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Design considerations for an acoustic MEMS filter


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Microelectromechanical system (MEMS) devices exhibit characteristics that make them ideal for use as filters in acoustic signal processing applications. In this study, a MEMS filter is constructed from multiple mechanical structures (e.g. cantilever beams) and a differential amplifier. The outputs of the structures are then processed by the differential amplifier to achieve the filter functionality. The important parameters of the mechanical structures and the MEMS filters are investigated using a simulation approach, including the structural damping factors, the normalized frequency ratios (NFR) of the MEMS filters, the number of mechanical structures required to construct individual MEMS filter, and the spatial arrangement of the multiple mechanical structures relative to the differential amplifier. Furthermore, the mutual coupling effects among these parameters are evaluated by detailed simulations. The simulation results show that a plot of the NFR versus the damping factors can be used to determine the optimal parameters for the mechanical structures. The number of mechanical structures required to construct a MEMS filter must equal 2n , with n as an integer, and these mechanical structures should be arranged as a geometric series with increasing resonant frequencies and with specific connections to the differential amplifier.
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Design considerations for an acoustic MEMS filter
S.-H. Shen, W. Fang, S.-T. Young
Abstract Microelectromechanical system (MEMS) devices
exhibit characteristics that make them ideal for use as filters
in acoustic signal processing applications. In this study, a
MEMS filter is constructed from multiple mechanical
structures (e.g. cantilever beams) and a differential ampli-
fier. The outputs of the structures are then processed by the
differential amplifier to achieve the filter functionality. The
important parameters of the mechanical structures and the
MEMS filters are investigated using a simulation approach,
including the structural damping factors, the normalized
frequency ratios (NFR) of the MEMS filters, the number of
mechanical structures required to construct individual
MEMS filter, and the spatial arrangement of the multiple
mechanical structures relative to the differential amplifier.
Furthermore, the mutual coupling effects among these
parameters are evaluated by detailed simulations. The
simulation results show that a plot of the NFR versus the
damping factors can be used to determine the optimal
parameters for the mechanical structures. The number of
mechanical structures required to construct a MEMS filter
must equal 2
, with nas an integer, and these mechanical
structures should be arranged as a geometric series with
increasing resonant frequencies and with specific connec-
tions to the differential amplifier.
A crucial aspect for many signal-processing techniques,
including acoustic signal processing, is to divide the signal
into multiple frequency bands. With its powerful computing
capabilities, the digital signal processor (DSP) now forms
the core for such techniques [1, 2]. However, contemporary
DSPs still present limitations for some applications, in terms
of their power consumption and computation time. Where
these factors are crucial, the electromechanical filter – as a
passive device – provides a viable alternative. Electrome-
chanical filters have been well known for at least 5 decades
[3]. They can be used to extract signals from a specific fre-
quency band, and hence provide functionality similar to
electrical filters. Electromechanical filters also provide
excellent aging and thermal-stability characteristics [4].
With the introduction of microelectromechanical systems
(MEMSs), the application of electromechanical filters to
signal processing has become more feasible, from high-
frequency to radio-frequency regions [5–8]. An electrome-
chanical filter bank constructed from silicon beams for a
high-frequency communication system was recently inves-
tigated [9]. Each filter in this filter bank comprised a single
beam structure with a sharp frequency response. A sharp
frequency response always results in poor linearity for the
filter passband signals.
This study proposes a novel MEMS filter for acoustic
signal processing. Its characteristics and design param-
eters were investigated by simulations of filters com-
prising multiple mechanical structures. The simulation
approach enabled complete characterization of the crit-
ical parameters of the mechanical structures and the
MEMS filters, such as the structural damping factors, the
normalized frequency ratios (NFRs) of the MEMS filters,
the number of mechanical structures required to con-
struct an individual MEMS filter, and their spatial
arrangement. The simulations demonstrate that the
proposed MEMS filter can be implemented, and that it
would be an effective device for acoustic signal-pro-
cessing applications, such as in miniature hearing aids.
