑚𝑙 and 𝑆𝑒𝑙 , is dramatically increased by more than 23 orders of magnitude. Although this advantage reduces with the increasing 𝜇𝑟′ and 𝜀𝑟′ , the active sensor is still superior to the passive one with 𝜇𝑟′ = 2 and 𝜀𝑟′ = 10. 5. Experimental Validation To verify the capability of the proposed active SIW-based sensor for measuring complex permittivity

19

and permeability, the experimental prototype is fabricated, as shown in Fig. 18(a). The SIW cavity is directly fed by 50 Ω SMA connector, and the circuit is powered by a +2 V power supply. The electrical characteristics of the proposed sensor is captured by using Keysight N5247A PNA-X vector network analyzer (VNA). The samples of various materials are prepared in advance, cut in appropriate size, and placed in proper positions.

SIW cavity

ATF 54143

ro

GND

of

Vdd

lP

re

-p

(a)

Jo

ur na

(b)

(c) Fig. 20. (a) Photograph of the fabricated sensor. (b) Photographs of the sensors in the measurements of permittivity and permeability. (c) Experimental setup.

20

Figs. 20(b) and 18(c) show the photographs of the proposed active SIW-based sensor in measuring 𝜇𝑟 and 𝜀𝑟 of the MUT, respectively. The measured reflection coefficients of the proposed sensor are plotted in Fig. 21. In the measurements, the unloaded case is set as reference, with the material parameters extracted based on the procedure described in Section IV. Here, three dielectric materials (FR4 and TP composites with different permittivity) and two MD materials (M-type hexaferrite-PVDF (20 wt. %) and Ni-Zn ferritePVDF (10 wt. %)) are tested. M-type hexaferrite-PVDF (20 wt. %) and Ni-Zn ferrite-PVDF (10 wt. %) are named as MD1 and MD2, respectively. The extracted permittivity and permeability of the samples are listed in Table 6. It is found that in the measurements of permittivity and permeability, the test error is below 4.7%, which may potentially arise from the measurement uncertainties.

of

5

ro

-5

-25

Air

-35

Ni-Zn ferrite-PVDF (10 wt.%) M-type hexaferrite-PVDF (20 wt.%)

-p

S11 (dB)

-15

TP (r=2.2)

TP (r=3)

re

FR4

-45 1.6

1.8

2.0

2.2

2.4

Frequency (GHz)

5

ur na

-5

lP

(a)

S11 (dB)

-15 -25

Air

TP (r=2.2) TP (r=3)

Jo

-35

FR4 M-type hexaferrite-PVDF (20 wt.%) Ni-Zn ferrite-PVDF (10 wt.%)

-45 1.8

1.9

2.0

2.1

2.2

2.3

2.4

Frequency (GHz)

(b)

Fig. 21. Measured reflection coefficients of the fabricated sensor when the samples are loaded on the (a) permittivity sensing area and (b) permeability sensing area. Table 6. Measured Parameters of Different Materials 𝜺′𝒓

𝐭𝐚𝐧 𝜹𝒆 Reference 2.2

This work 0.00095

Reference

TP1 (𝜀𝑟 = 2.2)

This work 2.299

TP2 (𝜀𝑟 = 3)

2.868

3

0.0024

≤0.001

≤0.001

21 FR4 MD1

4.254 2.569

4.4 2.49

0.004 0.017

≤0.2

MD2

2.31

2.21

0.015

≤0.2

Reference 1.2

This work 0.31

Reference

MD1

This work 1.144

MD2

1.334

1.4

0.12

≤0.5

𝝁′𝒓

0.02

𝐭𝐚𝐧 𝜹𝒎 ≤0.5

6. Conclusion

of

In this work, a high quality factor sensor was developed by using the SIW technology, with an improved CSRR etched on the metal ground plane. The CSRR had separate permeability sensing area and permittivity

ro

sensing area. It was demonstrated that the electric field concentrates on the permittivity sensing area and vanishes on another sensing area. The magnetic field has an opposite distribution. This is, the measurements of the complex permittivity and the complex permeability can be conducted independently. The SIW-based

