JAM Based Trap Assissted Biosensonsing applications

Microelectronics Journal 143 (2024) 106032
Available online 4 December 2023
1879-2391/© 2023 Elsevier Ltd. All rights reserved.
Physics-based analytical model for trap assisted biosensing in dual cavity
negative capacitance junctionless accumulation mode FET
Snehlata Yadav, Sonam Rewari *
, Rajeshwari Pandey
Department of Electronics and Communication Engineering, Delhi Technological University, Delhi, India
A R T I C L E I N F O
Keywords:
Biosensor
Ferroelectric
Junctionless accumulation mode
Sensitivity
A B S T R A C T
The design of a ferroelectric-based biosensor for detecting various biomolecules like proteins and DNA has
captivated the interest of researchers in early disease diagnostics and treatment monitoring. Doomed by this
interest, an analytical model for trap-assisted biosensing in Dual Cavity Negative Capacitance Junctionless
Accumulation Mode FET is proposed for detecting various biomolecules. The biomolecules are treated as traps
that tunnel through the biosensor’s ferroelectric layer. The analytical model is validated through extensive
numerical device simulations. The device incorporates the detection of charged and uncharged biomolecules in
terms of dielectric constants and biomolecule concentration. The nano-cavities are created inside the gate
dielectric stack to collect biomolecules like proteins and DNA. As the biomolecules are infused as traps in cavity
areas, electrical properties of the biosensor, like input characteristics, transconductance, threshold voltage, on-
state current, and subthreshold swing change. The sensitivity obtained for the proposed biosensor is compared
with the existing biosensor and found that it is best suited for susceptible biosensing applications.
1. Introduction
The remarkable properties of biosensors sparked a great deal of in
terest in continuing research in this area. The development of
technology-aided in pushing the field of biosensors to its limit and
expanding its use in various industries, including pasteurization, envi
ronmental sensing, and national healthcare [1]. Because of its early
detection, ongoing assessment, and diagnosis capabilities, the biosensor
is crucial in the medical industry. The outbreak of corona (Covid-19)
pandemic is the finest example of the significance of biosensors in
medical diagnosis since early disease detection can prevent the virus’s
spread [2,3].
A field-effect transistor (FET)-based biosensors draws interest due to
their compressed area, great sensitivity, low energy utilization, acces
sible mass manufacture technique, and broad detection range [4]. Bio
sensors are primarily used in the early detection of biomarkers to
prevent and diagnose the disease has been one of the interesting
research fields. Systems with increased sensitivity are constantly
required in biological research because even modest relative fluctua
tions in a biomarker’s concentration can be significant [5]. The bio
sensor’s current sensitivity is determined by the difference in current
between conditions with and without the presence of biomolecules.
In order to recognize biomolecular entities at ultralow concentra
tions, higher current sensitivity is required [6]. Higher current sensi
tivity can be reached while the biosensor is running in the subthreshold
region for FET-based biosensors. The highest current sensitivity that can
be attained is however restricted by the Boltzmann limit of subthreshold
swing (SS) to 60 mV/decade at ambient temperature in typical
FET-related biosensors [7]. With the development of technology, effi
ciency has become much more in demand. Therefore, a transition to a
different device that can handle these difficulties is required. A
steep-switching device such as negative capacitance FETs (NCFETs) is a
possible method for overcoming the Boltzmann limit. A ferroelectric
(FE) material layer is used in the gate-stack to accomplish internal
voltage amplification and the requisite steep subthreshold slop of
NCFETs [8]. Negative capacitance (NC) has a positive impact from two
angles. Firstly, it decreases the SS, increasing current sensitivity in the
weak inversion domain. Secondly, it significantly overdrives the sensor,
lowering its power consumption [9]. The rapid source-drain junction
formation, higher parasitics, and challenging fabrication process of
traditional MOSFETs are further downsides [10]. To overcome such
drawbacks, a modified variant of the Junctionless transistor (JLT) was
developed, known as Junctionless Accumulation Mode FET (JAM-FET)
[11]. The JAM-FETs have a single dopant structure with an
* Corresponding author.