Theory and methods
Theory on MEMS filters
A mechanical structure has a preferred vibrating mode
referred to as resonance that depends on the configuration
of the structure and its mechanical properties. This
vibrating mode can be characterized by the magnification
factor, which is taken as a normalized vibration amplitude
in this paper, and phase versus frequency in the first mode
of vibration, expressed as Eqs. (1) and (2), respectively
Microsystem Technologies 10 (2004) 585–591 ÓSpringer-Verlag 2004
DOI 10.1007/s00542-003-0335-6
Received: 20 November 2002 / Accepted: 19 September 2003
S.-H. Shen, S.-T. Young (&)
Bioelectronics Laboratory, Institute of Biomedical Engineering,
National Yang Ming University 155, Sec. 2, Li-Nung St,
Shih-Pai, Taipei 112, Taiwan
W. Fang
Micro Device Laboratory, Department of Power Mechanical
Engineering, National Tsing Hua University, Hsinchu 300,
This material is based (in part) upon work supported by the
National Science Council (Taiwan) under Grant NSC 91–2213-
E-010-008 and Delta Electronics Foundation. The authors would
like to express their appreciation to the NSC Central Regional
MEMS Center, Semiconductor Research Center of National Chiao
Tung University (Taiwan), and the NSC National Nano Device
Laboratories (Taiwan) in providing experimental facilities.
Magnification factor ð1Þ
5Phase shift ð2Þ
where X
is the amplitude of the steady-state vibration,
Dsis the static displacement when the exciting force F
is slowly applied to the mechanical structure, kis the
spring constant of the structure, xnand xare the res-
onance and operating frequency of the structure, and f
is the damping factor. In this study, micromachined
cantilevers were employed to detect the acoustic waves.
Hence, the F
/k of these cantilevers with lin length and t
in thickness can be expressed as Eq. (3) [11].
where pis the acoustic pressure, and Eis the Young’s
modulus of cantilever. By dividing X
into F
/kusing pre-
signal-processing tools, such as amplifiers or programs, we
can easily acquire the normalized signals.
The proposed MEMS filter is shown in Fig. 1, which
consists of multiple mechanical structures with sensing
circuits and a differential amplifier. The MEMS filter had
designed with a bandpass characteristic. The mechanical
structures respond to acoustic stimulation, according to
their particular frequency responses, and cause the
sensing circuits to produce the associated electrical sig-
nals. The differential amplifier processes the electrical
signals picked up from some parts of the mechanical
structures. The resulting signal can be a filtered signal
when the mechanical structures are designed with
appropriate frequency responses and their outputs are
coupled in the differential amplifier in an appropriate
arrangement. For a MEMS filter with multiple mechani-
cal structures, the output of each mechanical structures
is connected to either a positive or a negative port of the
differential amplifier through a switching mechanism,
which is called as a positive and negative switch (PNS),
as shown in Fig. 1a. It is obvious that the variety of
possible PNS arrangements will increase with the num-
ber of mechanical structures in a MEMS filter. Besides,
the MEMS filter can be implemented by, for example,
micromachined cantilevers and piezoresistive sensing
circuitry as shown in Fig. 1b.
For unobvious effects from higher-order resonance
modes and convenient illustration, we only considered the
first resonance mode of the mechanical structure. Com-
bining Eqs. (1) and (2), the vibration of a mechanical
structure can be presented by means of a cosine wave
equation, x
cos 2pxtþtan12fx
The suffix irepresents the label of an individual structure.
Multiple mechanical structures can be designed such that
their resonant frequencies increase sequentially, with their
responses x1;x2;...;xicoupled together to implement a
MEMS filter. The general response of such a MEMS filter
can be presented as
xtotal ¼xiþþxiMxiNx1
Performance definition and evaluation of MEMS filter
We evaluated the performance of the MEMS filter by
measuring certain filter parameters, including the pass-
band ripples and the filter shape. We wanted the passband
ripple to be less than 1 dB, and in any case ensure that it
did not exceed 3 dB to avoid violation of the cutoff-
frequency definition. The asymmetric filter shape is
assessed by a defined shape factor. The shape factor of the
MEMS filter was divided into the lower shape factor (LSF)
and higher shape factor (HSF), which describe either side
of the bandpass filter’s shape. LSF and HSF are defined in
Fig. 1a, b. Illustrations of MEMS filters: aa concept diagram of
the proposed MEMS filter; ba practical MEMS filter with
micromachined cantilevers and piezoresistive sensing circuitry
Eqs. (6) and (7), respectively, and the related definitions
are illustrated in Fig. 2. According to our definitions, a
MEMS filter with lower LSF and HSF values has a sharper
passband, and the filter is more symmetric when its LSF
and HSF values are similar:
LSF ¼The logarithmic bandwidth between f0and fL;40dB
The logarithmic bandwidth between f0and fL
¼log f0
ðÞlog fL;40dB
log f0
ðÞlog fL
ðÞ ð6Þ
HSF ¼The logarithmic bandwidth between f0and fH;40dB
The logarithmic bandwidth between f0and fH
¼log fH;40dB
log f0
log fH
ðÞlog f0
ðÞ ð7Þ
where f
is the lowest resonant frequency and f
is the
highest resonant frequency of the structures comprising
the MEMS filter; and f
is the center frequency, equal to the
average of f
and f
;fL;40dB and fH;40dB are the upper and
lower frequencies at which 40-dB attenuations occur.