-p

sensor was connected to a negative resistance, which was realized by an active device E-PHEMT ATF54143. By utilizing the negative resistance circuit, the quality factor was improved from 183 to an ultrahigh value

re

of 13399. A prototype of the proposed sensor was fabricated and tested, and the measured results exhibited

Declaration of interests

lP

a good accuracy.

ur na

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported in part by the National NSFC under Grants 61874038 and 51602256, the Talent

Jo

Project of Zhejiang Association for S&T under Grant 2017YCGC012, and the Key Lab Fund Project of S&T on Micro-system Laboratory under Grant 614280401010317.

References [1]

R. Mirzavand, M. M. Honari, and P. Mousavi, “High-resolution balanced microwave material sensor with extended dielectric range,” IEEE Trans. Indus. Electron., vol. 64, no. 2, pp. 1552-1560, Feb. 2017.

[2]

S. Trabelsi and S. O. Nelson, “Microwave sensing of quality attributes of agricultural and food products,” IEEE Instrum. Meas. Mag., vol. 19, no. 1, pp. 36-41, Feb. 2016.

[3]

M. A. H. Ansari, A. K. Jha, and M. J. Akhtar, “Design and application of the CSRR-based planar sensor for noninvasive measurement of complex permittivity,” IEEE Sensors J., vol. 15, no. 12, pp. 7181-7189, Dec. 2015.

22 [4]

M. A. H. Ansari, A. K. Jha, Z. Akhter, and M. J. Akhtar, “Multi-band RF planar sensor using complementary split ring resonator for testing of dielectric materials,” IEEE Sensors J., vol. 18, no. 16, pp. 6596-6606, Aug. 2018.

[5]

C. S. Lee and C. L. Yang, “Thickness and permittivity measurement in multi-layered dielectric structures using complementary split-ring resonators,” IEEE Sensors J., vol. 14, no. 3, pp. 695-700, Mar. 2014.

[6]

N. K. Tiwari, A. K. Jha, S. P. Singh, Z. Akhter, P. K. Varshney, and M. J. Akhtar, “Generalized multimode SIW cavitybased sensor for retrieval of complex permittivity of materials,” IEEE Trans. Microw. Theory Tech., vol. 66, no. 6, pp. 3063-3072, Jun. 2018.

[7]

K. Xu, Y. Liu, S. Chen, P. Zhao, L. Peng, L. Dong, and G. Wang, “Novel microwave sensors based on split ring resonators for measuring permittivity,” IEEE Access, vol. 6, pp. 26111-26120, May 2018.

[8]

J. Carnerero-Cano, G. Galindo-Romera, J. J. Martínez-Martínez, and F. J. Herraiz-Martínez, “A contactless dielectric

of

constant sensing system based on a split-ring resonator-loaded monopole,” IEEE Sensors J., vol. 18, no. 11, pp. 4491-4502, Jun. 2018. [9]

J. Dong, F. Shen, Y. Dong, Y. Wang, W. Fu, H. Li, D. Ye, B. Zhang, J. Huangfu, S. Qiao, Y. Sun, C. Li, and L. Ran,

Microw. Theory Tech., vol. 64, no. 9, pp. 2883-2892, Sep. 2016.

S. Chen, M. Guo, K. Xu, P. Zhao, Y. Hu, L. Dong, and G. Wang, “A dielectric constant measurement system for liquid

-p

[10]

ro

“Noncontact measurement of complex permittivity of electrically small samples at microwave frequencies,” IEEE Trans.

based on SIW resonator,” IEEE Access, vol. 6, pp. 41163-41172, Aug. 2018. [11]

H. Mosallaei and K. Sarabandi, “Magneto-dielectrics in electromagnetics: Concept and applications,” IEEE Trans.

[12]

re

Antennas Propag., vol. 52, no. 6, pp. 1558-1567, Jun. 2004.