E-mail address: rewarisonam@gmail.com (S. Rewari).
Contents lists available at ScienceDirect
Microelectronics Journal
journal homepage: www.elsevier.com/locate/mejo
https://doi.org/10.1016/j.mejo.2023.106032
Received 24 August 2023; Received in revised form 31 October 2023; Accepted 17 November 2023

2
n+–n–n+/n++–n–n++ homojunction, and the doping concentration of
the channel area is lower than that of the Source/Drain region. To
decrease parasitic resistance, the JAM-FET features a high doping con
centration (1019
cm− 3
) in the Source/Drain areas. It also reduces the
fabrication complexity and the mobility degradation, which arises in a
Junctionless transistor due to high doping in the channel [12]. There has
been a lot of FET-based nanoscale sensors presented recently [13–17],
and in order to improve sensitivity and detection, more design param
eter optimisation was required.
Therefore, a very sensitive biosensor is developed by acquiring the
benefits of NC and JAMFET. It is made possible by incorporating a
ferroelectric layer in the gate stack structure of JAM-FET. The main
impetus for researching the advantages of NC-based JAM-FET for bio
sensing applications is the need for faster and more accurate biosensors
without adding extra burden on expensive manufacturing equipment.
Hence, to address the need for highly sensitive and quick biosensing
applications, a ferroelectric material-based Dual Cavity Negative
Capacitance Junctionless Accumulation Mode FET (DC–NC–JAM-FET)
based biosensor is proposed in this paper. The nano-cavities are created
inside the gate dielectric stack to collect biomolecules with different
dielectric constant, such as proteins and DNAs. Nano-cavities are filled
with air if no biomolecules are present. The electrical properties of the
biosensor, like threshold voltage, drain current, and SS change as the
targeted biomolecules are infused in the nano-cavities because the
effective oxide capacitance changes as a result of the biomolecules’
dielectric constants [18].
Devices and circuits are connected through analytical and compact
models. These models are also useful for gaining a deeper understanding
of how devices work and for assessing how well biosensors perform.
There are several analytical models of JLT and FE-FET accessible in the
literature [19–21]. However, to the best of the author’s knowledge,
there isn’t any analytical model of DC–NC–JAM-FET biosensing device.
Thus, by incorporating the benefits of NC and double-gate JAMFET, this
study proposes an analytical model of DC–NC–JAM-FET biosensor ar
chitecture. Ferroelectric material, when used as gate oxide material
improves the subthreshold swing, improves the gate control over the
channel and establishes its applicability in low-power biosensor design
[22]. The proposed biosensor provides advantages such as high sensi
tivity, label-free detection, compatibility, and fabrication feasibility.
These qualities make them well-suited for various biosensing
applications.
2. Device architecture and simulation
A 2D schematic cross-sectional view of the DC–NC–JAM-FET
biosensor is shown in Fig. 1(a). The device employs two nano-cavities
for biomolecules, and ferroelectric material layers made of hafnium
zirconium oxide (HZO). TiN with work function 4.65 eV is used as gate
metal [23]. In JAM structure source and drain are heavily doped (1019
cm− 3
) and channel is moderately doped (1017
cm− 3
). Ferroelectric,
insulator, and channel layer thicknesses are assumed to be 5 nm, 2 nm,
and 20 nm, respectively. DC–NC– JAM-FET detects biomolecules such as
streptavidin, biotin, APTES, protein A, and DNA having different
dielctric constants. The dielectric constant for biomolecules is shown in
Table 1. Fig. 1(b) shows the cavity region with no biomolecule, i.e., air
(ε = 1) and infusion of the biomolecules having different dielectric
constant (ε > 1). Fig. 1(c) shows the equivalent capacitance model, and
Fig. 1(d) represents Polarization-Electric field curve obtained from the
following equation:
E= 2αP+4βP3
+6γP5
(1)
Since capacitance (C) is proportionate to the gradient, dP/dE, this
curve exhibits a negative gradient region from which the negative
capacitance originates. The Silvaco ATLAS TCAD simulator is used for
the simulations, which include the Lombardi CVT model, Shockley-
Read-Hall (SRH) recombination, fermi, and Landau-Khalatnikov (LK)
models [24]. The calibration of this work [25] is done to validate and
give a realistic simulation environment as depicted in Fig. 2(a). Fig. 2(b)
depicts the relevant energy band representing the trap assisted phe
nomenon of biomolecules through the layers of the biosensor. Trap
assisted tunnelling (TAT) component is one of the major component
which have a significant impact on biosensor [26]. The trap tunnelling
rate increases significantly in the presence of an electric field, which
dramatically enhances the electron-hole production rate [27].