Simulation approach
Using Eqs. (4) and (5), we developed simulation programs
to explore the optimized design parameters of the pro-
posed MEMS filter, using the following criteria:
(a) The damping factors of the mechanical structures are
the first parameters to be investigated, since their
combination will determine the passband ripple and
resonant frequency of the MEMS filter. We simulated
different individual damping factors and different
combined ratios.
(b) The bandwidth is the second important parameter for
the MEMS filter. The bandwidth investigation is
achieved through the NFR. The NFR of a MEMS filter
constructed by multiple mechanical structures with
increasing resonant frequencies f
is described
by the normalized interval between the lowest resonant
frequency f
(= f
) and the highest resonant frequency
(= f
) of the MEMS filter. The NFR is defined as
NFR ¼Center frequency
The bandwidth between fHand fL
The center frequency f
is the average of f
and f
the definition, the NFR is inversely proportional to the
bandwidth for the same center frequency. How the
NFR effects the MEMS filter was also fully investigated
by the simulation program.
(c) Once the desired damping factors and filter bandwidth
were determined, the mechanical structures compris-
ing the MEMS filter were determined by simulations.
Different relationships between these structures and
the differential amplifier were also analyzed. These
were implemented by configuring the PNS shown in
Fig. 1. For clarity of illustration, when the PNS links
the mechanical structure to the positive port of the
differential amplifier, the structure is symbolized as a
positive sign (‘‘+’’); whereas when the PNS switches to
the negative port, the structure is symbolized as a
negative sign (‘‘)’’). The sequential presentation of
these signs in the MEMS filter indicates the mechanical
structures with increasing resonant frequencies.
(d) The effects of the individual parameters on the char-
acteristics of the MEMS filter are not independent, and
hence their mutual effects on each other were also
investigated in the study. The simulations analyzed the
relationships between the damping factors and the
NFR to explore their trade-off whilst maintaining an
acceptable passband ripple. The simulations also
thoroughly investigated the effects on the filter shape
factors of NFR and number of structures simulta-
neously to determine a reasonable number of
mechanical structures for the MEMS filter.
Simulation results
The results of simulations into the effects of the damping
factor, the NFR, and the number of mechanical structures
comprising the MEMS filters are presented in Sects.
3.1–3.4, respectively. For illustrative simplicity, 2-structure
MEMS filters are used to show the effects of damping
factors and NFR in Sects. 3.1 and 3.2. The simulation
results for multiple-structure MEMS filters are only
depicted with an NFR of 2.50 and a damping factor of
0.123; for these values the 2-structure MEMS filter exhibits
a passband ripple of only 1 dB in Sect. 3.3. The resonant
frequencies of adjacent structures are arranged as a
geometric series in multiple-structure filters. The mutual
relationships among the parameters and performance of
MEMS filters are then illustrated in Sect. 3.4.
Effects of damping factor
Figure 3 illustrates how the damping factors of the struc-
tures affect the frequency response of the MEMS filter with
center frequency, f
, 1000 Hz. In Fig. 3a, the damping
factors of two structures, f
and f
, were assigned values
of 0.123 and 0.984 (f
), 0.984 and 0.123 (f
Fig. 2. Illustration of the definitions of MEMS filter parameters
and 0.123 and 0.123 (f
), respectively. Figure 3b
shows the response of MEMS filters that were comprised of
two structures with equal damping factors of 0.083, 0.123,
and 0.200. The resulting LSF, HSF, and passband-ripple
values for these MEMS filters were 6.37, 7.45, and 3 dB;
7.35, 8.38, and 1 dB; and 9.28, 9.56, and 0 dB; respectively.
Effects of normalized frequency ratio
Figure 4 shows the effect of different NFRs on the fre-
quency response of MEMS filters. Figure 4a shows that
NFR values of 1.69, 2.50, and 3.90 produce MEMS filters
with LSF, HSF, and passband-ripple values of 7.36, 8.39,
and 3 dB; 7.35, 8.38, and 1 dB; and 10.16, 11.04, and 0 dB;
respectively. Figure 4b illustrates the frequency responses
of different MEMS filters that have center frequencies of
500 Hz, 1000 Hz, and 3000 Hz, but the same NFR and
damping factors of 2.50 and 0.123, respectively. These
MEMS filters produce identical LSF, HSF, and passband-
ripple values, of 7.35, 8.38, and 1 dB, respectively.
