chapter-4 simulation of hetrojunction solar cells...
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CHAPTER-4
SIMULATION OF HETROJUNCTION
SOLAR CELLS WITH AFORS -HET
A number of approaches have been developed to synthesize the CuInSe2 and
CuInGaSe2 based thin film solar cells [1-6]. Due to large numbers of parameters
involve in processing a solar cell such as the energy band gap of the back surface field,
thickness of the emitter, interface density etc. It is a difficult task to scrutinize and
control the effect of each variable on the performance of the solar cell in laboratory. A
method therefore based on computer simulations will be useful to provide a convenient
way to evaluate the role of various parameters present in the fabrication process of the
thin film heterojunction solar cells. A great advantage of computer simulation is its
capacity to study in conditions without loss of materials beyond what is impossible or
difficult experimentally. Computer simulation offers an attractive way of avoiding
practical problems during experiment or synthesis of materials. In this chapter, the
solar cells are computationally fabricated, simulated and optimized using AFORS-HET
(Automat for simulation of hetero-structures) code [7]. The details of this code is
available in ref. [7], however we briefly discuss the silent features of the code in
following sections.
4.1 Introduction
AFORS-HET (Automat for simulation of heterostructures) not only simulates (thin
film) heterojunction solar cells, but one can also observe the analogous measurement
techniques. It is a user – friendly graphical interface allows the visualization, storage
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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and comparison of all simulated data. Besides, arbitrary parameter variations and
parameter fits to the corresponding measurements can be performed. In different
experimental situations, one can freely chose a metal/semiconductor or
metal/insulator/semiconductor front contacts to perform different numerical module
based on requirements.
To simulate optical and electrical properties of a solar cell, the one dimensional
semiconductor equations (Poisson’s equation and the transport and continuity
equations for electrons and holes) can be solved by using different numerical models
with the help of finite different conditions i.e.: (a) equilibrium mode (b) steady state
mode (c) steady state mode with small additional sinusoidal perturbation, (d) simple
transient mode, that is switching external quantities instantaneously on/off, (e) general
transient mode, that is allowing for an arbitrary change of external quantities. A
multitude of different physical models has been implemented. The optical models can
be solve either by Lambert-Beer absorption including rough surfaces and using
measured reflection and transmission files or by calculating the plain surface
incoherent/coherent multiple internal reflections, using the complex indices of
reflection for the individual layers [7]. Different recombination models can be
considered within AFORS-HET: radiative recombination, Auger recombination,
Shockley-Read-Hall and/or dangling-bond recombination with arbitrarily distributed
defect states within the bandgap. Super bandgap as well as sub-bandgap generation/
recombination can be treated. For contacts different boundary models can be chosen:
The metallic contacts can be modeled as flatband or Schottky like metal/
semiconductor contacts, or as metal/ insulator/ semiconductor contacts. Furthermore,
insulating boundary contacts can also be chosen.
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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Thus using AFORS-HET all internal cell quantities, such as band diagrams, quasi
Fermi energies, local generation/recombination rates, carrier densities, cell currents and
phase shifts can be calculated. Furthermore, a variety of solar cell characterization
methods can be simulated, i.e.: current voltage, quantum efficiency, transient or quasi-
steady-state photoconductance, transient or quasi-steady-state surface photovoltage,
spectral resolved steady-state or transient photo and electro-luminescence,
impedance/admittance, capacitance-voltage, capacitance-temperature and capacitance-
frequency spectroscopy and electrical detected magnetic resonance. The program
allows for arbitrary parameter variations and multidimensional parameter fitting in
order to match simulated measurements to real measurements [8].
4.2 Modeling capabilities
An arbitrary sequence of semiconducting layers can be modeled, specifying the layer
and if needed interface properties, i.e the defect distribution of states. Using Shockley-
Read-Hall recombination statistics, the one-dimensional semiconductor equations are
solved for thermal equilibrium, various steady state conditions (specifying the external
cell voltage or cell current and the spectral illumination) and for small additional
sinusoidal modulations the external applied voltage/illumination.