M. Shafi K T, A. K. Jha, and M. J. Akhtar, “Improved planar RF sensor for retrieval of permittivity and permeability of materials,” IEEE Sensors J., vol. 17, no. 17, 5479-5486, Sep. 2017.

M. Shafi K T, M. A. H. Ansari, A. K. Jha, and M. J. Akhtar, “Design of SRR-based microwave sensor for characterization

lP

[13]

of magnetodielectric substrates,” IEEE Microw. Wireless Compon. Lett., vol. 27, no. 5, pp. 524-526, May 2017. [14]

M. Saadat-Safa, V. Nayyeri, M. Khanjarian, M. Soleimani, and O. M. Ramahi, “A CSRR-based sensor for full

2019. [15]

ur na

characterization of magneto-dielectric materials,” IEEE Trans. Microw. Theory Tech., vol. 67, no. 2, pp. 806-814, Feb. T. Yun and S. Lim, “High-Q and miniaturized complementary split ring resonator-based substrate integrated waveguide microwave sensor for crack detection in metallic materials,” Sensors and Actuators A: Phys., vol. 214, pp. 25-30, Aug. 2014. [16]

F. Aznar, M. Gil, J. Bonache, L. Jelinek, J. D. Baena, R. Marques, and F. Martin, “Characterization of miniaturized

Jo

metamaterial resonators coupled to planar transmission lines through parameter extraction,” J. Appl. Phys., vol. 104, no. 11, p. 114501, 2008.

[17]

F. Hettstedt, U. Schurmann, R. Knochel, and E. Quandt, “Double coil permeameter for the characterization of magnetic materials,” German Microw. Conf., Munich, Germany, Mar. 2009.

[18]

Z. Chen, W. Hong, J. X. Chen, J. Zhou, and L. S. Li, “Low-phase noise oscillator utilizing high-Q active resonator based on substrate integrated waveguide technique,” IET Microw. Antennas Propag., vol. 8, no. 3, pp. 137-144, Mar. 2014.

[19]

M. Nick and A. Mortazawi, “Low-phase noise planar oscillators based on low-noise active resonators,” IEEE Trans. Microw. Theory Tech., vol. 58, no. 5, pp. 1133-1139, May 2010.

[20]

Z. Chen, W. Hong, J. Chen, and J. Zhou, “Design of high-Q tunable SIW resonator and its application to low phase noise VCO,” IEEE Microw. Wireless Compon. Lett., vol. 23, no. 1, pp. 43-45, Jan. 2013.

23 [21]

W. Y. Park and S. Lim, “A low phase-noise microwave oscillator using a substrate integrated waveguide resonator based on complementary split ring resonator,” Asia-Pacific Microw. Conf., Melbourne, VIC, USA, Dec. 2011, pp. 371-374.

[22]

Z. Li, X. Tang, Y. Liu, and Z. Cai, “Design of Ku-band low phase noise oscillator utilizing high-Q air-filled substrate integrated waveguide resonator,” Int. Conf. Microw. Millimeter Wave Technol. (ICMMT), Chengdu, China, May 2018, pp. 1-4.

[23]

Y. T. Lee, J. Lee, and S. Nam, “High-Q active resonators using amplifiers and their applications to low phase-noise freerunning and voltage-controlled oscillators,” IEEE Trans. Microw. Theory Tech., vol. 52, no. 11, pp. 2621-2626, Nov. 2004.

[24]

Z. Chen, W. Hong, and J. X. Chen, “High-Q planar active resonator based on substrate integrated waveguide technique,” Electron. Lett., vol. 48, no. 10, pp. 575-577, May 2012.