Effects of number of mechanical structures and their
Figure 5 illustrates the frequency responses of 4-structure
MEMS filters, whose structures had resonant frequencies
of 800 Hz, 916 Hz, 1048 Hz, and 1200 Hz (i.e., f
= 800 Hz
and f
= 1200 Hz). The figure shows the responses of the
4-structure MEMS filters for only some of the possible
structure arrangements, which were arranged with equal
structures to connect to both ports of the differential
amplifier. The LSFs, HSFs, and passband-ripple values of
the 4-structure MEMS filters are 4.35, 5.10, and 0.32 dB, for
the ‘‘þþ’’ PNS arrangement; 7.04, 8.05, and 22.95 dB
for ‘‘þþ’’; and 6.75, 7.73, and 0 dB for ‘‘þþ’’.
Fig. 3a, b. The effect of damping factors on the frequency re-
sponses of MEMS filters comprised of two structures with: a
different damping factors and, bthe same damping factor
Fig. 4a, b. The effect of NFR on the frequency responses of
MEMS filters: awith various NFRs but with the same center
frequency and damping factor; bwith different center frequency
but with the same NFRs and damping factors
Fig. 5. The frequency responses of 4-structure MEMS filters with
different structure arrangements
Figure 6 shows the best frequency responses of 6-, 8-,
12-, and 16-structure MEMS filters, for PNS arrangements
of ‘‘þþþ’’, ‘‘þþþþ’’,
‘‘þþþþþþ’’, and
‘‘þþþþþþþþ’’, respectively. The
LSF and HSF values for 8-, 12-, and 16-structure MEMS
filters were 3.02 and 3.47; 2.88 and 3.3; and 2.46 and
2.78; respectively, while the passband-ripple values were 1
dB, 0 dB, and 3.43 dB, respectively. The responses of the
8- and 12-structure MEMS filters intersect around 380 Hz
and 2650 Hz. Due to the serious asymmetry to the central
frequency axis of its response, the passband-ripple values
and shape factors cannot be defined in the 6-structure
MEMS filter.
Figure 7 depicts the responses of 8- and 16-structure
MEMS filters with different center frequencies and the
same NFR of 2.5. The center frequencies were set as
500 Hz, 1000 Hz, and 3000 Hz, and the PNS arrangements
were set as ‘‘þþþþ’’ and
‘‘þþþþþþþþ’’. The LSF, HSF,
and passband-ripple value of the 8-structure MEMS filters
are 3.02, 3.47, and 1 dB, and those of the 16-structure
MEMS filters are 2.46, 2.78, and 3.43 dB.
Mutual effects among crucial parameters
For passband-ripple values of 1 dB and 3 dB, Fig. 8 shows
that the damping factors and the NFRs were inversely
relationships irrespective of the number of the mechanical
structures used to construct the MEMS filter. The mutual
relationship of NFRs in 4-, 8-, and 16-structure MEMS
filters, and damping factors and filter shape factors are
illustrated in Fig. 9 for 1-dB and 3-dB passband ripples.
These figures show the trade-off between the shape factors
LSF and HSF with different desired NFRs.
As designing a MEMS filter constructed from mechanical
structures, it is necessary to define its center frequency,
filter bandwidth, acceptable passband ripple, and desired
filter shape. The characteristics of a MEMS filter are
affected by many parameters, including the damping fac-
tors of the mechanical structures, the NFRs, and the
number and arrangement of mechanical structures con-
stituting the filter. This study investigated these parame-
ters by simulating various MEMS filters, and the results
provide certain guidelines for the design of such filter.
Fig. 6. The best frequency responses in 6-, 8-, 12-, and 16-
structure MEMS filters
Fig. 7a, b. The frequency responses of MEMS filters constructed
by multiple structures with the same damping factor and
NFR, but various center frequencies: a8-structure MEMS filters;
b16-structure MEMS filters
Fig. 8. The relationship between NFRs and damping factors with
differing numbers of structures and passband-ripple values
The damping factor of the mechanical structure is one
of these important parameters. The simulation results
showed that the damping factors of the mechanical
structures should be as similar as possible to ensure the
symmetry of the frequency response of the MEMS filter.
When a MEMS filter is made from structures with unbal-
anced damping factors, its filter profile will skew to the
frequency response of the structure with the lower
damping factor. The more unbalanced the damping factors
are, the more asymmetric the filter profile appears; and in
extreme cases the filter may lose its filtering functionality,
with undefined LSF and HSF values. Moreover, appropri-
ate damping factors are evidently necessary: a larger
damping factor decreases the passband ripples but
enlarges the LSF and HSF, when NFR is kept constant;
whereas a small damping factor produces a MEMS filter
with small LSF and HSF. However, damping factors that
are too small will produce a MEMS filter with individual
mechanical structures that do not exhibit mutual coupling.
