MODELING THE PHOTOELECTRIC PARAMETERS OF THIN SILICON-BASED SOLAR CELLS

USING THE SENTAURUS TCAD

Komilov M.

Master student, Andijan State University

Abstract

The Sentaurus TCAD software package is widely used in the modeling of semiconductor devices. This article presents the stages of modeling silicon-based solar cells and the results obtained based on the modeling. In this case, the I-V characteristics of a thin silicon-based solar cell were determined. It has a short-circuit current density of 26 mA/cm2 and an operating voltage of 0.46 V. It was found that the thickness of the base of the solar cell has a significant effect not only on the current density but also on the voltage.

Keywords: solar cell, modeling, Sentaurus TCAD, I-V characteristics

I INTRODUCTION

Extensive work is being done to increase the share of renewable energy sources in the energy produced. There are many types of renewable energy sources. One of them is solar energy. Solar energy can be used to generate heat and electricity for two different purposes. Solar elements are mainly used to convert solar energy into electricity [1]. There are many types of solar cells. The most widely used of these are silicon-based solar cells. Because silicon is the most common semiconductor on earth. In this scientific work, monocrystalline and polycrystalline silicon-based solar elements have been studied.

The methodology of scientific research is divided into 3. These are through theoretical, experimental, and modeling [3]. Modeling style has emerged in recent history and is one of the new modern styles. Modeling is a combination of theory and practice [4].

Solar cell modeling uses software such as the Sentaurus TCAD, Silvaco TCAD, and Crosslight TCAD. Comsol Multiphysics software is widely used to model the system in conjunction with the device and the environment. In this research, Synopsys's Sentaurus TCAD software package was used to study the photoelectric parameters of silicon-based solar cells [5].

The Sentaurus TCAD software package consists of 21 tools, of which 17 are basic and 4 are additional tools. Each instrument is designed to work independently and together in an environment. There are 4 main instruments used in the modeling of solar cells. These are the Sentaurus Structure Editor (SDE), the Sentaurus Device (SDevice), the Sentaurus Visual (SVisual), and the Sentaurus Workbench (SWB).

SDE is the only module of Sentaurus Structure Editor. Based on SDE, geometric models of semiconductor devices are made. In addition, the material type, contacts, input concentration, input atom type of each field are given, and a geometric model is compiled for calculation in numerical methods. In SDE, geometric models can be created in two different styles. The first is by using standard forms in the standard SDE module interface, and the second is by writing code in the SDE's specific intrumental language. Creating complex structures by writing code is convenient and effective. Because the instrumental language of SDE has many features in programming languages. That is, there

are cycles, conditions, functions, arithmetic operations, and so on.

The SDevice is used to determine the electrical, optical, thermal, and similar properties and parameters of the device being modeled using numerical methods, giving physical properties to the geometric model generated in the SDE. The SDevice is divided into 6 parts. These are Files, Electrods (Thermods), Physics, Math, Current Plot and Solve. The file contains all the incoming files, i.e. the geometric model and its test file, material properties files, light spectrum, and additional similar files by giving their names and locations. The electrode (Thermod) contains the properties of the contacts, such as resistance, output, type, and the amount of current and voltage applied to the contacts. If there is a thermode, the temperature and heat fluxes of each thermode are given. The Physics section provides the required physical models. There are also a number of features, such as the temperature of the device. When choosing a physical model, care must be taken with the device being modeled and its material type. Because different physical models represent the same phenomenon for different materials. The Math section mainly manages errors, computational limits, computational methods, and some parameters. Based on the output files in the Solve section and the physical models given in the physics section, the Poisson and Continuity equations for electrons and cavities are solved based on the calculation methods given in the Math section. It is also possible to study the dependence of the properties of the solar cell on each barometer.

SDViced results in SVisual are displayed graphically and visually and can be exported. It is also possible to process the results obtained in it.

The 3 instruments mentioned above can work independently. But for them to work together, they need to be integrated into a single environment. This environment is performed by SWB. SWB increases tool performance and efficiency. That is, different results can be obtained by giving values to the variables generated in each instrument via SWB.

One of the most important tasks in the design of high-efficiency solar cells is the study of the properties and photoelectric parameters of silicon-based solar cells.

