# Millimetre-Wave Metamaterial-Based Sensor for Characterisation of Cooking Oils

Authors: Suhail Asghar Qureshi; Zuhairiah Zainal Abidin; Adel Yahya Isa Ashyap; Huda A. Majid; Muhammad Ramlee Kamarudin; Ma Yue; Mohd Syis Zulkipli; Jamel Nebhen
Journal: International Journal of Antennas and Propagation
 (2021)

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## Abstract

The characterisation of the cooking oils presents a significant challenge due to minor changes in their dielectric behaviour. In this paper, a new metamaterial-based sensor incorporating a split-ring resonator (SRR) with a microstrip transmission line is presented to characterise cooking oils. The design demonstrates metamaterial characteristics of negative permittivity and permeability simultaneously at the resonance frequency. Furthermore, its operation in the range of millimetre-wave frequencies can further enhance its sensitivity, especially for liquid materials. The sensor’s novelty is the operation at millimetre-wave frequencies that offers a high shift in the transmission coefficient while operating at 30 GHz. The sensor’s performance analysis is undertaken by using six MUTs with dielectric constants ranging from 0.126 to 4.47. The presented structure designed on 12 × 8 mm2 Rogers substrate offers a sensitivity of 1.12 GHz per unit change in dielectric constant. The phase's shift demonstrates a lower percentage error than the amplitude and linearly moves towards higher frequencies with the increase in dielectric constant and tangent loss of MUT. The designed sensor can be prominently useful for detecting liquids' chemical characteristics in chemistry and medicine fields.


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## Body

## 1. Introduction

Each material has specific electrical properties, including permittivity, conductivity, tangent loss, and permeability. Microwave sensors are smart to measure these properties in biomedical, chemical, industrial, and electronic applications as they provide stable, high-quality, and highly sensitive sensing. The microwave sensors also reduce the cost of measurement and production. Various mechanisms of microwave sensors have been presented recently for dielectric characterisation of materials, including transmission line-based resonator [1, 2], cavity-based resonator [3, 4], oval wing resonator [5], and antenna-based resonator [6, 7]. Besides, the existing sensors have been presented for different applications such as material detection [8], label-free sensing of DNA [9], bacterial growth monitoring [10], and imaging of the breast [11]. In this regard, metamaterial resonators offer higher sensitivity than other microwave sensors and they have been reportedly found to sense small variation in EM (electromagnetic) properties of the sample [12]. As a result, metamaterial-based sensors have been presented for dielectric characterisation of ethanol and methanol [13], assessment of dielectric substrates [14], blood glucose monitoring [15–17], measurement of material thickness [18], biomedical applications [19], detection of cancerous cells [20], and the evaluation of oils [21]. Metamaterials (MMs) are artificially engineered structures that exhibit negative permeability and permittivity simultaneously [22]. MM designs are often subwavelength structures that are easier to manufacture and have much simpler shapes. MM-based sensing offers enhanced resolution and sensitivity and more flexibility in designing the sensors [23].The most widely used configuration of MM is the split-ring resonator (SRR) due to its intriguing EM characteristics. The SRR provides a strong magnetic resonance in response to EM excitation when the magnetic energy stored in the inductor and the electrical energy stored in the capacitor is balanced by distance, size, structure, and orientation [24]. Since the last few years, numerous researchers have demonstrated the use of metamaterials as electrochemical sensors. Recent advances in thin-film metamaterials used in therapeutic and diagnostic applications are reviewed in [25]. Microfluidic sensors based on MM are presented in [22], operating from gigahertz to terahertz. A substrate-integrated waveguide sensor for characterising chemicals at millimetre-wave (mm-W) frequency range was presented in [26]. The researchers have proposed various techniques to increase the sensitivity of these sensors by creating a gap between complementary split-ring resonator (CSRR) [27], employing planar microwave resonators [10], and designing closed-loop inside split-ring resonator [17].A couple of MM-based sensors were reported in [2, 28] to detect branded and unbranded diesel types. In another study, a G-shaped metamaterial absorber based sensor was proposed to detect various oils including corn oil, olive oil, and cotton oil [29]. Most sensors studied have low sensitivity, which can cause difficulties in detecting oils having small changes in dielectric permittivity and loss tangent. The sensor can be manipulated for various MM-W band applications with an appropriate design, leading to smaller sizes and inconsequential response to impurity in the material under test (MUT) and temperature variation [20].Besides, public health’s significance requires a regular check on cooking oil’s quality as the consumption of unhealthy oils can lead to deadly diseases. Particularly in developing countries, the awareness of edible oil purchasing choice is relatively lower than in developed regions [30]. To the best of the author’s knowledge, no metamaterial-based sensor applicable in oil’s characterisation has been proposed yet operating at millimetre-wave (MM-W) frequencies. Therefore, lightweight, smaller, and highly sensitive metamaterial-based split-ring resonator (MM-SRR) could be designed to assess the quality of cooking oils by detecting minor changes in the dielectric constant due to its chemical characteristics.