The internal cell characteristics, such as band diagrams, local generation and
recombination rates, local cell currents, free and trapped carrier densities can be
calculated. In addition, a variety of characterization methods can be simulated, i.e.
current-voltage (I-V), quantum efficiency (IQE, EQE), surface photovoltage (SPV),
photo-electroluminescence (PEL), impedance spectroscopy (IMP), capacitance-voltage
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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(C-V), capacitance-frequency (C-f) and electrically detected magnetic resonance
(EDMR).
The freely available and developed numerical modules are listed below:
(a) The front contact can be treated either as a metal /semiconductor contact (Schottky
contact) or as a metal/insulator/semiconductor (MIS contact). (b) The transport across
each semiconductor/semiconductor interface can be modeled either by drift-diffusion
currents or by thermionic emission. (c) The optical generation rate can be calculated
taking into account coherent/ incoherent multiple reflections. (d) A specific numerical
module for crystalline silicon considers impurity and carrier – carrier scattering [9, 10].
4.2.1 Optical calculation: super bandgap generation models
To calculate the generation rate Gn(x,t), Gp(x,t) of electrons and holes due to photon
absorption within the bulk of the semiconductor layers, a distinction between super
bandgap generation and sub bandgap generation is developed. The super-bandgap
generation rate is calculated by optical modeling as it is independent of the local
particle densities n(x,t) and p(x,t). Sub-bandgap generation depends on the local
particle densities and has been calculated within the electrical modeling part. The
optical superbandgap generation rate is equal for electrons and holes
G(x,t)=Gn(x,t)=Gp(x,t) which can either be imported by loading an appropriate file
(using external programs for its calculation) or it can be calculated within AFORS-
HET.
So far, two optical models are implemented in AFORS-HET, i.e. the optical model
Lambert- Beer absorption and the optical model coherent/incoherent internal multiple
reflections. The first one takes textured surfaces and multiple internal boundary
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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reflections into account (due to simple geometrical optics) but neglects coherence
effects [7-10]. It is especially suited to treat wafer based crystalline silicon solar cells.
The second takes coherence effects into account, but this is done only for plain
surfaces. If coherence effects in thin film solar cells were applied accordingly.
4.2.1.1 Optical model: Lambert-Beer absorption
The absorption within the semiconductor stack using optical mode can be calculated
assuming simple Lambert-Beer absorption, allowing multiple forward and backward
travelling of the incoming light, however disregarding coherent interference. A
(measured) reflectance and absorbance file of the illuminated contact R(λ), A(λ) have
been loaded. The incoming spectral photon flux φ0 (λ,t) is weighted with the contact
reflection and absorption, i.e. the photon flux impinging on the first semiconductor
layer is given by φ0(λ,t)R(λ)A(λ). To simulate the extended path length caused by a
textured surface, the angle of incidence δ of the incoming light can be adjusted. On a
textured Si wafer with <111> pyramids, this angle is δ = 54.740 , whereas δ=0
0 equals
normal incidence. The angle γ in which the light travels through the layer stack
depends on the wavelength of the incoming light and is calculated according to
Snellius’ law:
,)(
1)sin(arcsin)(
n 4.1
Where, n(λ) is the wavelength dependent refractive index of the first semiconductor
layer at the illuminated side. In this model, the change in γ(λ) is ignored, when the light
passes through a semiconductor/semiconductor layer interface with two different
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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refraction indices. It is assumed that all photons with a specified wavelength cross the
layer stack under a distinct angle γ.
The photon absorption is calculated from the spectral absorption coefficient αx(λ) =
4πk(λ)/λ of the semiconductor layer corresponding to the position x within the stack,
using extinction coefficient k(λ) of the layer. The super bandgap electron/hole
generation rate for one single run through the layer stack is (no multiple passes) given
by:
)cos(
)(max
min
0 )()()(),(),(
x
x
x
eARtdtxG
4.2
The minimum and maximum wavelength λmin, λmax for the integration were generally
divided by the loaded spectral range of the incoming spectral photon flux, φ0(λ,t). Only
super band gap generation is considered, λmax is modified in such order to ensure that
only super bandgap generation is considered: λmax ≤ hc/Eg.