Fig. 1. (a) Structure of DC–NC–JAM-FET biosensor, (b) biomolecule infusion in the cavity region, (c) equivalent capacitance model (d) P-E curve for ferroelectric
illustrating the negative capacitance region.
Table 1
Biomolecules and corresponding dielectric constants.
Biomolecules Dielectric Constant
Streptavidin [28] 2.1
Biotin [21] 2.63
APTES [28] 3.57
Protein A [29] 4
DNA [30] 8
S. Yadav et al.

3
3. Analytical model formulation
The two major regions are taken into account in the development of
an analytical model for the proposed device. Region I is the insulator
layer, and region II is the cavity layer which is to be filled with bio
molecules. The equivalent capacitance model of these regions is pre
sented in Fig. 1(c) and is given by the following equations:
CIL =
εIL
tIL
(2)
Cbio =
εbio
tbio
(3)
where εIL, εbio, tIL, and tbio are permittivity and thickness of the insulator
layer and cavity layer to be filled with biomolecules, respectively. For
the sake of simplicity, the thickness of the biomolecule layer and the
insulator is considered to be equal.
The total capacitance CTotal for region 1 and region 2 is expressed as:
CTotal = CIL + Cbio (4)
The total gate capacitance of the device is given by:
1
CG
=
1
CFE
+
1
CIL + Cbio
+
1
CSC
(5)
Additionally, the drain current and charge density models are com
bined with the Landau-Khalatnikov (L-K) equation in order to build the
analytical model [31]. Drops across the insulator layer and cavity layer
(VIL + Vbio), ferroelectric layer (VFE), flat band voltage (VFB), and surface
potential (φSP) are added to determine the overall gate voltage:
VGS = VFE + VIL + Vbio + VFB + φSP (6)
where
VIL =
QTOT
CIL
,Vbio =
QTOT
Cbio
,VFB = φM − φsi
φsi = χ +
Eg
2
−
kT
q
ln
(
N+
D
ND
)
(7)
where N+
D is the doping concentration in source/drain regions of JAM
FET and (φsi) is the work function of silicon.
The following equation determines the charge density (QTOT) over
the entire channel [32]:
QTOT (x = tCH) = qNDtCH − qND
∫
+tCH
/
2
− tCH
/
2
e
(φ− V)
kT
/q dx (8)
The ferroelectric layer’s negative capacitance is included into the
computation of VFE using the Landau-Khalatnikov (L-K) equation as
shown below [33]:
VFE= 2αtFEQTOT +4βtFEQ3
TOT +6γtFEQ5
TOT (9)
Here α, β, and γ are the material parameters, which are determined as
given in Ref. [34]. On solving (6) and (9) the following expression is
obtained:
VGS − VFB − φSP =
QTOT
CIL + Cbio
+2αtFE
QTOT
2
+4βtFE
(
QTOT
2
)3
+6γtFE
(
QTOT
2
)5
(10)
To obtain the threshold voltage, a fully depleted channel is assumed,
and hence, the total charge density can be expressed as:
QTH = qNDtCH
⎛
⎜
⎜
⎜
⎝
1 −
1
2
̅̅̅̅̅̅̅̅̅̅̅
̅
πkT/q
φSP
√
⎞
⎟
⎟
⎟
⎠
(11)
(φSP) can be evaluated from [35] as:
φSP =
qNDt2
CH
8εsi
(12)
Now, the threshold voltage is obtained by substituting (11) and (12)
in (10):
VTH = VFB +
qNDt2
CH
8εsi
+
(
1
CIL + Cbio
+ αtFE
)
QTH+4βtFE
(
QTH
2
)3
+6γtFE
(
QTH
2
)5
(13)
The mobile charge in the channel is obtained by putting
φSP = tCH
8εsi
(QMOB +qNDtCH) [12] and QTOT = (QMOB +qNDtCH) along with
simple mathematical computations of (8) and (10) as:
Fig. 2. (a) Calibration with the reported work. (b) Energy band diagram showing trap assisted tunnelling (TAT) of biomolecules through ferroelectric layer.