The NFR of the MEMS filter is another important
parameter – it essentially determines the bandwidth of the
MEMS filter. Increasing the NFR both narrows the filter
bandwidth and makes the passband ripple smaller. The
simulation results also revealed the interesting character-
istic that MEMS filters with identical NFRs and damping
factors will have identical passband ripples and shape
factors, even though they can have different center
frequencies. This will simplify the design of MEMS filters
for use at different frequencies. Furthermore, the NFR and
the damping factor have mutual effects on the MEMS filter.
The simulation results (in Fig. 8) show that the damping
factor and the NFR are inversely related, which is impor-
tant information when designing for the allowable pass-
band ripple and desired shape factor of the MEMS filter: to
decrease the bandwidth of a MEMS filter it is necessary to
decrease the damping factor whilst simultaneously
increasing the NFR.
The number and arrangement of the structures is
especially important in the construction of multiple-
structure MEMS filters. The simulations showed that the
mechanical structures in a MEMS filter must be arranged
in a mirror relationship to the differential amplifier (e.g.
‘‘þþþþ’’ for eight structures and
‘‘þþþþþþþþ’’ for 16 structures.
This arrangement can be explained with reference to logic.
A 2-structure MEMS filter has its basic arrangement as
‘‘þ’’ (or ‘‘þ’’). For a 4-structure MEMS filter, its best
PNS arrangement is ‘‘þþ’’, which can be considered
as two adjacent subsets, ‘‘þ’’ and ‘‘þ’’. Each subset can
be taken as a new structure, with the subset ‘‘þ’’ being
regarded as the inverse of ‘‘þ’’. The combination of the
two subsets can then be considered as another 2-structure
MEMS filter arranged with the mirror relation ‘‘þ’’.
Following this arranging rule, the best arrangement of an
8-structure MEMS filter is then derived from the combi-
nation of subset ‘‘þþ’’ and its inverse ‘‘þþ’’, and
the best arrangements of the 16-structure MEMS filter is
predicted as the combination of ‘‘þþþþ’’ and
‘‘þþþþ’’. The mirror relation in this best PNS
arrangement implies that the number of structures in a
MEMS filter must be equal to 2
, where nis an integer.
This also means that the train of the arrangement can be
folded up until it has its basic arrangement as ‘‘þ’’.
Although the multiple-structure MEMS filter can be
regarded as a pair of structures that process the incoming
signals, each virtual structure exhibits damping that is
different from that exhibited by the preceding structure
combination; therefore, this study has not provided a
complete comparison between 2-structure and multiple-
structure MEMS filters.
The mutual effects of all parameters on the MEMS filters
were very important when designing the filter proposed in
the study. The damping factor of each structure within the
filter is determined by both structural and environmental
factors, with changes in environmental conditions being
more significant at micron dimensions. The squeezed-film
effect is often taken as the critical solution for tuning the
damping factors in microstructures. Based on the
squeezed-film theory, the gap depth and covered area of
the microstructure – as controlled by the fabrication
process – enables any damping factors to be obtained; for
instance, the stationary structures proposed in [12] can be
employed to tune the quality factor of bulk micro-
machined structures by incorporating with the squeezed-
film damping. However, using a single damping factor for
all the structures is expected to simplify the fabrication of
the proposed MEMS filter on a wafer. In this case, the
Fig. 9a, b. The relationship between NFR and shape factors for a
response: awith a 1-dB passband ripple and different numbers of
structures and, bwith a 3-dB passband ripple and different
numbers of structures
number of structures becomes as a major selectable
parameter for obtaining the desired passband ripple and
bandwidth. Figure 8 shows that with a fixed damping
factor, increasing the number of structures will increase
NFR and decrease passband ripple, except in the 2-struc-
ture MEMS filter. Increasing NFR decreases the band-
width. A large number of structures will also decrease LSF
and HSF values, as shown in Fig. 9, and the decreasing
LSFs and HSFs produces a sharper filter. A large number
of structures will then enhance the filter performance.
Another interesting phenomenon is that increasing NFR
will increase the LSF but decrease the HSF. This trend
brings the LSF and HSF closer, producing a more sym-
metrical filter. However, the advantages of increasing the
number of mechanical structures do not continue indefi-
nitely: too many mechanical structures will complicate the
filter fabrication and decrease the yield rate. We therefore
propose that an 8-structure MEMS filter represents the
best compromise.
