Efficiency Enhancement of Ultra-thin CIGS Solar Cells Using Bandgap Grading and Embedding Au Plasmonic Nanoparticles

The objective of this study is to enhance the efficiency of copper indium gallium selenide (CIGS) solar cells. To accomplish that, composition grading of absorber layer was carried out by using SILVACO's technology aided computer design (TCAD) ATLAS program. Results showed a meaningful improvement of output parameters including open-circuit voltage (V_oc), short-circuit current (I_sc), fill factor (FF), and power conversion efficiency (η). For further performance improvement of the cell, Au plasmonic scattering nanoparticles were loaded on the top of the ZnO window layer. Plasmonic nanoparticles can restrict, absorb, navigate, or scatter the incident light. By using the spherical Au nanoparticles, a very good increase in the light absorption in the cell over the reference planar CIGS solar cell was observed. The highest η = 19.01% was achieved for the designed ultra-thin bandgap-graded CIGS solar cell decorated by Au nanoparticles.

Keywords: CIGS; Bandgap grading; FDTD; Light trapping; Surface plasmon

Solar cells are semiconductor devices that absorb the sunlight and generate electron-hole pairs. Compared with c-Si costly solar cells, the economic and high efficient thin film solar cells can pave the way to generalize the photovoltaic (PV) technology across the world. Copper indium gallium selenide (CIGS) solar cells are one of the most promising candidates to develop the PV technology. CIGS is an alloy of CInSe2 and CGaSe2 which result in a quaternary compound with properties common between both components. Despite several advantages of CIGS-based solar cells, further development and optimizations are needed to improve their efficiency. The well-known Shockley-Queisser limit evaluates the maximum power conversion efficiency around 33.7% for a single-junction solar cell [[1]]. Nevertheless, the highest reported efficiency for CIGS solar cells is even much lower than this limited value [[2]]. Hence, it seems necessary to find new ways to improve the performance of CIGS-based solar cells. In the present study, we are pursuing two strategies to enhance the efficiency of CIGS solar cells: (a) bandgap grading and (b) using metallic plasmonic nanoparticles (NPs). These will be accomplished by numerical simulations based on finite-difference time-domain (FDTD) method. Along with experimental endeavours, the numerical simulation can be a great help to save time and cost plus better understanding of the mechanisms involved in the considered device.

Bandgap grading is a method that is used to increase the efficiency of CIGS solar cells by varying x = Ga/(In + Ga) in absorber layer. So far, several experimental and theoretical studies have been done on the effects of bandgap grading on the performance of CIGS solar cells [[3]–[8]]. Accordingly, 1–3% efficiency improvement has been achieved. However, only few works have been reported on dual-graded bandgap CIGS solar cells. In the present study, bandgap dual-grading of an ultra-thin CIGS solar cell will be performed. Developing ultra-thin layers in solar cells make them more economic and eco-friendly. However, it may cause some degradations related to shortening of diffusion length that we intend to overcome those by using bandgap grading and plasmonic NPs. It has been shown that the trap density in CIGS solar cells is a function of Ga concentration [[9]]. It implies that higher Ga content may not cause higher efficiency. Hence, an optimization problem rises; what is the optimum value of x in CuInxGa1−xSe2 to present the best performance? Finding an appropriate answer is one aim of the present study. Using plasmonic metallic NPs is another way to improve the performance of ultra-thin CIGS solar cells. Increasing the optical path length inside the cell may cause increasing light trapping that in turn raises the cell efficiency. Utilizing plasmonic nanostructures can increase the absorption of light owing to excitation of localized surface plasmons. Surface plasmons are the free electron oscillations that happen at the interface between metals and dielectrics. Noble metals like Au, Ag, Al, and Cu show strong plasmonic effect. Reports on plasmonic nanoparticles embedded in CIGS solar cells are very limited. In the present study, the effect of embedment of Au NPs on the surface of CIGS solar cell will be studied. Au NPs were used in this study because of (a) strong interaction between Au NPs and ZnO layer due to small differences in lattice parameters between Au (111) and ZnO (101) atomic planes, (b) strong surface plasmon resonance (SPR) response compare to other metallic NPs, and (c) very high stability against oxidization in air that is very crucial for solar cells. Combination of the bandgap-graded absorber layer and surface-embedded plasmonic NPs to obtain highly efficient CIGS solar cells is the main goal of this article.

The basic structure includes Mo layer as the back contact, a CIGS absorber layer, a CdS buffer layer, and a ZnO window layer. The simulation was carried out by using the values that have been stored in ATLAS library (Table 1). The simulated cell was irradiated with AM1.5 spectrum. Meanwhile, the temperature was kept constant at 300 K.