To simulate the influence of light trapping mechanisms, internal reflections at both
contacts have been additionally specified. They can either be set as a constant value or
depending on wavelength (a measured or calculated file can be loaded). The light then
passes through the layer stack several times as defined by user, thereby enhancing the
absorbtivity of the layer stack (the local generation rate). The residual flux after the
defined number of passes is added to the transmitted flux at the contact, at which the
calculation ended (illuminated or not-illuminated contact), disregarding the internal
reflection definitions at this contact. This model was designed to estimate the influence
of light trapping of crystalline silicon solar cells and to adapt the simulation to real
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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measurements. By neglecting the internal multiple reflections and refractions within
the layer stack.
4.2.1.2 Optical model: coherent/ incoherent multiple reflections
This model calculates the absorption within the semiconductor stack by modeling
coherent or incoherent internal multiple reflections within the semiconductor stack. To
model the effect of anti-reflection coatings additional non-conducting optical layers in
front of the front contact/ behind the back contact of the solar cell is assumed. The
reflectance, transmittance and absorbance of all layers (optical layers and the
semiconductor layers) were calculated, using the concepts of complex Fresnel
amplitudes. Each layer has been specified to be optically coherent or optically
incoherent for a particular light beam (incident illumination). A layer is considered to
be coherent if its thickness is smaller than the coherence length of the light beam that is
incident on the system.
In order to consider the coherent effects, the specified incoming illumination φ0(λ,t)
has been modeled by an incoming electromagnetic wave, with a complex electric field
component ),(~
0 tE . The complex electric field components of the travelling wave are
retraced according to the Fresnel formulas, and thus the resulting electromagnetic wave
),,(~
txE at any position x within the layer stack is calculated, while an incoherent
layer is modeled by a coherent calculation of several electromagnetic waves within that
layer (specified by the integer NincoherentIteration), assuming some phase shift between
them, and averaging over the resulting electric field components.
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4.2.2 Electrical calculation
Within the bulk of each semiconductor layer, Poisson’s equation and the transport
equations for electrons and holes have been solved in one dimension. So far, there are
two semiconductor bulk models are available, i.e. the bulk model” standard
semiconductor” and the bulk model “crystalline silicon”. Using the standard
semiconductor model, all bulk layer input parameters individual, adjusted accordingly.
For silicon bulk model, most input parameters for crystalline silicon are calculated
from the doping and defect densities ND(x), NA(x), Ntrap of crystalline silicon. Thus the
effects like bandgap narrowing or the doping dependence of the mobility or of the
Auger recombination of crystalline silicon are explicitly modeled.
Within each layer, a functional dependence in space has been specified for the doping
densities ND(x), NA(x). These input parameters can be chosen to be (1) constant, (2)
linear, (3) exponential, (4) Gaussian like, (5) error function like decreasing or
increasing as a function of the space coordinate x.
4.2.2.1 Bulk model: standard semiconductor
The doping densities ND (x), NA(x) of fixed donator/ acceptor states at position x
within the cell are assumed to be always completely ionized. In contrast, defects Ntrap
(E) located at a specific energy E within the bandgap of the semiconductor can be
locally charged/ uncharged within the system. Defects have been chosen to be either
(1) acceptor-like Shockley –Read-Hall defects, (2) donor-like Shockley-Read-Hall
defects or (3) dangling bond defects.
Depending on the defect-type chosen, these defects can either be empty, singly
occupied with electrons or even doubly occupied with electrons (in case of the
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dangling bond defect). Acceptor-like Shockley-Read-Hall defects are negatively
charged or neutral, if occupied and empty, respectively. Donor-like Shockley-Read-
Hall defects are positively charged, if empty, and neutral, if occupied. Dangling bond
defects are positively charged, if empty, and neutral, if singly occupied and negatively
charged, if doubly occupied.
4.2.2.2 Electrical calculation - interfaces: semiconductor/semiconductor interface
models
Each interface between two adjacent semiconductor layers can be described by three
different interface models: (1) interface model:”no interface”, (2) interface
model:”drift- diffusion interface” and (3) interface model:” thermionic emission
interface”. If no interface is chosen, the transport across the interface is treated in
complete analogy to the “drift diffusion” model. The ‘drift diffusion” interface model
considers the transport across the heterojunction interface in the same way as in the
bulk layers, thereby assuming a certain interface thickness. The “thermionic emission”
interface model treats a real interface which interacts with both adjacent semiconductor
layers.