S. Yadav et al.

4
VGS − VFB − V +
tCH
8εsi
(QMOB + qNDtCH) + VT ln
(
QMOB
̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅
(QMOB + qNDtCH)
2εsiπVT q2
N2
DtCH
√ )
=
(
αtFE +
1
CIL + Cbio
)
(QMOB + qNDtCH)+4βtFE
(
QMOB + qNDtCH
2
)3
+6γtFE
(
QMOB + qNDtCH
2
)5
(14)
The drain current expression is derived using the above mobile
charge model. It is determined by integrating QMOB from source to drain
using the Pao-Sah integral [32] as follows:
ID= − μ
W
L
∫
VDS
0
QMOBdV (15)
Here, QMOBS and QMOBD are obtained from (14) by varying the voltage
from zero to drain to source voltage (VDS).
The expression for transconductance can be expressed as follows
[36]:
gm =
dID
dVGS
(17)
4. Results and discussion
4.1. DC–NC–JAM-FET as a bio-sensing device for different biomolecules
In this section, the dielectric modulated DC–NC–JAM-FET is used as
biosensing device for detecting various biomolecules with different
dielectric constants. These biomolecules include Streptavidin, Biotin,
APTES, Protein A, and DNA. The biomolecule in the cavity influences
the electrical behavior of the device. The ability to detect biomolecules
is made possible by adjusting a material’s permittivity since a change in
permittivity also affects a material’s capacitance. The proposed
biosensor is typically used for sensing biomolecules in dry
environments.
Fig. 3 (a) depicts the electron concentration contour plots. It also
shows the concentration remaining unchanged when no biomolecule is
present. However, when additional biomolecules are added, the area
below the cavity region are induced with charges. As evident from the
figure, the charges that are induced depends on the various bio
molecules. Fig. 3 (b) shows the energy band profile of DC–NC–JAM-FET
based biosensor at different dielectric constant. It can be observed that
the band profile bends more at the junction near the source/channel
interface regions with the immobilization of dielectric biomolecules in
the formed cavity, and when the dielectric value of biomolecules in
creases, the bands bend more at junction region, which enhances the
coupling between the source and the channel. The energy band bending
depends upon the change in the flat band voltage in the cavity regions.
The amount of the change in the flat band voltage depends upon the
capacitance of the nanaogap cavity regions which depends upon the
dielectric constant of the cavity regions.
Fig. 3 (c) show the surface potential along the horizontal direction
with different dielectric constant of the biomolecules. It can be observed
that, in the absence of biomolecules (ε = 1), the surface potential has a
smaller value underneath cavity region. On the other hand, in the ex
istence of biomolecules at ε > 1, the surface potential achieves a higher
value in the cavity region. As the dielectric constant increases (ε), the
coupling between gate and channel increases which leads to surface
potential.
Fig. 4 (a) implies that the DC–NC–JAM-FET attains superior drain
current when compared to DC–NC–JL-FET. The proposed device’s
higher drain current is caused by the high electron mobility provided by
the JAM structure’s high doping concentration in the source/drain re
gions which reduces the parasitics. Fig. 4 (b) shows the analytical results
analogous to the TCAD simulated results. The figure makes it quite
evident that the analytical and simulated outcomes agree closely.
