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Meta-material
research at NIT Trichy
Updated March
28, 2010
Click
here to go to our other page on metamaterials
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here to go to NIT Trichy's Microwaves101 page
New for April 2010! This
work was contributed by Vidyalakshmi M. R., a Master of Science
(by Research) student under the guidance of Dr. S. Raghavan, at
NIT Trichy.
Introduction
Metamaterials are artificially engineered
materials which display negative permeability and permittivity over
a certain range of frequency. First proposition of this was done by
Prof. V.G. Veselago in 1968. Since realization of such materials was
difficult at that time, there was very little progress in this field.
But the first breakthrough was given by J.B. Pendry et al in
2000 by showing an array of two circular concentric rings and thin
wire could exhibit the metamaterial property. The rings had a gap
between them and hence the structure was named split ring resonator
(SRR). We know that the lumped equivalent circuit of the SRR is an
LC circuit. The various forms of SRR and complementary split ring
resonator (CSRR) and their equivalent circuits are given in detail
by Marques et al. Then in 2002, C. Caloz and T. Itoh gave the transmission
line equivalent of metamaterials.
Summary
A new structure of triangular
split ring resonator with edge-coupling is proposed in [1]. The
structure consists of two equilateral concentric triangles made
of metal with dielectric medium (Arlon Cu-clad substrate of =2.43)
filled in the gaps. When the structure below is excited with a perpendicular
magnetic field, the current flows through the rings gives rise to
inductance and the capacitance arises out of the gap between the
two rings.
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Figure
1. Proposed structure
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Figure
2. Unit cell quivalent circuit
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Hence the lumped equivalent circuit
of this structure becomes an LC tank circuit. The advantage of this
structure includes the reduction in size of the SRR and the wide
range of resonant frequencies possible. The layout or the structure
with the equivalent circuit and the Computer Aided Design model
(CAD) design are presented. The Lorentz-Drude model had been derived
for proving the negative values of effective permeability and permittivity.
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| Figure 3a. Real
part of effective permeability versus frequency (GHz) |
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Figure 3b. Imaginary
part of effective permeability versus frequency (GHz) |
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| Figure 4a. Real
part of effective permittivity versus frequency (GHz) |
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Figure 4b. Imaginary
part of effective permittivity versus frequency (GHz) |
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| Figure 5. Resonant
frequency f0 (Hz) versus conductor width w (m) |
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Figure 6. Resonant
frequency f0 (Hz) versus dielectric width d (m) |
The variation of the resonant
frequencies with respect to the conductor and dielectric width is
also shown above in Figures 5 and 6. It also brings about the reduction
in size to 46% as compared to the existing TSRR. There is also a
good match with the values obtained theoretically and by simulation.
Another form of metamaterial
is the planar version or the transmission line version known as
left-handed transmission line (LH TL). But, realizing a pure LH
TL was difficult because of the parasitic inductance and capacitance.
So, we instead use a composite right left handed transmission line
(CRLH TL). An accurate CAD model of the CRLH TL is proposed [2].
It could be used for both balanced as well as unbalanced CRLH TL.
The least-mean-square (LMS) error and the relative error plots between
the theoretical and practical values are also presented below.
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| Figure 7. Least-mean-square
error of group velocity plotted versus frequency (GHz) |
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Figure 8. Relative
error of phase constant plotted versus frequency (GHz) |
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| Figure 9. Least-mean-square
error of characteristic impedance plotted versus frequency (GHz) |
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It was observed that the phase
velocity is negative and the group velocity is positive as it is
the group velocity that deals with power flow. The CAD model accurately
estimates all the secondary constants of the CRLH TL. Results shown
in Figures 7-9 are in good agreement between the theoretical and
obtained values.
Optimization before fabrication
will help choose the right size and also would reduce fabrication
cost. We shall present a work in which the size of the spilt ring
resonator could be optimized for a particular resonant frequency
by artificial neural networks and by genetic algorithm [3]. Comparison
of both the methods is also presented. For the ANN method, a feed-forward
back propagation network and binary genetic algorithm type in genetic
algorithm were used.
ANN performance curves are shown
in Figure 11.
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| Figure 10. Circular
split ring resonator with the dimensions considered for optimization-
external radius, conductor width and the dielectric width |
Figure 11. Testing
errors and training errors |
TABLE I. Results of optimization
with binary
genetic algorithm for circular SRR
| Resonant Frequency (GHz) |
5.15 |
7.6 |
| External radius rext
(mm) |
2.265 |
2 |
| Conductor width c (mm) |
0.254 |
0.2 |
| Dielectric width
d (mm) |
0.179 |
0.2 |
| Resonant frequency obtained
(GHz) |
5.5008 |
7.58 |
| Fitness index value |
0.0001 |
0.0026 |
The fitness index value is taken
to be absolute relative error between the desired and the calculated
resonant frequencies. The external radius, the conductor width and
the dielectric spacing between the two rings are taken as the parameters
for optimization minimizing the error function to get the best dimensions
for the given resonant frequency. In both cases as shown from Figure
11 and Table. I, error was found to well within the tolerable limits.
We have also presented an artificial
neural network (ANN) model of a complementary circular split ring
resonator [4]. Taking advantage of Babinet's principle, we take
a circular ring resonator and develop an ANN model for determination
of its resonant frequency. Various algorithms of Levenberg-Marquardt
scaled conjugate gradient and quasi newton methods are used to train
the neural network and the results have been compared.