4.2.2.3 Electrical calculation - boundaries: semiconductor/semiconductor interface
models
The electrical front/back contacts of the semiconductor stack are usually assumed to be
metallic, in order to be able to withdraw a current. However, they may also be
insulating in order to be able to simulate some specific measurement methods like for
example quasi steady state photoconductance (QSSPC) or surface photovoltage (SPV).
Till date, four different boundary models for the interface between the contact and the
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semiconductor adjacent to the contact can be chosen: (1) “flatband
metal/semiconductor contact”, (2) “Schottky metal/semiconductor contact”, (3)
“insulator/semiconductor”. The boundaries serve as a boundary condition for the
system of differential equations describing the semiconductor stack, thus three
boundary conditions for the potential and the electron/hole currents at the front and at
the back side of the stack have to be stated.
4.3 Parameters used for CuInSe2 and CuInGaSe2 solar cell
simulation
In order to numerically model the CuInSe2 and CuInGaSe2 based solar cells, the
variables in the semiconductor transport equations should be correctly given. The
parameters, such as bandgap energy, effective density of states, dielectric constants,
etc., are the properties of the material. Unlike, silicon whose properties is extensively
investigated and standardized, the reported values of CuInSe2 and CuInGaSe2 material
parameters vary in a wide range. Table 4.1 and 4.2 summarize the parameters used in
simulation of these solar cell materials.
In the present work, AFORS-HET code is used for simulation to determine the current-
voltage and photoelectroluminescence characteristic of solar cells. AFORS-HET has
been quite successful in predicting the I-V and photoelectroluminescence
characteristics for variety of heterojunction solar cells [8-9].
4.4 Results and discussion
4.4.1 Copper Indium Diselenide (CIS) based solar cell.
CuInSe2 (CIS) and related materials form a class of materials useful for photovoltaic
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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applications due to their peculiar optical, electrical and structural properties [10]. The
CIS enjoys considerable interest for photovoltaic application because of its suitable
direct bandgap (1.04 eV), high optical absorption coefficient, a moderate surface
recombination velocity and the radiation resistance, which give an opportunity to
fabricate the low cost, stable and highly efficient thin film solar cells [11-15]. Many
investigators have tried to improve the experimental efficiency of the cells, by tailoring
the physical parameters of the participating layers in the thin film solar cells. Also, the
variation of the Cu/In ratio, carrier concentrations, resistivity, thickness of CIS
absorber, phases, etc. play important roles. In the present work, heterojunction of
ITO/CIS/CdS/ZnO:Ag thin film solar cells has been designed and performance is
analyzed by computer simulation [14]. The cell parameters like open circuit voltage
(Voc), short circuit current (Isc), efficiency (η) and fill factor were also evaluated. The
J-V characteristics of the cell are obtained by varying optimum operating temperature.
Table 4.1: The parameters used for CuInSe2 solar cell simulation.
Parameters Standard
Values Reference
Value
used
Band gap (Eg) (eV) 0.95-1.05 [19] 1.05
Electron affinity (chi) [eV] 5.48
4 [20] 4
Dielectric constant (dk) 12
15 [21] 15
Effective conduction band density (Nc) cm-3
1016
-1018
[22] 1E18
Effective valence band density (Nv) cm-3
1016
-1018
[23] 8E18
Acceptor concentration (Na) cm-3
1016
-1018
[24] 9E18
Donor concentration (Nd) cm-3
1016
-1018
[25] 0
Electrons mobility (µn) (cm2/V.s) 10-400 [26] 400
Holes mobility (µp) (cm2/V.s) 10-400 [27] 300
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Table 4.2: The parameters used for CuInGaSe2 solar cell simulation.
The parameters obtained by varying optimum operating temperature are enlisted in
table 4.3 [16].