Additionally, it is deduced that the drain current increases with the
biomolecules’ dielectric constant. This occurs because when the
dielectric constant is increased, the extent of band bending increases,
resulting in a reduction in the width of the barrier.
Fig. 5 (a) shows the transconductance behavior of both the simulated
architectures. The proposed device has a greater drift in trans
conductance as contrasted to the conventional device. This is because
the transconductance is proportional to the drain current. Fig. 5 (b)
shows the analytical results for the transconductance variation of the
proposed device and its comparison with the TCAD simulation. The
results appear to be relatively close to one another, and it is also evident
that the transconductance value increases with the increase in the
dielectric constant of the biomolecules.
The crucial factor for any type of sensor is its sensitivity, and a high
sensitivity level is always desirable. The sensitivity of DC–NC–JAM-FET
is analyzed in terms of Threshold voltage (VTH), On Current (Ion), and
Subthreshold Swing (SS), respectively. The expressions for sensitivity for
each of the parameters can be expressed as below:
SVTH
=
VTH,bio − VTH,air
VTH,air
(18)
SION
=
ION,bio − ION,air
ION,air
(19)
SSS =
SSbio − SSair
SSair
(20)
Here, VTH, bio, and VTH, air is the threshold voltage values when the
cavities are filled with biomolecules at dielectric constants of bio
molecules (ℇ = 2.1, 2.63, 3.57, 4, 8) and no biomolecules, i.e., air (ℇ =
1). Fig. 6 (a), (b), (c) shows the sensitivity comparison between the
proposed and existing biosensor. It is observed that as the dielectric
constant increases, the sensitivity increases for both devices. It can also
be inferred from the figures that the proposed device possesses higher
sensitivity as compared to existing device. This is owing to the fact that
ID= − μ
W
L
⎡
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎣
qNDtCH
2
ln(QMOB + qNDtCH) −
αtFEQ2
MOB
2
− 3βt2
FEQ2
MOB
⎧
⎪
⎪
⎪
⎪
⎨
⎪
⎪
⎪
⎪
⎩
Q2
MOB
8
+
QMOBNDqtCH
2
+
(
NDqtCH
2
)2
⎫
⎪
⎪
⎪
⎪
⎬
⎪
⎪
⎪
⎪
⎭
−
QMOB
2
(
3VT −
QMOBtCH
8εsi
+
QMOBtCH
2εIL + εbio
)
⎤
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎦
QMOBD
QMOBS
(16)
S. Yadav et al.

5
the surface potential increases with the increase in dielectric constant.
Therefore, the proposed device can be used as a biosensor for detecting
various biomolecules such as Streptavidin, Biotin, APTES, Protein A, and
DNA. It can be noticed that as the dielectric constant increases, the
coupling between gate and channel increases which leads to improve
ment in SS magnitude. From Fig. 6 (c), it can be analyzed that the SS
sensitivity increases with an increase in the dielectric constant of the
biomolecule. Hence, it can be concluded that the smaller value of SS
shows a better sensitivity of DC–NC–JAM-FET biosensor.
4.2. Impact of biomolecule concentration on DC–NC–JAM-FET
The surface potential of the proposed device for different biomole
cule concentration (positive, negative, and neutral) is shown in Fig. 7. It
is observed that, when the cavity regions are filled by the positively
(negatively) charged biomolecules, the minimum surface potential
Fig. 4. (a) Drain current characteristics of the devices for different biomolecule dielectric constant, (b) analytical drain current characteristics.
Fig. 3. (a) The contour plot for electron concentration with different biomolecules (b) Energy band plots against position along the channel showing the conduction
and valence band of DC–NC–JAM-FET at different dielectric constants (c) Surface potential along the lateral direction for different dielectric constants.
S. Yadav et al.

6
increases (decreases) in comparison to the case when the cavity regions
are filled by the neutral biomolecule which have the dielectric constant
(ε = 8).