Summary and conclusions
This paper has proposed the design of a MEMS filter and
investigated its important parameters using a simulation
approach. In theory, all the requirements of MEMS filters
can be satisfied through the selection of appropriate
damping factors of the mechanical structures, NFR, and
the number and arrangement of the mechanical structures
that constitute the filter. For individual MEMS filter with
multiple mechanical structures, the structures should have
similar damping factors. The NFR of the MEMS filter is
another important parameter, which determines the filter
shape and bandwidth for different center frequencies.
Furthermore, the simulation results show that the number
of mechanical structures required to construct a MEMS
filter must be a power of 2, and the resonant frequencies of
these structures should be arranged as a geometric series.
These mechanical structures are connected to a differential
amplifier, and their PNS arranged using a mirror rela-
tionship. The fine tuning of these parameters allows the
desired filter characteristics to be realized step by step. The
filter designer can follow the design rules in this paper to
easily construct a MEMS filter with the desired function-
ality. The MEMS filter provides not only the advantages of
MEMS technology but also a creative and feasible concept
for acoustic signal processing which represents a viable
alternative to DSP implementations, with advantages of
lower power consumption and shorter computation time.
We firmly believe that these novel MEMS filters represent
promising new devices for acoustic signal processing.
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... [3][4][5] The army and air force researchers use metamaterials to detect the presence of explosives, biological materials, and contamination. [6][7][8][9][10] Metamaterials easily manipulate sound wavelengths that are much larger than light. Sound bends around it provided by Navy Researcher, which may be used to hide submarines in military applications. ...
Metamaterials are man-made substances with unique spatial alternations in their constituent ‎components. They are widely used in modifying elastic, acoustic, or electromagnetic properties of ‎materials. Metamaterials induce low/high-frequency band gaps to control wave propagations with ‎different wavelengths and are also frequently applied in microwave engineering, waveguides, ‎dispersion compensation, smart antennas, and lenses. For instance, permittivity and permeability ‎of the metamaterials can take positive or negative values. Due to smaller single-cell dimensions ‎than their wavelength, the selective frequency of surface-based metamaterials is used for ‎waveguiding. The need for adjustable bandgaps can also lead to a plethora of research into ‎metamaterials' tunability for structures that operate at different speeds. In this article, recent ‎studies in the field of metamaterials and their applications are reviewed. The piezoelectric ‎metamaterials and the electromagnetic metamaterials are introduced, that is followed by a review ‎of new types of chiral metamaterials. Additionally, absorber, nonlinear, terahertz, tunable, ‎photonic, selective surface-based frequency in acoustic metamaterials are compared, and some ‎remarks on tuning bandgaps methods in locally resonant metamaterials.‎
... Recent progress in microfabrication and microelectromechanical systems (MEMS) has highlighted the potential of compact and miniaturized devices for on-chip acoustic signal generation, detection, manipulation and processing [143,144]. In particular, many important MEMS-based applications have been suggested lately, including acousto-optic modulators [145], acoustic MEMS filters [146], and biosensors [147]. A typical device consists of several key components, which include resonant transmitters and receivers that generate and receive mechanical vibrations, and a signal transmission line, i.e. waveguide network, along which phonon waves are guided between the signal processing modules [148]. ...
Nanocrystal superlattices (NCSLs) are materials formed by assembly of monodisperse nanocrystal building blocks that are tunable in composition, size, shape, and surface functionalization. Such materials offer the potential to realize unprecedented combinations of physical properties, however, theoretical prediction of such properties remains a challenge. Because of the different length scales involved in these structures, modeling techniques at different scales, from ab-initio methods up to continuum models, can be used to study their behavior. This presents a challenge of understanding when and for which properties we can use computationally inexpensive continuum or mesoscopic models and when we will have to use microscopic models. Our goal here is to develop models that can predict phononic and thermal properties of different NCSLs. This includes (1) predicting bulk mechanical properties of NCSLs such as Young's and bulk modulus which are related to the behavior of low frequency acoustic phonons (2) predicting phononic band gaps through finding phonon dispersion curves of NCSL (3) predicting thermal conductivity of NCSLs. We also study the topic of one-way phononic devices that can possibly be implemented with acoustic metamaterials such as NCSLs or phononic crystals in general. This idea of one-way phonon isolation is investigated in a theoretical framework by considering systems such as acoustic waveguides and low dimensional materials.