The tables revealed that the open circuit voltage (Voc) is the most affected parameters
under temerature. The impact of increasing temperature on Voc is shown in Fig. 4.1. It
shows that the Voc decreases with increase in temperature because of the temperature
dependence of the reverse saturation current. The reverse current is due to the diffusive
flow of minority electrons or holes. Hence Is, reverse saturation current depends on the
diffusion coefficient of electron and holes. The minority carriers are thermally
generated and highly sensitive to temperature change. The reverse saturation current Is
is given as:
Tk
AeEI
B
g
s
4.3
Parameters Values Reference Value used
Band gap (Eg) (eV) 1.05-1.65 [28] 1.4
Electron affinity (chi) [eV] 4.5
4.2 [29] 4.2
Dielectric constant (dk) 13.6
10 [30] 10
Effective conduction band density (Nc) cm-3
1016
-1018
[31] 2.2E18
Effective valence band density (Nv) cm-3
1016
-1018
[32] 1.8E19
Acceptor concentration (Na) cm-3
1016
-1018
[33] 2E16
Donor concentration (Nd) cm-3
1016
-1018
[32] 0
Electrons mobility (µn) (cm2/V.s) 100 [32] 100
Holes mobility (µp) (cm2/V.s) 25 [32] 25
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Where A is nearly constant independent of temperature and dependent on diffusion
coefficient of holes and electrons. Eg is the bandgap of the semiconductor, kB is the
Boltzmann constant, ʋ is a constant and T is the absolute temperature. The most
significant effect on the solar cell parameter is due to the intrinsic carrier concentration
(ni). Narrowing of bandgap energy may accelerate the recombination of electron-hole
pairs (EHP) between valence and conduction bands. At high temperature, the band gap
energy is unstable which may lead to recombination of electrons and holes across the
regions. Hence slightly decrease in Jsc as shown in table 4.3. Fill factor and efficiency
depends on Voc and Jsc, therefore reduction of Voc on increasing operating temperature
leads to the reduction in fill factor and efficiency [17].
The thickness of the optimum CdS buffer layer was kept within 50nm -60nm [18]. As
the thickness of CdS is increases the Voc and Jsc decreases. This results in higher
photon absorption loss. Due to reduction in Voc and Jsc fill factor of the cell also
decreases. As shown in Table 4.4 as buffer layer increases, more photons which carry
the energy are being absorbed by this layer. Therefore it will lead to the decrease in the
number of photons in the absorber layer. The 0.065 thickness of the CdS µm gives the
efficiency of about 5.19% which is highest.
According to Beer’s law, the thickness of the absorber should be sufficient to absorb
most of the photons from the solar spectrum, when they impinge on the solar cells.
Ninety percent of photons can be absorbed by the film thickness of > 1µm, therefore
1.5 µm-2.5µm thick absorber is enough [34,35]. In ITO/CIS/CdS/ZnO:Ag structure
CIS has been used as an absorber and increase of the thickness of the absorber results
in the improvement in the efficiency of cell.
The thickness of CIS absorber was kept 0.70 μm to 0.95 μm . Table 4.5 shows the
effect of the CIS absorber layer thickness on Voc and Jsc. Both parameters increase with
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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the thickness of CIS absorber layer. Longer wavelength photons will be deeper within
the CIS absorber layer as shown in Fig. 4.3. Thus the efficiency and fill factor
increases on increasing the thickness of CIS absorber increases. The efficiency is best
at the thickness of 0.95 µm CIS solar cell and equal to 6.17 %.
Figure 4.1: J-V Characteristics of ITO/CIS/CdS/ZnO:Ag structure at various temperatures.
Table 4.3: J-V parameters of CIS solar cell at various temperatures.
The role of window layer is also critical in the thin film solar cells in ITO/ZnO: Ag/p-
Cds/n-CIS/Au. The CIS absorber layer in the present calculation is designed onto the
CdS window layer. Table 4.6 enlist the parameters used during simulation process. In
T(K) Voc (mV) Jsc (mA/cm2) FF(%) η (%)
300 682 8.964 82.06 5.017
310 666 8.992 82.11 4.921
320 650 9.019 81.51 4.784
330 635 9.045 75.05 4.312
340 619 9.07 76.69 4.309
350 605 9.094 77.91 4.290
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present simulation process, the solar radiation AM 1.5 is adopted as the illumination
source with a power density of 100 mW/cm2. The PEL and J-V characteristics of the
cell is given in Figs. 4.4 and 4.5
Figure 4.2: J-V Characteristics of ITO/CIS/CdS/ZnO:Ag structure at various thickness of CdS
Table 4.4: J-V parameters of CIS solar cells at various thickness of buffer CdS.