Fig.12. Structure of circular
complementary SRR with the dimensions of the slot-external, internal
radius, width of the conductor and dielectric slot.
TABLE II. Resonant frequency calculated by all three algorithms
for = 2.6mm, s=0.5mm and w=0.2mm
| Algorithm |
Resonant frequency (GHz) |
Mean square error |
| Levenberg-Marquardt algorithm |
6.010 |
1.934 x 10-9 |
| Scaled Conjugate gradient
algorithm |
6.0099 |
1.00 x 10-8 |
| Quasi Newton algorithm |
6.0077 |
5.2900 x 10-6 |
The ANN model for circular CSRR
was developed using a three hidden layer feed forward back propagation
network with the inputs as the dimensions of the CSRR and output
being the resonant frequency using three training algorithms and
was illustrated that Levenberg-Marquardt method of training algorithm
was the best suited as it gave minimal error.
The three optimization techniques
namely genetic algorithm (GA), artificial neural networks (ANN)
and hybridization of GA-ANN is applied to the case of square split
ring resonator in [5] and the obtained results are compared. In
all the cases, the size of the split ring resonator is optimized
in order to obtain minimum error in resonant frequency. There are
many types of GA and ANN. Here, binary genetic algorithm and feed
forward backpropagation ANN is chosen. A new method of hybridization
is presented here which gives effective results.

Figure 13. Structure of square split ring resonator
Results obtained through genetic
algorithm (GA)
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| Figure 14. Optimized
values of conductor width and dielectric spacing of SSRR with
respect to resonant frequency |
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Figure 15. Optimized
value of side length of the SSRR with respect to resonant frequency |
Results obtained through artificial
neural network (ANN)
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| Figure 16. Values
of side length of the SSRR obtained at various frequencies |
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Figure 17.Values
of conductor width at various frequencies |
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| Figure 18. Values
of dielectric spacing between the rings |
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TABLE. III. Dimensions of the
SSRR obtained as a result of hybridization.
Resonant
frequency
(GHz) |
a (mm) |
w (mm) |
d (mm) |
Obtained
resonant
frequency
(GHz) |
Absolute
Error |
| 1.0 |
6.2913 |
0.6323 |
0.6894 |
0.9995 |
0.0008 |
| 1.5 |
4.7410 |
0.3041 |
0.7167 |
1.4988 |
0.0008 |
| 2.0 |
4.4614 |
0.4114 |
0.9604 |
2.0006 |
0.0003 |
| 3.0 |
3.4066 |
0.4211 |
0.8575 |
3.0015 |
0.0005 |
| 4.0 |
3.2414 |
0.6182 |
0.9525 |
4.0176 |
0.0044 |
| 5.0 |
3.1144 |
0.7589 |
0.9375 |
5.0023 |
0.0005 |
| 6.0 |
3.1652 |
0.9085 |
0.9648 |
6.0047 |
0.0008 |
The error is also minimal in
hybridization structure as compared to both the above techniques
being used separately which are evident from the above Table.III.
TABLE IV. Comparison between the optimization techniques presented.
| Optimization Technique |
Accuracy |
Execution
time |
Memory
requirement |
| BGA |
Good |
Large |
Large |
| ANN |
Less accurate |
Medium |
Less |
Hybrid
GA-ANN |
Best |
Large |
Medium |
From Table IV, we understand
the trade-off between the criteria of accuracy, execution time and
memory requirement. Depending on the need, we are able to select
the technique needed for the problem.
A reconfigurable triangular split
ring resonator using MEMS technology has also been proposed in [6].
The gap in the outer ring of the triangular resonator can be adjusted
with the help of control actuators for each side of the triangle
thus making the resonant frequency shift. This can be used in various
potential applications.
Conclusion
Thus a new structure of triangular
split ring resonator was proposed and the Lorentz-Drude model was
also demonstrated along with the CAD model. The CRLH TL CAD model
was also developed from the basic equations with minimal error.
A series of optimization techniques of GA, ANN and its hybridization
were applied to various resonators and its results were studied.
A small proposal on reconfigurable MEMS split ring resonators was
also made.
References
1.Vidyalakshmi. M.R and Dr. S.
Raghavan," A CAD Model of Triangular Split Ring Resonator Based
on Equivalent Circuit Approach", presented at IEEE AEMC 2009,
Kolkata.
2. Vidyalakshmi. M.R and Dr.
S. Raghavan, "CAD Model of a Composite Right Left Handed Transmission
Line", ICMARS 2009, Jodhpur.
3. Vidyalakshmi. M.R and Dr.
S. Raghavan,"Optimization of Circular Split Ring Resonator
by Artificial Neural Networks and Genetic Algorithm", IEEE
ICCCNT 2010, Karur. (Results awaited).
4. Vidyalakshmi. M.R and Dr.
S. Raghavan, "A CAD Model of Complementary Circular Split Ring
Resonator Using Artificial Neural Networks", ADVICE 2010, Chandigarh.
5. Vidyalakshmi. M.R and Dr.
S. Raghavan, "Comparison of Optimization Techniques for Square
Split Ring Resonator", IEEE ITSIM 2010. (Accepted).
6. Vidyalakshmi. M.R and Dr.
S. Raghavan,"Reconfigurable Triangular split ring resonator
with artificial neural network and Genetic algorithm analysis",
Metamaterials 2010, Germany. (Results awaited).
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