Metamaterial has received great interest during the last ten years in distinct field, owing of its key characteristics such as enhancement in bandwidth, radiated power, directivity and controls the direction of electromagnetic radiation. It is a smart or a new class of manmade invented materials that can achieve electromagnetic properties that do not occur naturally, such as electromagnetic cloaking or negative index of refraction. These materials exhibit negative value of permittivity, permeability and refractive index. In addition, metamaterial extract their properties from their structure rather than the material of which they are composed of. Further, these materials exhibit excellent design flexibility with their customized properties and their tunability under external stimuli. Due to these attractive properties, metamaterials have enabled the development of new devices and concepts and possible utilization in diverse novel applications. Thus, metamaterials find wide application in medical sector, automotive, aerospace, and many other devices (biosensor, crowd control, absorbers, antennas, optical filters, infrastructure monitoring, smart solar power management, energy harvesters and even shielding structure from earthquakes etc). Hence the aim of this paper is to provide a comprehensive overview of different metamaterial, historical development and their applications in different sectors. In addition, perspective about the challenges and future scope for development of metamaterial is also presented, so that this article could become the torch bearer for the new researchers working in the area of advanced materials.
Conference Paper
Noise cause many problems the world, it is considerably in the precision technology. There are many type of filters to remove the noise. Compliant bistable mechanisms (CBMs) have many application in MEMS technology. The article introduces the compliant mechanism assigns to the filter. The CBM is capable of signal amplification and filtering. The system exploits the nonlinear behaviour of CBM to detect the original signal. A mathematical model of system developed to predict the result. Through the CBM, the signal-to-noise (SNR) ratio, -13.14 dB, of a contaminated signal can be increased to 15.20 dB. It is found that the force-displace (f-d) curve of the BM should be symmetric force for effective filtering.
A robust control scheme for dynamic resonance frequency tracking in NEMS resonant mass sensors arrays is described. This is accomplished using a simple measurement set-up that can be integrated to the sensor altering the frequency resolution and enhancing the performance and the robustness to the parameters dispersion effect and to the global model uncertainty. It is based on a PLL oscillating loop in which the VCO generates the common excitation of the whole array and the feedback signal is given by the collected array's output. The measurement issue is turned to a servo-control problem that maintains the phase shift between the drive signal and the output's one at - π/2 that occurs on resonance, adjusting the VCO frequency to the sensor's variant resonance frequency. The controller is designed using H∞ loop-shaping method, rejects the disturbance described by the resonance frequency shift with a large bandwidth, attenuates the phase noise and guarantees good stability margins. The VCO control voltage shows an image of the amount of change in the resonance frequency surpassing the need of additional hardware components and external measurement circuitries.
One of the most important benefits provided by M/NEMS is their ability to be fabricated in a massive way combining them into arrays. However, many problems limit the use of such systems such as control complexity, elements dispersion and couplings, non-linearities and noise sources, etc. Hence, it is crucial to take these features into consideration since the design stage, eliminating their effects or making advantage of them to make new architectures that achieve high performances. A contribution to flexible micro-structures control is developed using a large array of distributed nano-transducers. The continuous structure is then replaced by a NEMS array whose model is detailed for the first time in function of existing dispersions. Coupled arrays architectures are suggested in order to reduce the dispersions effects, enhancing by that the selectivity of the derived filters. Based on the distributed transductions scheme, a novel tuning strategy is elaborated by using modal control. The different arrays (coupled or not) can be used in sensing applications, where the measurement system is modelled depending on the used technique and on the chosen structure before improving the performances by appropriate control. A new configuration based on transduction nonlinearities is designed for variation compensation and measurement of a sensor resonance frequency allowing system complexity reduction.
We present a method to achieve one-way mode isolation in acoustic waveguides by considering spatio-temporal modulation of material properties. Mode conversion between symmetric and antisymmetric shear horizontal (SH) modes of an unbounded plate acoustic waveguide is demonstrated using this method. Analytical and numerical evidence for the possibility of mode conversion is presented. Possible experimental implementation and applications for on chip signal isolation in MEMS devices are also suggested.
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This work fabricates a laminated-suspension microelectromechanical filter, respectively, by a fully compatible CMOS 0.6μm single poly triple metal (SPTM) process and CMOS 0.35μm single poly quadri-metal (SPQM) process. Experimentally, due to the top metal layer being used as the etch-resistant mask during the subsequent dry etching. Therefore, this study performs maskless etching with plasma and obtains excellent results including high selectivity and full release of the structure. Additionally, the microelectromechanical filter can be driven by applying low-voltage of around 5V and a measured center frequency of around 13.1kHz and a quality factor of around 1871 were obtained for a single-comb resonator operated in air. The filter successful proposed herein has a monolithic integration capability with the relative electric circuits in the standard CMOS 0.35μm process.