4.4.1.1 Optical and electrical properties
(i) Photoelectroluminescence
The optical model is obtained by Lambert-Beer is absorption method. The external
illumination of AM 1.5 radiation is adopted as the illumination source with a power
density of 100 mW/cm2. The emitted radiation according to generalized Planck’s
CdS thickness
(µm) Voc (mV) Jsc (mA/cm
2) FF(%) η (%)
0.055 608 9.57 77.78 4.53
0.058 610 9.84 77.74 4.67
0.060 611 10.03 77.63 4.76
0.062 613 10.20 77.53 4.85
0.065 618 10.89 77.24 5.19
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Figure 4.3: J-V Characteristics of ITO/CIS/CdS/ZnO:Ag structure at various thickness of CIS.
Table 4.5: J-V parameters of CIS solar cells at various thickness of CIS absorber.
equation can be calculated as:
1/()(exp
1.
),(2)(
5
kTxExEhc
xdxcI
FPFn
4.4
Where α is the absorption coefficient, λ is a given wavelength, EFn and EFp is the
quasi-fermi level of electrons and holes and I(λ) is the emitted intensity of photons.
The wavelength dependent emitted intensity to the back and front is calculated by
CIS thickness
(µm) Voc (mV) Jsc (mA/cm2) FF(%) η (%)
0.70 619.5 11.3 82.06 5.40
0.80 622.7 11.69 76.96 5.60
0.85 625.8 12.08 76.71 5.79
0.90 627.3 12.45 76.63 5.98
0.95 628.9 12.81 76.54 6.16
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integrating over the whole structure, taking photon re-absorption into account. External
illumination or applied voltage that cause quasi-Fermi level splitting are specified.
Furthermore the wavelength region for which the emitted intensity is calculated can be
selected.
Figure 4.4 shows photoluminescence (PL) spectra of ITO/ZnO:Ag/p-Cds/n-CIS/Au
heterojunction solar cell at different temperatures. As shown in Figure 4.4 PEL spectra
at 250 and 275 K show two peaks at the wavelengths 393 nm and 403 nm respectively.
With increase in temperature the intensity of PL spectra also increases. The peaks also
shift towards higher wavelength. This is because the sensitivity towards interface state
densities (Dit) increases as temperature increases. It means spectral response increase
as device temperature increases.
Table 4.6: Parameters used in the simulation of ITO/ZnO: Ag/p-Cds/n-CIS/Au cell.
(ii) Electrical properties
The electrical front/back contacts of the semiconductor stack are usually assumed to be
metallic, in order to be able to withdraw a current. However, they may be insulating in
Parameter p-CIS n-CdS ZnO
Thickness (nm) 1 80 80
Bandgap (eV) 1.05 2.4 1.924
Dielectric constant 15 10 9
Electron affinity 4 4.2 4.4
Electron mobility 400 0 100
Hole mobility 300 0 25
Conduction band density 1E18 2.8E19 2.8E19
Effective valence banddensity 8E18 2.68E19 2.68E19
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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Figure 4.4: PEL spectra of of ITO/ZnO:Ag/p-Cds/n-CIS/Au heterojunction solar cell
under different temperature.
Figure 4.5: Current-voltage simulation under AM 1.5 illumination at illumination
intensity of 100mW/cm2.
order to simulated some specific measurements like quasi steady state photo
conductance (QSSPC) of surface photovoltage (SPV). This measurement is performed
by varying the external voltage at the boundaries and plots the resulting external
current through the semiconductor stalk in order to obtain the current – voltage (Fig.