## 2. Design of MM-Based Split-Ring Resonator

A grouping of split-ring resonators connected by a microstrip transmission line and a ground structure is considered for the characterisation of oils by calculating their changes in the dielectric constant. The design’s novelty lies in the two split rings (one enclosed by the other) and its operation at millimetre-wave frequencies. Rogers 5880 of 0.25 mm thickness having a dielectric constant,εr = 2.2, and tangent loss, tan θ = 0.0009, is used as a preferred substrate for above 10 GHz applications frequencies. The transmission line and the ground are made of copper having a thickness of 35 nm. The cross-sectional view of the proposed design is shown in Figure 1, consisting of two circular split-ring patterns with a different radius and inverse split path. The outer ring is connected to Port 1, while the inner ring is connected to Port 2. The inner ring is surrounded by an outer ring that gives the sensor an enhanced coupling effect.Figure 1
Design of proposed metamaterial-based SRR: (a) top view and (b) bottom view (full ground plane).
(a)(b)MM-based ring resonator works like a parallel LC circuit whose resonance frequency is defined by equation (1). The effective inductance (Leff) and effective capacitance (Ceff) are caused by the circuit that depends on the metamaterial design’s dimensions such as the radii (R1 and R2), the width of the split rings (w) as well as the substrate's thickness (h) [31]:(1)fr=12πLeffCeff.The effective capacitance is the sum of surface capacitance (Cs) and the gap capacitance (Cg), which are represented in equations (2) and (3), respectively [6]:(2)Cg=ε0hwg+ε02πhln2.4h/w,where ε0 = free-space permittivity. (3)Cs=2ε0hπln4R2g.The effective inductance of the resonator is determined using the following equation [31]:(4)L=μ0R1+w/22πln8R2+w/2h+w−0.5,where μ0= free-space permeability.The parametersh, w, R1, R2, and G altogether change the metamaterial resonator's resonant frequency. The required dimensions of the structure were calculated using equations (1)–(4). Through parametric studies, further modifications were done to get the resonance frequency near the desired range. Table 1 shows the optimized dimensions for the designed resonating at 30 GHz.Table 1
Dimensions of the split-ring resonator in mm.
ParameterValue (mm)ParameterValue (mm)XL8YL12R11.45R22.5w = Lr1 = Lr20.5G0.6Lw0.6