The input values of the parameters used in the simulation. Eg, χ, 휀r, Nc/Nv, μe/μp, and NA/ND denote the bandgap, electron affinity, dielectric permittivity, CB/VB density of states, electron-hole mobility, and shallow uniform acceptor/donor density, respectively

The preliminary requirement for the simulation of a solar cell is the precise modelling of electron-hole pair generation. LUMINOUS is an optoelectronic simulation module in ATLAS that evaluates the photogeneration (electron-hole pair generation) at each mesh point in a defined structure in ATLAS by doing two simultaneous calculations. LUMINOUS uses the refractive index to carry out an optical ray trace in the cell. The rate of light transmission and reflection then is determined through differences in n values across material boundaries. By tracking the path of light from the source to a mesh point, the optical intensity can be determined at that point by LUMINOUS. On the other hand, the extinction coefficient κ is utilized to calculate the rate of absorption and photogeneration for the evaluated optical intensity at each mesh point. Altogether, the explained simulations give the wavelength-dependent photogeneration throughout a solar cell. To increase the precision of the modelling, finer meshing was applied at junctions. The rest of the physical parameters including electrons and holes lifetime and mobility, surface recombination velocities, and doping levels were then defined. The scheme of the modelled basic CIGS solar cell is shown in Fig.1. The finite element mesh grids are shown in Fig. 2. The surface plasmon effect was modelled by loading Au NPs on the ZnO window layer of the cell. Gold loaded on ZnO layer occurs in different oxidation states: Au+, Au3+, Auδ+, Au0, Auδ− [[10]]. However, the coupling of ZnO with Au NPs, considering HAuCl4 (Au3+ ions) as the source of Au in an appropriate Au/ZnO ratio, can cause a suitable binding between ZnO and Au NPs [[11]]. By considering the surface plasmon effects, the FDTD method was used for calculating the wavelength-dependent total reflection of the front surface of the designed CIGS solar cell. The FDTD method employs finite differences as approximations to both the spatial and temporal derivatives that appear in Maxwell's equations (specifically Ampere's and Faraday's laws). Meanwhile, the absorption coefficient was calculated for all layers of the cell. The outputs of this model were saved as input for ATLAS.

Graph: Fig. 1 The modelled traditional CIGS solar cell

Graph: Fig. 2 Mesh specification of the basic structure of CIGS solar cell

Modelling was initiated with a basic cell (Fig. 1) to verify the appropriate implementation into ATLAS and the capability to produce outputs. The calculated and measured solar cell parameters including the short-circuit current (Isc), open-circuit voltage (Voc), fill factor (FF), and power conversion efficiency (η) are shown in Fig. 3. The x value of 0.3 is usually considered for fabrication of CuInxGa1−xSe2 compound. This value was taken in the first round of simulation. Results are quite coincident with the reported values [[12]]. This confirms the validity and accuracy of the simulation process.

Graph: Fig. 3 Simulated and experimental measured IV curves along with the related output parameters for a typical CIGS solar cell for x = 0.3

Using expensive elements including In and Se in CIGS compound increases the production price. One way to overcome this challenge is to decrease the thickness of CIGS layer. However, this will lead to shortening of the photon travelling path that in turn results in decrease of photocurrent. Results of simulations on the ultra-thin CIGS solar cells show the best power conversion efficiencies in the range of 10–11% [[14]], which limits the application of this type of CIGS solar cell. Figure 4 shows the calculated IV curve of an ultra-thin CIGS solar cell with an absorber layer thickness of 750 nm. As it was expected, all output parameters decreased with the decrease of CIGS layer thickness.

Graph: Fig. 4 The calculated IV curve along with output parameters of an ultra-thin CIGS solar cell

Inclusion of graded Ga concentration within the absorber layer is an efficient method to increase the overall efficiency of CIGS solar cells. Usually, three different profiles for grading are used: (a) back grading, Ga concentration is increased moving towards the back contact; (b) front grading, Ga concentration is decreased moving towards the back contact; and (c) dual-grading, higher Ga content towards top and bottom contacts with a minimum Ga concentration in the middle of the absorber layer. The bandgap of CuInxGa1−xSe2 compound varies from 1.01 to 1.67 eV when the x composition is changed from 0 to 1 (Fig. 5) according to the following equation [[15]]:

Graph

Graph: Fig. 5 Bandgap variation with x values for CIGS compound

After verification of the basic cell, the first change was the implementation of bandgap grading on the ultra-thin absorber layer (750 nm). At the first attempt, a single gradient in the absorber layer was examined in which x was varied over a range of slopes all with a constant value of x = 0.3 at the midpoint. Two different cases of decreasing and increasing Ga mole fractions going from top to bottom were tested and the maximum efficiency of 15.76% was recorded for the cell with the smallest forward graded absorber layer. This can be linked to the increased internal electric field arisen from the concentration gradient in the absorber layer. In the second attempt, a dual-grading profile (Fig. 6a) was examined in which the absorber layer was divided into two equal sections to be allowed to specify two Ga concentration gradients: (1) a falling gradient from top to bottom in the top section which causes a front field that sweeps photogenerated carriers towards the p-n heterojunction and (2) a rising gradient from top to bottom in the bottom section which gives a back field that sweeps photogenerated carriers towards the back contact. The combination of these two fields should increase the overall efficiency of the cell by sweeping carriers towards the contacts before they can recombine.