4.5) characteristic of the simulated structure. For each voltage the total current through
the structure (the sum of the electron and hole current at a boundary grid point) is then
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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calculated. This can be done in the dark or under an illumination. The measurement
model can iterates the specific data points to determine the maximum-power point
(Impp), open –circuit voltage (Voc), short circuit current (Isc) and thus calculate the fill-
factor (FF) and the efficiency (Eff) of the solar cell. The parameters evaluated are
shown in Table 4.6 along with the available experimental results.
mpp mpp
oc sc
V IFF
V I 4.5
scocscoc
mppmpp
IV
FillFactor
IV
IV 4.6
The efficiency of 10.33% is achieved by designing CuInSe2 based heterojunction solar
cell in the present study.
4.4.2 CIGS based solar cell parameters
The Cu(InGa)Se2 (CIGS) based thin film solar cells have earned special interest among
the family of solar cells because their efficiency has been significantly enhanced to
20%. There are several important merits in CIGS for each high efficiency:(i) the
bandgap of CIGS can be varied by varying Ga composition to obtain required band gap
that meets the solar spectrum to absorb most of the photons (ii) in order to make abrupt
junction with window layer, the carrier concentration and resistivity of CIGS can be
varied by controlling its intrinsic composition without using extrinsic dopants. The
thickness of 1.5-2.5 µm for CIGS layer is enough to form CIGS based thin film solar
cells beacuse of its direct bandgap, whereas in the case of Si based solar cells, the Si
needs thicker layers about 250 µm owing to indirect band gap. In present simulation
process, the solar radiation AM 1.5 radiation is adopted as the illumination source with
a power density of 100 mW/cm2 as shown in Fig. 4.6.
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Table 4.6. J-V parameters of ITO/ZnO:Ag/p-Cds/n-CIS/Au thin film solar cell.
4.4.2.1 Optical and electrical properties of CIGS based solar cell
(i) Photoelectroluminescence
Figure 4.7 shows photoelectroluminescence spectra simulated at various temperature
of the device. On increasing temperature spectral response flux of the device also
increases. Molebedenum is used as a back contact or metallic contact of the cell to
obtain good conductivity. There is an increase in the flux as the operating temperature
of the cell increases it means number of electrons and holes emission is maximum at
400K. The electrical conductivity of the CIGS cell is obtained by keeping device
temperature at 400K.
Figure 4.6: Schematic diagram of the CIGS based thin film solar cell.
Cell structure Voc(V) Jsc(mA/cm2)
Fill
Factor η Growth Reference
ITO/ZnO:Ag/p-Cds/n-
CIS/Au 304 56.8 59.78 10.33 Present
Glass/ZnO:Al/CdS/CIS/Au 350 39.8 58 8.1 CBD 10
Glass/TCO/CdS/CIS/Au 220 32.8 29 2.06 CBD 11
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
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Figure 4.7: Photoelectroluminescence of the cell
(ii) Electrical properties
Fig. 4.8 shows the current voltage characteristics of ITO/Mo/CIGS/CdS/ZnO/Al
heterojunction solar cells. The solar cell parameters like open circuit voltage as (Voc)
512 mV, short circuit current is 40 mA/cm2, fill factor is 80.66 and efficiency is
16.52%.
Figure 4.8: I-V characteristics of the cell.
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
97
4.5 Conclusions
The present chapter describes the results of CuInSe2 and CuInGaSe2 based solar cell
devices using a computer simulation code namely AFORS-HET. We have investigated
the cell parameters like open circuit voltage, short circuit current, efficiency and fill
factor for both CuInSe2 and CuInGaSe2 systems. Our results show that the open circuit
voltage is the most affected parameter with temperature. The Voc decreases with
temperature due to the temperature dependent behavior of reverse saturation current
arising from the diffusive flow of minority electrons or holes. The parameters fill
factor and efficiency depend on Voc and Jsc. The temperature also affects the intensity
of PL spectra, which show increasing trend with increasing temperature. Our
simulation results show that the efficiency is about 10 and 16 % respectively for CIS
and CIGS systems. CdS is used as a buffer layer in CuInSe2 and CuInGaSe2
respectively. For CuInSe2 and CuInGaSe2 based solar cell 10.2 % and 16.5 %
respectively efficiency is achieved. Work is in progress for further improvement in the
efficiency of these devices.
Simulation of heterojunction solar cells with AFORS-HET Chapter-4
98
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