## 3. Simulation and Characterisation of the Design

Overall dimensions of the proposed structure were optimized through a parametric study. The numerical study was conducted on the three potential parameters affecting the transmission response of the design. Figures2–4 show the effect of the width of split rings (Lr1 and Lr2), the radius of outer split-ring (R2), and the radius of inner split-ring (R1), respectively, on resonance frequency. It can be noticed that the increase in radii of split rings causes the resonance to move towards lower frequencies. On the other hand, width shifts the resonance towards higher frequencies due to the lesser gap between the two rings. We have chosen Lr1 and Lr2, 0.5 mm to maintain a sufficient difference between them and avoid the rings overlap over each other.Figure 2
Effect of the “w” on resonance.Figure 3
Effect of “R2” on resonance.Figure 4
Effect of the “R1” on resonance.The highest negative peak is obtained whenR1 is 1.45 mm and R2 is 2.5 mm.The proposed design is simulated and optimized using Computer Simulation Technology (CST) microwave studio and MATLAB software for metamaterial characterisation. A Numerical Robust Method (NRM) is used to test the characteristics of the metamaterial using equations (5)–(9) [32]. Figure 5 shows the simulated transmission, S21, and reflection, S11, coefficients, which indicate that the structure resonates at 30 GHz (S21). However, the reflection coefficient, S11, at the resonance frequency, is found to be close to zero. As seen in Figure 6 at the negative peak of S21, effective permittivity, εr, becomes negative and stays negative at 29 to 31 GHz (highlighted in blue). Besides, permeability, μ is negative from 22 GHz to 32 GHz, and a transition from positive to negative is observed in the refractive index, n, precisely at the resonance frequency (30 GHz). Metamaterial exhibiting double negative (DNG) characteristics is represented in a bandwidth of 30 GHz to 31 GHz where all parameters (ε, µ, and n) had a negative value in this range of frequencies:(5)n=1k0dlneink0d″+2mπilneink0d′,where(6)eink0d=X±i1−X2,(7)X=12S211−S112+S212.Figure 5
S-parameters of the designed SRR.Figure 6
Metamaterial characterisation of the proposed SRR.Here,m is associated with the branch index (n’) whose real part is represented by (’) and the imaginary part is represented by (’’):(8)ε=nz,(9)μ=nz.On the other hand, physical characterisation for the designed resonator is described by the electric field and surface current distribution. The resultant electric field distributions due to Port 1 and Port 2 on the resonator are illustrated in Figures7(a) and 7(b), respectively, for the resonance frequency. It can be seen in Figure 7 that the electric field distributes evenly to the sides of the split ring by the impact of gaps between the outer and inner ring, which is visible at the sides of the outer ring. Moreover, it can be seen that electric field distribution for the outer ring is weaker than the inner ring emphasising that the inner ring is the central entity responsible for the resonance frequency. The electric field's high intensity can be seen at the resonance frequency near the gap of the inner split ring and both copper rings, which represents the most sensitive area to the dielectric changes.Figure 7
Electric field distribution at 30 GHz due to (a) Port 1 and (b) Port 2.
(a)(b)As shown in Figures8(a) and 8(b), the surface current illustrates that the surface current’s clockwise direction is dominant in the inner ring, while the counterclockwise direction is dominant in the outer ring. The strength of the resultant surface current at the inner ring’s sides is comparatively higher than that of the outer ring at the resonance frequency of 30 GHz. Similar to electric field distribution, it can be seen from the surface current distributions that the inner ring is mainly responsible for the resonance frequency.Figure 8
Surface current distribution due to (a) Port 1 and (b) Port 2.
(a)(b)


## 4. Validation of Sensor

In this section, performance and sensitivity analysis is carried out on the designed sensor by realising the perturbation phenomenon, which leads to the change in quality factor and shift in the resonance frequency. The magnetic field’s stored energy is typically equal to the energy stored due to the electric field at the resonance frequency. Conversely, the magnetic and electric fields form a new resonance by altering the material under test (MUT) insertion on or near the resonator depending on the variation in permittivity, permeability, and MUT volume [33]. In this study, the MUT was introduced on the sensor covering its entire surface, as shown in Figure 9, where MUT can be termed as an overlayer.Figure 9
Placement of MUT on the surface of the sensor.