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 Geometrical method

The geometric model of solar elements is made in SDE. The coding method was used. The solar element is made up of 4 layers. From top to bottom, the SiO:

optical layer, the contact area n the area, and the area p. Figure 1 shows a geometric model of a solar cell made of SDE. 1e15 cm-3 of boron atoms were added to silicon to form p type. to form type n, 1e17 cm-3 of phosphorus atoms were introduced. When creating nets, the contact points are made smaller and the other areas are larger. In addition, the anode and cathode were formed and activated.

Picture 1. A reticulated form of a thin silicon-based solar cell formed in SDE

2.2 Theory

When modeling semiconductor devices, at least the Poisson equation must be solved (Formula 1). To do this, the charge carriers must be in equilibrium [6]. To solve the Poisson equation, the concentration of primary and non-basic charge carriers must be known. The concentration of charge carriers is determined by Bolts-man or Fermi distributions [7]. The solution of the Poisson equation gives the electric field strength and potential generated in semiconductors. In equilibrium devices with p-n junction, the equilibrium state is defined as the state in which the potential difference is zero.

Acp = — — (p — n + Nd + Na)

(1)

e - dielectric permittivity n and p - electron and hole concentration ND and NA - donor and acceptor impurities concentration

q - electron charge

If light is incident on a solar cell, it will generate electrons and cavities. This causes a potential difference in the solar cell. This means that the charge carriers will move. Continuity equation is used to calculate the charge transfer (Formula 2). The solution of the equation of continuity takes into account changes in the

concentration of charge carriers, generation rates[8-13].

recombination and

V 7„ = q(R„ -Gn) + q

--vTp = q(Rp-Gp) + qft

dn

dt

dp

(2)

Where: Rn va Rp electron and holes recombination ratio.

Gn and Gp ratio of electron and holes generation Jn - current density of electrons Jp - current density of holes n va p - electron and hole concentration q - electron charge III RESULTS AND DISCUSSION A single-crystal silicon-based solar cell was modeled and the I-V characteristic was determined (Picture 2). Through these I-V characteristics, the photoelectric parameters of a solar cell can be determined. The rated operating voltage was 0.46 V and the short-circuit current was 26 mA/cm2. The short-circuit current is smaller than the photogeneration current due to the fact that the concentration of charge carriers in monocrys-talline silicon increases with the concentration of light and recombines until the charge carriers reach the contact.

I-V characterics

0 0.2 0.4

Voltage

Picture 2. I-V characteristics of a single crystal silicon-based solar cell

Graph

0.4 0.6 0.8

Wavelength

Picture 3. AM1.5D light source spectrum AM1.5D light spectrum was captured as a light source for the solar cell (Figure 3). Figure 3 shows the AM1.5D light spectrum, i.e. the intensity dependence of the light wavelength.

Graph

Wavelength

Picture 4. Dependence of the optical parameters of a single-crystal silicon-based solar cell on the wavelength. R

- return, A - absorption, T - transition.

The biggest problem with thin solar cells is that the absorption coefficient drops. We know that silicon mainly absorbs light in the visible field. Therefore, the absorption coefficient of the silicon-based solar cell shown in Figure 4 is low in relation to the wavelength. The conversion rate is high. This means that most of the light passes through without being absorbed.

IV CONCLUSION

In short, thin silicon-based solar elements need to form textures on the surface and bottom to increase the absorption coefficient. Or you need to add particles. Then the cost of the solar cell will be cheaper and better. It is also expedient to make extensive use of the modeling method in conducting scientific research. Because modeling also saves time and money.

REFERENCES:

1. Hirst, L. C., & Ekins-Daukes, N. J. (2010). Fundamental losses in solar cells. Progress in Photovol-taics: Research and Applications, 19(3), 286-293. https://doi.org/10.1002/pip. 1024

2. 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

3. 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 .

4. Burgelman M, Nollet P, Degrave S. Modelling polycrystalline semiconductor solar cells. Thin Solid Films 2000; 361-362: 527-532.

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. 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

7. 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

8. 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

9. 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

10. 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

11. 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.

12. 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.

13. 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.