Graph: Fig. 6 Grading profiles used for absorber layer. a Triangular profile. b Trapezoidal profile

The highest efficiency of 16.12% was obtained for the cell with the smallest negative slope. This slope corresponded to the top absorber layer with Ga mole fraction from 0.31 to 0.3 going from the top to the bottom of the layer. For the underlying layer, the Ga mole fraction was increased from 0.3 to 0.31 going from the top to bottom. Much like the single-absorber layer simulations, the higher magnitude negative slopes resulted in increases in the open-circuit voltage. The short-circuit currents decreased significantly for these higher slopes, resulting in an overall decrease in efficiency. Despite promising results came out of the mentioned single- and dual-graded absorber layer, the best output was achieved by a trapezoidal profile (Fig. 6b) of grading accomplished on a three-stage processed CIGS layer with a constant content of Ga in the middle layer (250 nm) and a decreasing Ga concentration from the top layer (250 nm) plus an increasing Ga concentration profile from the mid layer to the bottom layer (250 nm). The resulting structure of this profile is illustrated in Fig. 7. The results of these simulations led to a cell with the highest efficiency of 16.80%, as illustrated in Fig. 8. All other output parameters improved after performing the mentioned trapezoidal grading procedure (listed in inset of Fig. 8). Compared with the common thick CIGS solar cells, the designed modelled ultra-thin solar cell shows a quite high performance.

Graph: Fig. 7 The three-stage processed CIGS layer for dual-grading of an ultra-thin CIGS solar cell

Graph: Fig. 8 The calculated IV curve along with output parameters for an ultra-thin trapezoidal-graded CIGS solar cell

In the next step of optimization of the proposed ultra-thin CIGS solar cell, Au nanoparticles were loaded on the topmost layer of the cell. Au has low tendency to undergo oxidation and is very stable when is exposed in ambient temperature. The designed configuration has been shown schematically in Fig. 9.

Graph: Fig. 9 Schematic view of 3-D CIGS-based plasmonic solar cell

In this study, the planar ZnO window layer was replaced with a ZnO window layer where Au NPs have been distributed on it periodically. To account for the morphology effect of this layer, the FDTD method was used to calculate the related optical constants. To define a new compound in ATLAS, the pertinent refractive index and extinction coefficient are needed. Figure 10 shows the calculated refractive index and extinction coefficient of ZnO window layer decorated by Au NPs at different radii. Afterward, the calculated n and κ were fed to ATLAS for the simulation of the designed solar cell.

Graph: Fig. 10 The FDTD calculated refractive index (n) and extinction coefficient (κ) of ZnO window layer and ZnO window layer decorated by Au nanoparticles with different radii

For light-capturing purposes, the metallic nanoparticles (MNPs) are placed on semiconducting substrates with higher refractive indices than MNPs to trap the light through scattering effect. The interface between a material with positive dielectric constant and a material with negative dielectric constant (metals for instance) can cause the propagation of a specific kind of electromagnetic waves called surface plasmons that are limited to surface zone. The mentioned superficial waves possess an electrical field component that decreases exponentially moving away from the surface. Now, if the surface is uneven and rough or covered with MNPs, then, there will be a static wave called localized surface plasmon (LSP) instead of travelling wave. Both kinds of plasmons can be used to increase the light absorption in solar cells. To see how the efficiency of the solar cell with plasmonic nanoparticles (PNPs) increases compared with a solar cell without PNPs, the absorption enhancement parameter g(λ) is defined as follows:

2 $$g\left(\lambda \right)=\frac{{\mathrm{QE}}_{\text{PNPs}}}{{\mathrm{QE}}_{\text{Bare}}}$$

Graph

where QEPNPs and QEBare stand for the quantum efficiency (QE) for the solar cell with PNPs and without PNPs (bare cell), respectively. The g values larger than 1 mean that the PNPs enhance the absorbed photon number compared with the bare cell. Figure 11 displays the variation of g with diameter of Au NPs.