### 4.1. Impact of Sample Volume

Initially, the impact of the thickness of MUT on resonance was analysed by keeping the dielectric value constant at 2.454 (near the range of oils’ dielectric values) and varying its volume. It was done to find the minimum thickness sufficient to mitigate the sensor's cross-sensitivity to sample volume. Figure10 shows the percentage shift in resonance frequency when the MUT thickness is increased from 0.8 mm to 1.6 mm. It can be demonstrated that when the thickness is increased above 0.8, the percentage shift in the resonance frequency is lower than 0.2. Therefore, the suitability of the sensor can be determined as an instrument distinguishing the dielectric properties of MUT regardless of its volume.Figure 10
The percentage error in resonance shift versus thickness of MUT.In order to test the applicability of the sensor for oil chemical characterisation purposes, the sensor was investigated with the existence of the 5 mm thickness of MUT having different dielectric constants. The dielectric constants of castor oil, olive oil, tallow, corn oil, soybean salad oil, and conventionally rendered bacon fat were considered in simulation [34, 35]. The dielectric constant in oils is typically influenced by temperature and chemical characteristics such as oils' moisture contents. The dielectric properties and chemical characteristics (iodine contents, moisture and volatile ratio, and solid-fat index values) of the six oils considered in this study are represented in Table 2.Table 2
Chemical and dielectric properties of some commercial oils [34–36].
Oil nameIodine contentsMoisture and volatiles (%)Relative dielectric constant (εr′)Loss tangent (tanδ)Solid-fat indexBacon fat171 (gI2/100g)0.062.50.053223.6Tallow45 (gI2/100g)0.0752.4300.048526.3Castor oil85 (gI2/100g)0.24.470.032297.5Olive oil84 (gI2/100g)0.23.2540.033120Soybean salad oil121 (gI2/100g)0.042.5060.0539NoneCorn oil110 (gI2/100g)0.322.5260.0566NoneFigure11 depicts that, with the increase in dielectric constant, the resonance frequency shifted to the left side (lower frequencies) and demonstrated that a larger dielectric value causes a larger shift in the resonance frequency dip. Six types of oils were used to analyse the sensor's sensitivity that caused the realisation of perturbation in the sensor's transmission coefficient (S21). The resonance frequency of the sensor on the smallest value of dielectric constant occurred at 35.5 GHz (above resonance frequency) due to the comparatively large volume sample with a low value of permittivity and loss tangent.Figure 11
Perturbation in resonance frequency under MUT.Nevertheless, a significant shift in resonance frequency can be observed. There is a difference of 0.94 GHz seen in the resonance frequencies of bacon fat and tallow, and 2.11 GHz between olive oil and tallow's resonances.For further assessment, the transmission coefficient’s phase is used to distinguish the oil’s properties. The characteristics of a metamaterial can be demonstrated with the transition in phase at the resonance frequency. Similar to prior investigations, the impact of the MUT’s thickness was also analysed. The phase transition is depicted in Figure12, where distinct shifts are noticeable inside the red-box in the frequency range of 28 to 37 GHz for castor oil, olive oil, tallow, corn oil, soybean salad oil, and conventionally rendered bacon fat. On the other hand, there is a shallow difference found in the negative peak of resonance frequencies for corn oil and soybean salad oil due to their almost similar dielectric properties.Figure 12
The shift in the transition of phase under MUT on different cooking oils at the resonance frequency.Figure13 represents the percentage error in the transition of the shift in the transmission coefficient phase when MUT thickness is increased. It is validated that overlayer thickness provides less percentage error shift in the phase transition than the percentage error shift in the resonance frequency. According to these simulations, the proposed structure can be used in investigations of various oils. The proposed model can detect the low values of the dielectric constant regardless of the thickness of the samples.Figure 13
The percentages error in phase shift versus thickness of MUT.


### 4.2. Sensitivity Analysis

This part of the study explores the sensitivity of the metamaterial-based sensor in dielectric characterisations. The sensitivity analysis is calculated based on the results from full-wave electromagnetic simulations. When an oil sample is placed over the sensor’s surface, the shift in the negative peak of resonance frequency can be observed. The resonance frequency shift can be defined mathematically as in equation (10), where fr is the resonance frequency due to the MUT introduced and α is the resonance frequency without any sample, while fs is the difference between the new and original notch frequencies (shifted frequency) [37]:(10)fs=fr−α.By taking into account the differences in the highest and lowest dielectric constants of the materials under tests and respective frequency shifts observed, the sensitivity can be calculated using [37](11)S=limΔεh−εl⟶0Δfsh−ΔfslΔεh−Δεl.In equation (11), fsh and fsl represent the frequency shift on the placement of MUT with the highest and lowest dielectric constant, respectively, whereas εh represents the highest dielectric constant and lowest dielectric constant considered in this study is represented by εl since the highest and lowest value of dielectric constant exhibited by the MUTs considered in this study is 4.47 and 0.126, respectively.Therefore, the calculated sensitivity for the designed sensor is 1.12 GHz per unit change in dielectric constant as shown in Figure14. The sensitivity graph depicts that the trend is approximately linear with the rise in dielectric constant according to the frequency shifts. It is worth recalling that the sample’s dielectric constant assumed here is the maximum value, which occurs at the equilibrium between the electrical field and the molecular orientation [34]. Another point to remember is that each oil contains several fatty acids that differ in relative percentages depending on the type and origin of the oil; hence, a logical assessment essential to pure fatty acids and pure acids cannot be carried out easily. Despite that, there is a minimal difference in dielectric constants’ magnitude between the values observed under various temperature and frequency conditions.Figure 14
Sensitivity chart according to the dielectric constants.Nevertheless, working in the millimetre-wave contributes to tackling this issue as it is insignificantly affected by the temperature variations. Besides, mm-wave also offers a higher sensitivity to the minimal changes in the dielectric constant of oils according to the differing proportions of fatty acids and pure acids. Thus, the designed sensor can be assumed to be a promising candidate in sensing the chemical characteristics of oil based on the contents that vary its dielectric characteristics.Table3 describes the sensitivity of the designed sensor for the characterisation of oils compared to the previously designed sensors. The results based on a shift in resonance frequency often display a better accuracy for low values of dielectric constants. However, the accuracy in the designed resonator increases as the value of the dielectric constant decreases. This makes the mm-wave more sensitive to the dielectric changes, which is the key to the designed sensor’s relatively enhanced efficiency.Table 3
Comparison with the other designed resonators.
ReferenceSensor designMethod of sensingOperating frequency (GHz)Sensitivity (GHz)Application[26]SIWS11160.14Chemical[27]CSRRS212.30.1Alcohol[10]PSRRS211.90.2Bacterial growth[28]OmegaS2120.05Methanol[38]CSRR resonatorS112.50.5Glucose[39]M-CRRS212.40.06Liquids[40]PMWRS211.50.01LiquidsThis studyMM-SRRS21301.12Oils


