CC BY
31TECHNICAL SCIENCES
STUDY OF THE EFFECT OF OPTICAL LAYER THICKNESS ON THE PHOTOELECTRIC PARAMETERS OF SILICON-BASED SOLAR CELLS USING SENTAURUS TCAD
Komilov M.
Andijan State University, master student
ABSTRACT
There are many ways to improve the optical properties of silicon-based solar cells. One of them is to cover the surface of solar elements with optical layers. One of the important tasks is to study the effect of different optical materials on the properties of silicon and to determine the optimal conditions for the thickness of the optical layers covering the surface of solar cells. In this paper, the effect of SiNx and SiO2 on the optical properties of coated silicon-based solar cells has been extensively studied. In this case, the optimal thickness value for SiNx was determined by modeling at 75 nm and for SiO2 at 100 nm. It was also found that when the surface of a silicon-based solar cell is coated with SiNx, it is 1.1 times more effective than SiO2.
Keywords: Optical parameters, solar cell, silicon, Sentaurus TCAD, absorption.
I INTRODUCTION
Solar elements are now becoming the main source of energy. Because the world is running out of non-renewable energy sources. The best solution for the economy at this time is, of course, renewable energy sources. There are many types of solar cells. The cheapest of these are silicon-based solar cells. Silicon is one of the most common elements in the world. If we divide the losses into two, the first is optical and the second is electrical. By covering the solar elements with the desired optical layers, both its optical and electrical properties can be improved. For example, by coating the surface of silicon-based solar cells with SiÜ2 or SiNx [1]. This is because both optical materials have the property of passivating the silicon surface, ie reducing the surface recombination [2].
The number of modeling programs is growing day by day [3]. Reliable and widely used programs by scientists today are Silvaco TCAD (Technology Computing Aided Design) and Synopsys Sentaurus TCAD. Because these programs are designed for high-precision modeling of semiconductor devices in 3D/2D/1D sizes. However, if we want to model the interaction of an entire system and system with the environment, rather than a semiconductor device, it is advisable to use Comsol Multiphysics [4-5].
II METHOD
The modeling of solar cells was mainly based on the Sentaurus TCAD program, which developed a model of thin silicon-based solar cells.
2.1 PROGRAMMING METHOD
Synopsys's Sentaurus TCAD software was used to model the solar cells. The Centaurus TCAD consists of a total of 20 instruments, of which 17 are primary and 3 are auxiliary instruments. There are 4 main tools used to model solar cells. These are Sentaurus Structure Editor (SDE), Sentaurus Device (SDevice), Sentaurus Visual (SVisual) and Sentaurus Work Bench (SWB).
SDE is designed to create a geometric model that can work independently. That is, if the user does not have knowledge of programming, it is possible to draw a geometric model using shapes. If you have algorithmic design and programming skills, you can create a geometric model by writing code directly using the
Tool Command Language (TCL). In addition to creating a geometric model in the SDE, the following is done: the numerical method is set up to perform calculations, the material types of all fields are declared, the required type of input concentration, the amount is given, the contacts are activated.
SDevice is a multi-dimensional high-level device simulator designed to simulate the electrical, thermal, and optical properties of silicon-based and other semiconductor devices. SDevice is a next-generation software package for designing and optimizing current and future semiconductor devices. In addition, the SDevice numerical method simulates the electrical properties of a single semiconductor device in isolation or in a semiconductor device chain. Terminal currents, voltages and charges are calculated on the basis of physical equations, ie the distribution and conduction mechanisms of charge carriers.
SVisual results allow visualization in one, two and three dimensions. Graphs are also generated. The results obtained can be obtained for processing the database. One of the most important characteristics of semiconductor devices is the ability to view the volt-ampere characteristic graphically and process it for articles or presentations.
SWB allows all instruments to be interconnected and work together. Because all the tools are designed to work independently. That's why we have to put it all together in one environment. This environment is performed by SWB. The possibilities of SWB are wide and it is possible to get results for several different values of the model at the same time. The advantage of this is that you can assign values to a variable on an SDevice or SDE.
The geometric model of the solar cell was made in SDE with the variable thickness of the optical layer on its surface. The variable is programmed so that the values are passed through the swb. This allows different results to be obtained by giving multiple values to a single model. The thickness of the solar cell ranges from 100 to 300 microns in industrial production. This allows the result obtained in the model to be compared with the result obtained in the experiment.
2.2 Theory
There are two main methods used to model the optical properties of semiconductor devices. These are the transfer matrix method and the Ray tracing method. If only the absorption, return, and transition in layers need to be calculated, the use of the transfer matrix method is sufficient and effective. The ray tracing method is designed to calculate the refraction and refraction of light rays, as well as the refraction of refracted and reflected rays in the subsequent environment and on the surface with a decrease in intensity.