[25]

M. U. Memon, H. Jeong, and S. Lim, “Metamaterial-inspired radio frequency based touchpad sensor system,” IEEE Trans.

of

Instrum. Meas., available online in early access.

ro

Biographies

lP

re

-p

Author Biography

ur na

Li-Chao Fan received the B.E. degree from Lanzhou Jiaotong University, Lanzhou, China, in 2017. He is currently working towards the M.E. degree at Hangzhou Dianzi University, Hangzhou, China. His research interest is focused on the design of microwave

Jo

sensors for IoT applications.

24 Wen-Sheng Zhao received the B.E. degree in electronic science and technology from Harbin Institute of Technology, Harbin, China, in 2008, and the Ph.D. degree in electronic science and technology from Zhejiang University, Hangzhou, China, in 2013. He was a Visiting Ph.D. Student with National University of Singapore, Singapore, from 2010 to 2013, and a Visiting Scholar with Georgia Institute of Technology, Atlanta, USA, from 2017 to 2018. He is currently an Associate Professor at Hangzhou Dianzi University, Hangzhou, China. He has authored or co-authored two books, three book chapters, and over 100 papers in refereed journals and conference proceedings (including over 30 IEEE journal papers). His current research interests include 3-D integrated circuits, carbon nanoelectronics, signal and power integrity, microwave sensor, multiphysics simulation, and machine learning application in electronic design. He is a Senior Member of IEEE and Chinese Institute of Electronics and serves as an Associate Editor for IEEE

re

-p

ro

of

Access.

lP

Hong-Yi Gan received the B.E. degree from Anhui Institute of Information Technology, Wuhu, Anhui, China, in 2018. He is currently working towards the M.E. degree at Hangzhou Dianzi University, Hangzhou, China. His research interest is focused on

Jo

ur na

the design of microwave sensors for IoT applications.

Li He received the B.E. and Ph.D. degrees in electronic science and technology from Xi’an Jiaotong University, Xi’an, China, in 2009 and 2015, respectively. He is currently an Associate Professor at Xi’an University of Technology, Xi’an, China. His main research field is magnetic-dielectric composite materials and devices.

25

of

Qi Liu received the B.E. and Ph.D. degrees from Zhejiang University, Hangzhou, China, in 2011 and 2016, respectively. She is currently a Faculty Member with Hangzhou Dianzi University, Hangzhou, China, since 2018. Her research interests include the

ur na

lP

re

-p

ro

design and applications of microwave sensors.

Linxi Dong received the Ph.D. degree from Zhejiang University, Hangzhou, China, in 2004. He is currently a Professor with Hangzhou Dianzi University, Hangzhou, China. His current research interests include the design of inertial MEMS sensors,

Jo

resonators, including design, modeling, and fabrication of microstructures.

of

26

Gaofeng Wang received the Ph.D. degree in electrical engineering from University of Wisconsin-Milwaukee, WI, USA, in 1993,

ro

and the Ph.D. degree in scientific computing from Stanford University, CA, USA, in 2001. He was a Scientist with Tanner Research Inc., Pasadena, CA, USA, from 1993 to 1996. He was a Principal Researcher and Development Engineering with Synopsys Inc., Mountain View, CA, from 1996 to 2001. In 1999, he served as a Consultant with Bell Laboratories, Murray Hill, NJ. He was the

-p

Chief Technology Officer (CTO) of Intpax, Inc., San Jose, CA, USA, from 2001 to 2003. He was the CTO of Siargo Inc., Santo Clara, CA, USA, from 2004 to 2010. He was a Professor and the Head of CJ Huang Information Technology Research Institute with Wuhan University, Wuhan, China, from 2004 to 2013. He was a Chief Scientist with Lorentz Solution, Inc., Santa Clara, CA, USA,

re

from 2010 to 2013. He is currently a Distinguished Professor with Hangzhou Dianzi University, Hangzhou, China. He has over 250 journal articles and held 47 patents. His current research interests include integrated circuit and microelectromechanical system

Jo

ur na

lP

design and simulation, computational electromagnetics, electronic design automation, and wavelet applications in engineering.