## 4.1. Impact of Sample Volume

Initially, the impact of the thickness of MUT on resonance was analysed by keeping the dielectric value constant at 2.454 (near the range of oils’ dielectric values) and varying its volume. It was done to find the minimum thickness sufficient to mitigate the sensor's cross-sensitivity to sample volume. Figure10 shows the percentage shift in resonance frequency when the MUT thickness is increased from 0.8 mm to 1.6 mm. It can be demonstrated that when the thickness is increased above 0.8, the percentage shift in the resonance frequency is lower than 0.2. Therefore, the suitability of the sensor can be determined as an instrument distinguishing the dielectric properties of MUT regardless of its volume.Figure 10
The percentage error in resonance shift versus thickness of MUT.In order to test the applicability of the sensor for oil chemical characterisation purposes, the sensor was investigated with the existence of the 5 mm thickness of MUT having different dielectric constants. The dielectric constants of castor oil, olive oil, tallow, corn oil, soybean salad oil, and conventionally rendered bacon fat were considered in simulation [34, 35]. The dielectric constant in oils is typically influenced by temperature and chemical characteristics such as oils' moisture contents. The dielectric properties and chemical characteristics (iodine contents, moisture and volatile ratio, and solid-fat index values) of the six oils considered in this study are represented in Table 2.Table 2
Chemical and dielectric properties of some commercial oils [34–36].
Oil nameIodine contentsMoisture and volatiles (%)Relative dielectric constant (εr′)Loss tangent (tanδ)Solid-fat indexBacon fat171 (gI2/100g)0.062.50.053223.6Tallow45 (gI2/100g)0.0752.4300.048526.3Castor oil85 (gI2/100g)0.24.470.032297.5Olive oil84 (gI2/100g)0.23.2540.033120Soybean salad oil121 (gI2/100g)0.042.5060.0539NoneCorn oil110 (gI2/100g)0.322.5260.0566NoneFigure11 depicts that, with the increase in dielectric constant, the resonance frequency shifted to the left side (lower frequencies) and demonstrated that a larger dielectric value causes a larger shift in the resonance frequency dip. Six types of oils were used to analyse the sensor's sensitivity that caused the realisation of perturbation in the sensor's transmission coefficient (S21). The resonance frequency of the sensor on the smallest value of dielectric constant occurred at 35.5 GHz (above resonance frequency) due to the comparatively large volume sample with a low value of permittivity and loss tangent.Figure 11
Perturbation in resonance frequency under MUT.Nevertheless, a significant shift in resonance frequency can be observed. There is a difference of 0.94 GHz seen in the resonance frequencies of bacon fat and tallow, and 2.11 GHz between olive oil and tallow's resonances.For further assessment, the transmission coefficient’s phase is used to distinguish the oil’s properties. The characteristics of a metamaterial can be demonstrated with the transition in phase at the resonance frequency. Similar to prior investigations, the impact of the MUT’s thickness was also analysed. The phase transition is depicted in Figure12, where distinct shifts are noticeable inside the red-box in the frequency range of 28 to 37 GHz for castor oil, olive oil, tallow, corn oil, soybean salad oil, and conventionally rendered bacon fat. On the other hand, there is a shallow difference found in the negative peak of resonance frequencies for corn oil and soybean salad oil due to their almost similar dielectric properties.Figure 12
The shift in the transition of phase under MUT on different cooking oils at the resonance frequency.Figure13 represents the percentage error in the transition of the shift in the transmission coefficient phase when MUT thickness is increased. It is validated that overlayer thickness provides less percentage error shift in the phase transition than the percentage error shift in the resonance frequency. According to these simulations, the proposed structure can be used in investigations of various oils. The proposed model can detect the low values of the dielectric constant regardless of the thickness of the samples.Figure 13
The percentages error in phase shift versus thickness of MUT.