An introduction is presented to the subject of electro-mechanical bandpass filters, with special emphasis on problems of interest to those concerned with circuit theory. The acoustical (mechanical) network where the filtering takes place is composed of resonators and coupling wires. The resonators and wires are high Q (10,000-20,000) iron-nickel alloys that can be heat-treated to obtain a temperature coefficient of frequency as low as 1-2ppm/ degree C and aging characteristics of 50 ppm/10 years. The most common vibration modes of both the resonators and coupling wires are flexure, length-extension and torsion. Physical realizations of presently manufacturd mechanical filters are described. Network design problems are viewed in terms of electrical equivalent circuits of transducers, resonators and coupling wires.
This report demonstrates the tuning the quality factor of a micromachined structure using the air damping of a small squeezed-film area (300 μm 2 to 800 μm 2). Two micromachining processes have successfully been established to fabricate novel stationary structures using thin films and bulk silicon, in which the stationary structure and a vibrating micromachined cantilever form a squeezed-film region. Measurements showed that, under the assistant of bulk silicon stationary structure, the quality factor of the vibrating beam decreased by 48% when the squeezed-film area was increased from 300 μm 2 to 800 μm 2 under a 760-torr ambient pressure. Moreover, even when the ambient pressure was only 20 mtorr, the quality factor of the beam still decreased by 20% for the same increase in area. Under the assistant of thin film stationary structure, the quality factor of the vibrating beam decreased by 35% when the squeezed-film area was increased from 300 μm 2 to 500 μm 2 under a 760-torr ambient pressure. Consequently, the proposed two stationary structures can be exploited to significantly alter the quality factor of dynamic systems.
The use of a multisilicon beam structure as a filter bank for extraction of very close signals is investigated. The theory and design of such a filter bank is presented. The filter fabrication is compatible with silicon IC technology so that it can be easily incorporated in any silicon integrated circuit. The filter bank can be used for channel filtering in HF communication systems.
A portable sound processor has been developed to facilitate research on advanced hearing aids. Because it is based on a digital signal processing integrated circuit (Motorola DSP56001), it can readily be programmed to execute novel algorithms. Furthermore, the parameters of these algorithms can be adjusted quickly and easily to suit the specific hearing characteristics of users. In the processor, microphone signals are digitized to a precision of 12 bits at a sampling rate of approximately 12 kHz for input to the DSP device. Subsequently, processed samples are delivered to the earphone by a novel, fully-digital class-D driver. This driver provides the advantages of a conventional class-D amplifier (high maximum output, low power consumption, low distortion) without some of the disadvantages (such as the need for precise analog circuitry). In addition, a cochlear implant driver is provided so that the processor is suitable for hearing-impaired people who use an implant and an acoustic hearing aid together. To reduce the computational demands on the DSP device, and therefore the power consumption, a running spectral analysis of incoming signals is provided by a custom-designed switched-capacitor integrated circuit incorporating 20 bandpass filters. The complete processor is pocket-sized and powered by batteries. An example is described of its use in providing frequency-shaped amplification for aid users with severe hearing impairment. Speech perception tests confirmed that the processor performed significantly better than the subjects' own hearing aids, probably because the digital filter provided a frequency response generally closer to the optimum for each user than the simpler analog aids.
Conference Paper
The digital hearing aid is designed to be a low-cost, digital replacement for a standard analog hearing aid
Conference Paper
With Q's in the tens to hundreds of thousands, micromachined vibrating resonators are proposed as IC-compatible tanks for use in the low phase noise oscillators and highly selective filters of communications subsystems. To date, LF oscillators have been fully integrated using merged CMOS+microstructure technologies, and bandpass filters consisting of spring-coupled micromechanical resonators have been demonstrated in the HF range. In particular, two-resonator micromechanical bandpass filters have been demonstrated with frequencies up to 14.5 MHz, percent bandwidths on the order of 0.2%, and insertion losses less than 1 dB. Higher-order three-resonator filters with frequencies near 455 kHz have also been achieved, with equally impressive insertion losses for 0.09% bandwidths, and with more than 64 dB of passband rejection. Evidence suggests that the ultimate frequency range of this high-Q tank technology depends upon material limitations, as well as design constraints-in particular, to the degree of electromechanical coupling achievable in micro-scale resonators
Conference Paper
Third-order, micromechanical bandpass filters comprised of three folded-beam resonators coupled by flexural mode springs are demonstrated using an IC-compatible, polysilicon surface-micromachining technology. The use of quarter-wavelength coupling beams attached to resonators at their folding-trusses is shown to suppress passband distortion due to finite-mass nonidealities, which become increasingly important on this micro-scale. A balanced, 300 kHz, prototype, three-resonator micromechanical filter is demonstrated with filter Q=590 and stopband rejection greater than 38 dB