When covering the surface of solar cells with optical layers, the main focus is on the light absorption coefficient of the dielectric. And then to its refractive index. This is because the light absorption coefficient of the dielectric should be close to zero and the refractive index should be between silicon and air. If there are more than one optical layer covering the surface of a solar cell, an effective refractive index can be found depending on their order (Formula 1).
f M+\-m ^
n = n
m sup
M+1
n
M+1
sub
(10)
Jg, %
Where:
nm - m-refractive index of antireflection coating nsup refractive index of the top layer nsub - refractive index of substrate M - number of layers
m - the layer sequence number we are looking for. In this paper, Sentaurus Device was used to model the physical properties of a silicon-based solar cell. III RESULTS AND DISCUSSION In modeling silicon-based solar cells, the main focus was on the thickness of the optical layer of the silicon-based solar cell. First, the volt-ampere characteristics for a simple and SiO2-coated solar cell were determined, and a database of these volt-ampere characteristics was generated to plot the photogeneration current as a function of the thickness of the optical layer. The results ranged from 20nm thick to 200nm thick SiNx and SiO2 dielectrics, and Graph 1 was used. From Figure 1, it was found that the optimal thickness for SiNx is 75nm and the optimal value for SiO2 is 100 nm. This is because they have different refractive indices and the absorption coefficients depend on the wavelength.
80
75
70
65
60
55
d, nm
20 40 60 80 100 120 140 160 180 200
Graph 1. Absorption coefficient of200 fim thick silicon coated with optical layer of different thicknesses.
1 - SiNx, 2 - SiO2.
The generation current was found to be high in the solar element coated with SiNx. Because if we look at formula 1, we can see that the most optimal dielectric for silicon and air is SiNx. Figure 2 shows the absorption coefficients of different SiO2 at different thicknesses. Figure 75 shows that 75 nm thick SiO2 improves the absorption of light, mainly at wavelengths
from 0.4 ^m to 0.6 ^m. However, an increase in 100 nm absorption was observed, as we determined the absorption in the general spectrum in Figure 1 above. It is also possible to improve the optical properties of silicon-based solar cells by the introduction of nanoparti-cles [6-11].
Graph 2. The dependence of the light absorption coefficient of a silicon-based solar cell coated with SiO2 of dif
ferent thickness on the wavelength of light.
IV CONCLUSION
In conclusion, it is advisable to cover silicon-based solar cells with different optical layers in order to increase the efficiency and improve the optical properties. When the surface of silicon is coated with SiNx and SiO2, not only the optical but also the kinetic properties of the charge carriers change, that is, the amount of surface recombination of the charge carriers on the silicon surface decreases.
References
1. H. K. Raut, V. A. Ganesh, A. S. Nair, and S. Ramakrishna. "Anti-reflective coatings: A critical, in-depth review". Energy Environ. Sci. 4 (2011), pp. 3779-3804. https://doi.org/10.1039/C1EE01297E
2. Aliev, R., Abduvoxidov, M., Mirzaalimov, N., and Gulomov., J. (2020). Kremniy asosli quyosh ele-mentlarida rekombinatsiya va generatsiya jarayoni. Science and Education, 1(2), 230-235. doi: 10.24412/2181-0842-2020-2-230-235
3. Gulomov, J., Aliev, R., Abduvoxidov, M., Mirzaalimov, A., Mirzaalimov, N. (2020). Exploring optical properties of solar cells by programming and modeling. Global Journal of Engineering and Technology Advances, 5(1), 032-038; doi.org/10.30574/gjeta.2020.5.1.0080
4. Kumari, S. and Babu,S. „Mathematical Modelling and Simulation of Photovoltaic Cell using MATLAB/Simulink Environment", International Journal of Electrical and Computer Engineering (IJECE) Vol. 2, No.1, PP. 26-34, 2012 .
5. D.T. Rover, P.A. Basore and G.M. Thorson, "Solar cell modelling on personal computers," Proc. 18th IEEE Photovoltaic Specialists Conference, Las Vegas, pp. 703-709, 1985
6. Gulomov, J., Aliev, R., Nasirov, M., and Ziyoitdinov, J. (2020). Modeling metal nanoparticles influence to properties of silicon solar cells, Int. J. of Adv. Res. 8(Nov), 336-345; doi.org/10.21474/IJAR01/12015
7. Aliev, R., Gulomov, J., Abduvohidov, M. et al. (2020) Stimulation of Photoactive Absorption of Sunlight in Thin Layers of Silicon Structures by Metal Nanoparticles. Appl. Sol. Energy 56, 364-370; https://doi.org/10.3103/S0003701X20050035
8. Gulomov, J., Aliev, R., Mirzaalimov, A., Mirzaalimov, N., Kakhkhorov, J., Rashidov, B., & Temi-rov, S. (2021). Studying the Effect of Light Incidence Angle on Photoelectric Parameters of Solar Cells by Simulation. International Journal of Renewable Energy Development, 10(4), 731-736. https://doi.org/10.14710/ijred.2021.36277
9. Гуломов, Д., Алиев, Р., Мирзаалимов, А., Абдувохидов, М., Мирзаалимов, Н., Каххоров, Ж., ... & Иззатиллаев, Х. (2021). Oddiy va nanozarracha kiritilgan kremniy asosli quyosh elementining fotoelektrik parametrlarini yorug'likning tushish bur-chagiga bog'liqligi. Общество и инновации, 2(1), 1222.
10. Aliev, R., Abduvohidov, M., & Gulomov, J. (2020). Simulation of temperatures influence to photoelectric properties of silicon solar cells. Physics & Astronomy International Journal, 4(5), 177-180.
11. Gulomov, J., Aliev, R., Abduvoxidov, M., Mirzaalimov, A., Mirzaalimov, N., & Rashidov, B. (2020). Mathematical model of a rotary 3D format photo electric energy device. World Journal of Advanced Research and Reviews, 8(2), 164-172.