Graph: Fig. 11 The absorption enhancement parameter g(λ) versus optical wavelength for different diameters of spherical Au NPs loaded on the window layer of an ultra-thin CIGS solar cell

As it comes from the figure, the QE of the solar cell increases with the diameter of NPs and a blue shift of the local extremum peak between 400 and 700 nm is seen. Meanwhile, the absorption enhancement due to Au NPs with 100 nm covers wider spectrum. So, we consider PNPs with 100-nm diameter for the next step of optimization process. The absorption per unit volume can be calculated from the divergence of the Poynting vector [[16]].

3 $$P_{\mathrm{abs}}=-\frac{1}{2}\text{real}\left(\nabla .\overrightarrow{P}\right)$$

Graph

It can be shown that the above formula is equivalent to [[16]]:

4 $$P_{\mathrm{abs}}=-\frac{1}{2}\text{real}\left(\mathit{i\omega \epsilon }{E}^2\right)=-\frac{1}{2}\omega {\left|E\right|}^2\text{imag}\left(\epsilon \right)$$

Graph

Hence, to evaluate the absorption as a function of space and frequency, it would be enough to know the electric field intensity and the imaginary part of the permittivity. Both quantities are measured easily in an FDTD simulation. Figure 12 illustrates the FDTD-modelled absorption profile for the resonance at λ = 600 nm for ZnO window layer region of an ultra-thin CIGS solar cell undecorated (a) and decorated (b) by Au NPs. It is evident from the figure that the Au NP has increased the light absorption drastically by the forward scattering of the incident light stemming from the SPR. The SPR is a result of interaction of conduction electrons of metal NPs with incident photons that has attracted a lot of attention in optoelectronic applications [[17]–[20]]. Figure 13 depicts the variation of g(λ) with the periodicity of Au NPs array. As it is obvious from the figure, the lowest absorption occurs for the periodicity equal to the diameter of nanoparticle. This can be linked to the strong coupling between the neighbouring NPs that gives rise a serious degradation of the absorption enhancement due to increased nonradiative losses [[21]]. On the contrary, the g value increases rapidly with the distance between nanoparticles and reaches the maximum value of 1.25 for the periodicity of 125 nm. After that, it decreases steadily and reaches 1 for longer wavelengths. This happens because of large dilution of the space [[21]]. To avoid both of strong coupling between the neighbouring NPs and large dilution of the space, we choose the optimal value of 125 nm for the periodicity of Au NPs array on ZnO window layer for the final step of the optimization. Figure 14 exhibits the IV curve along with the calculated output parameters for the optimized ultra-thin bandgap-graded CIGS solar cell with Au PNPs loaded on ZnO window layer. Inset of Fig. 14 shows comparatively the IV curves of different samples modelled in this study. As it comes from the figure, almost all parameters of the cell have been improved by bandgap grading and using PNPs in an optimized size and period. The main influence of Au NPs is seen on the Isc which can be linked to the scattering of light into the cell that causes generation of more electron-hole pairs. Upon embedment of Au NPs on the window layer, the short-circuit current increased by 17% for the ultra-thin-graded CIGS solar cell. As a result, the high power conversion efficiency of 19.01% was achieved for the optimized ultra-thin plasmonic CIGS solar cell.

Graph: Fig. 12 FDTD modelling of the propagation of scattered light for the resonance at λ = 600 nm by Au PNP in an ultra-thin CIGS solar cell. The scale bar represents the normalized intensity |E/E0|2

Graph: Fig. 13 The absorption enhancement parameter g(λ) versus periodicity of the spherical Au NPs (diameter = 100 nm) array embedded on the window layer of an ultra-thin CIGS solar cell

Graph: Fig. 14 IV curve along with the output parameters for an ultra-thin bandgap-graded CIGS solar cell with Au PNPs loaded on ZnO layer. Inset shows comparatively the simulated IV curves for the traditional thick CIGS solar cell, traditional ultra-thin CIGS solar cell, traditional ultra-thin-graded CIGS solar cell, and ultra-thin-graded CIGS solar cell decorated by Au NPs

In summary, performance improvement of an ultra-thin CIGS solar cell was analyzed by applying bandgap grading and using Au plasmonic nanoparticles array. Degradation of output parameters was observed when the thickness of absorber layer was decreased. By applying trapezoidal bandgap grading with optimized sleeps on both sides of the middle section of CIGS layer, the occurred degradation due to downsizing of absorber layer was compensated. Then, Au nanoparticles were loaded on the surface of ZnO window layer to navigate more light into the cell. Different size of nanoparticles was examined and nanoparticles with diameter of 100 nm showed the best surface plasmonic effect. The period of nanoparticles on the surface of window layer was also studied and the period of 120 nm showed the best result. In the final step of optimization, the combination of bandgap grading and surface plasmon effect was used. This resulted in remarkable enhancement of the cell efficiency around 19%. Fundamental discussion was done whenever it was necessary.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.