## 4.2. Sensitivity Analysis

This part of the study explores the sensitivity of the metamaterial-based sensor in dielectric characterisations. The sensitivity analysis is calculated based on the results from full-wave electromagnetic simulations. When an oil sample is placed over the sensor’s surface, the shift in the negative peak of resonance frequency can be observed. The resonance frequency shift can be defined mathematically as in equation (10), where fr is the resonance frequency due to the MUT introduced and α is the resonance frequency without any sample, while fs is the difference between the new and original notch frequencies (shifted frequency) [37]:(10)fs=fr−α.By taking into account the differences in the highest and lowest dielectric constants of the materials under tests and respective frequency shifts observed, the sensitivity can be calculated using [37](11)S=limΔεh−εl⟶0Δfsh−ΔfslΔεh−Δεl.In equation (11), fsh and fsl represent the frequency shift on the placement of MUT with the highest and lowest dielectric constant, respectively, whereas εh represents the highest dielectric constant and lowest dielectric constant considered in this study is represented by εl since the highest and lowest value of dielectric constant exhibited by the MUTs considered in this study is 4.47 and 0.126, respectively.Therefore, the calculated sensitivity for the designed sensor is 1.12 GHz per unit change in dielectric constant as shown in Figure14. The sensitivity graph depicts that the trend is approximately linear with the rise in dielectric constant according to the frequency shifts. It is worth recalling that the sample’s dielectric constant assumed here is the maximum value, which occurs at the equilibrium between the electrical field and the molecular orientation [34]. Another point to remember is that each oil contains several fatty acids that differ in relative percentages depending on the type and origin of the oil; hence, a logical assessment essential to pure fatty acids and pure acids cannot be carried out easily. Despite that, there is a minimal difference in dielectric constants’ magnitude between the values observed under various temperature and frequency conditions.Figure 14
Sensitivity chart according to the dielectric constants.Nevertheless, working in the millimetre-wave contributes to tackling this issue as it is insignificantly affected by the temperature variations. Besides, mm-wave also offers a higher sensitivity to the minimal changes in the dielectric constant of oils according to the differing proportions of fatty acids and pure acids. Thus, the designed sensor can be assumed to be a promising candidate in sensing the chemical characteristics of oil based on the contents that vary its dielectric characteristics.Table3 describes the sensitivity of the designed sensor for the characterisation of oils compared to the previously designed sensors. The results based on a shift in resonance frequency often display a better accuracy for low values of dielectric constants. However, the accuracy in the designed resonator increases as the value of the dielectric constant decreases. This makes the mm-wave more sensitive to the dielectric changes, which is the key to the designed sensor’s relatively enhanced efficiency.Table 3
Comparison with the other designed resonators.
ReferenceSensor designMethod of sensingOperating frequency (GHz)Sensitivity (GHz)Application[26]SIWS11160.14Chemical[27]CSRRS212.30.1Alcohol[10]PSRRS211.90.2Bacterial growth[28]OmegaS2120.05Methanol[38]CSRR resonatorS112.50.5Glucose[39]M-CRRS212.40.06Liquids[40]PMWRS211.50.01LiquidsThis studyMM-SRRS21301.12Oils


## 5. Conclusion

This study focuses on designing the metamaterial-based split-ring resonator to detect oils and their chemical characteristics. The sensing characteristics of the proposed sensing structure are provided using the transmission coefficient and its phase. The sensor’s sensitivity from the results can be estimated to be 1.12 GHz per unit increase in the dielectric constant. The design’s benefits and efficiency are significant for identifying minimal changes in the sample's dielectric constant regardless of the sample’s volume and impurities and temperature variations. A significant shift in the transmission coefficient (amplitude and phase) behaviour and linearity of sensing offer a novel sensing mechanism vital for other liquid-sensing applications, such as blood and water.



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*Source: 5520268-2021-03-13.xml*