The drain current characteristics of different device architectures for
various biomolecule concentrations is shown in Fig. 7 (a). It is observed
from Fig. 7 (a) that the drain characteristics are higher for the proposed
device. This is owing to the fact that the mobility degradation in the JAM
structure is negligible because of moderate doping in the channel region
of the JAM structure when compared to the JL transistor, and thus, it
improves the drain current. The analysis is carried out for various
biomolecule concentrations, i.e., for positively charged (1e12 cm2
),
negatively charged (-1e12 cm2
), and neutral biomolecules (0 cm2
). The
analytical drain current characteristics of DC–NC–JAM-FET biosensors
for different biomolecule concentrations is shown in Fig. 7 (b). It is
observed that there is a good agreement between the analytical results
and TCAD simulations. It is also inferred from the figure that the drain
current characteristics are higher for positively charged biomolecules.
When charged biomolecules bind to receptor molecules, certain target
molecules may become ionized, either carrying a positive or negative
charge. The nature of this charge depends on the specific biomolecule
involved. These charges, once located at the oxide surface, induce al
terations in the surface potential within the channel. As shown in Fig. 7,
positively charged biomolecules lead to an increase in the surface po
tential, consequently causing a shift in the drain current. Conversely,
negatively charged biomolecules lead to a decrease in the surface po
tential, resulting in a reduction in the drain current.
Fig. 8 (a) and (b) represent the transconductance values for the
different dielectric constants of the compared devices. The figure clearly
illustrates that the transconductance drift is larger for the DC–NC–JAM-
FET at different biomolecule concentrations. As the transconductance
value of the device is dependent on the drain current, it increases with
an increase in drain current. Fig. 7 (b) illustrates the analytical results
for different biomolecule concentrations. As observed, the analytical
results are analogous to the simulated results. It can also be interpreted
from the results that the gm value is higher positively charged bio
molecules are inserted and lower when negatively charged biomolecules
are inserted in the cavities. This is a result of the biomolecules’ insertion
altering the surface potential.
The impact of biomolecule concentration on the Sensitivity param
eters is also carried out in this section.
The sensitivity comparison of the proposed biosensor with the
existing, in terms of parameters such as threshold voltage on the current
and subthreshold swing is shown in Fig. 9 (a), (b), and (c). As observed
from Fig. 9 (a), the threshold voltage sensitivity for the DC–NC–JAM-
FET is higher in comparison to DC–NC–JL-FET. The reason for this is that
the threshold voltage can be modulated by biomolecule concentration
by changing the capacitance. Also, the sensitivity at negatively charged
biomolecule concentration is higher because the threshold voltage de
creases as the biomolecule concentration is increased from negative to
positive. Fig. 9 (b) shows the On current sensitivity of the DC–NC–JAM-
FET with the compared device. As evident, the sensitivity of the device
concerning to on-current is enhanced because the JAM structure lowers
the mobility degradation, which in turn increases the On-current.
Additionally, the On current value is higher for positively charged bio
molecules, so its sensitivity is low. Fig. 9 (c) shows the sensitivity for
both devices at different biomolecule concentrations in terms of SS. As
observed, the SS sensitivity is higher for the proposed device because
when the biomolecules’ dielectric properties in the cavities are
Fig. 5. (a) Transconductance of different devices for different dielectric constant, (b) analytical transconductance variation of the proposed device for various
biomolecules.
Fig. 6. Comparison of different devices with respect to (a) Threshold voltage sensitivity, (b) On Current sensitivity and (c) SS sensitivity at different dielec
tric constants.
S. Yadav et al.

7
increased, the subthreshold swing reduces, and hence the sensitivity
increases. It is also observed that as the biomolecule concentration in
creases, the subthreshold swing value increases, and thus the sensitivity
is lower at positively charged biomolecules. The device is highly
sensitive to negatively charged biomolecule concentrations. Therefore,
after these critical analyses, the proposed device can be a better alter
native to detect several biomolecules and can be used as a biosensing
device.
Fig. 7. Surface Potential of the biomolecule concentration along the channel position.
Fig. 7. (a) Drain current characteristics of the devices for different biomolecule concentration. (b) Analytical drain current characteristics of the proposed device.
Fig. 8. (a) Transconductance of diiferent devices for various biomolecule concentartions (b) Analytical transconductance values for various biomolecule
concentrations.
S. Yadav et al.

8
4.3. Impact of non-ideal effects on DC–NC–JAM-FET based biosensor
Non-ideal effects such as thickness of cavity (tcavity), length of cavity
(Lcavity), and fill factor are important constraints for analyzing the
sensing behavior of the device. In this concern, we have measured the
sensitivity of the proposed device with different cavity thicknesses,
cavity lengths and fill factor.
Figs. 10 and 11 shows the sensitivity of the biosensor considering
non-ideal effects like the thickness of the cavity (tcavity = 2 nm, 5 nm, 8
nm) and length of the cavity (Lcavity = 30 nm, 40 nm, 50 nm). The
sensitivity is measured in terms of parameters like threshold voltage and
on current. As evident from the figure, the maximum sensitivity is ob
tained as the length and thickness of the cavity is increased. These re
sults reveal that this device can be utilized as a better sensitive device for
the application of a label free biosensor.
Fig. 12 (a) shows the variation in the drain current characteristic of
Fig. 9. Sensitivity comparison of different devices in terms of (a) threshold voltage (b) On current (c) Subthreshold Swing at different biomolecule concentrations.
Fig. 10. (a) Threshold voltage sensitivity and (b) On current Sensitivity with respect to thickness of cavity.
Fig. 11. (a) Threshold voltage sensitivity and (b) On current Sensitivity with respect to length of cavity.
S. Yadav et al.

9
the biosensor having cavity thickness as 5 nm for DNA biomolecule for
different possible arrangements of the distribution of
Biomolecules in the cavity region. For investigating the practical
distribution of biomolecules of device, three points, i.e., 25 %, 50 %, 75
% have been analyzed. To investigate the influence of biomolecule fill
factor in cavities, a portion of the cavity is occupied by biomolecules,
while the rest is left empty or filled with air. The increase in fill factors
(in %) leads to an increase in the biomolecule occupancy due to an in
crease in effective dielectric/capacitance in the cavity region. Thus, it
can be noted that the drain current increases with the fill factor. The Ion
and Ion/Ioff sensitivity variation of DNA with the fill factor of the cavity
region is shown in Fig. 12 (b). It is evident that the sensitivity for both
the parameters is higher at 75 % biomolecule occupancy of the device.
5. Conclusions
A Physics-based analytical model for trap assisted biosensing in Dual
Cavity Negative Capacitance Junctionless Accumulation Mode FET
(DC–NC–JAM-FET) has been proposed for its better sensing ability. The
device incorporates the ferroelectric interfaced negative capacitance
with the junctionless accumulation mode FET and the biomolecules are
used as traps which tunnels through ferroelectric layer. When bio
molecules immobilize in the cavity region, electrical characteristics like
drain current, transconductance, and sensitivity have been regarded as
biosensing parameters for detecting them. The comparison of the pro
posed device with the existing device is carried out and found that the
proposed device exhibits a larger shift in drain current. The sensitivity is
calculated in terms of VTH, ION, and SS. Additionally, it has been
discovered that the proposed device has a threshold voltage sensitivity
for DNA detection that is almost two to three times higher. The On-state
current sensitivity and subthreshold sensitivity are also improved to a
greater extent. Hence, the research work carried out shows that
DC–NC–JAM-FET is an excellent candidate for a low-power ultra-sen
sitive biosensing device.
Funding
The authors declare that no funds, grants, or other support were
received during the preparation of this manuscript.
Authors contribution
Snehlata Yadav has simulated the device structure, developed the
computational framework, and prepared the original draft. Sonam
Rewari has conceived the idea, helped during the writing of final draft,
and supervised. Rajeshwari Pandey has supervised and helped in writing
- review, and editing. All authors reviewed the manuscript.
Ethical approval
This study did not involve human participants their data or biolog
ical material.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Declaration of competing interest
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.
Data availability
No data was used for the research described in the article.
Acknowledgements
Not applicable.
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