Научная статья на тему 'EXPLORING SOLAR CELLS BY PROGRAMMING LANGUAGES AND SSTANDART PROGRAMS'

EXPLORING SOLAR CELLS BY PROGRAMMING LANGUAGES AND SSTANDART PROGRAMS Текст научной статьи по специальности «Электротехника, электронная техника, информационные технологии»

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Ключевые слова
TCAD / solar cell / model / program

Аннотация научной статьи по электротехнике, электронной технике, информационным технологиям, автор научной работы — Khudoynazarov A.

In this article provides information about digital modeling programs and programming languages, besides models and programs which are created based on them.

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Текст научной работы на тему «EXPLORING SOLAR CELLS BY PROGRAMMING LANGUAGES AND SSTANDART PROGRAMS»

The values of the local efficiency for the mixture methanol - water without defoamer increased with the increase of M-index and a linear dependence was observed between the change of the local efficiency and the M-index. In presence of defoamer, however, the increase of the M-index caused decrease of the local efficiency from 87,3% to 84,65%, i.e. it can be assumed that when defoamer is added then the surface tension does not exert significant effect on the degree of separation.

References

1. Foams: Theory, Measurements and Applications, eds. R.K. Prud'homme and S.A. Khan, Surfactant Science Series, Vol. 57, Marcel Dekker, New York, 1996.

2. Defoaming: Theory and Industrial Applications, Vol. 45, ed. P.R. Garrett, Surfactant Science Series, Marcel Dekker, New York, 1993.

3. D.T. Wasan, K. Koczo and A.D. Nikolov, in Foams: Fundamentals and Applications in Petroleum Industry, ed. L.L. Schramm, ACS Symposium Series No. 242, ACS, New York, 1994, Chapter 2.

4. Zuiderweg, F.J., A. Harmens. The influence of surface phenomena on the performance of distillation columns, Chem Eng Sci, 1958, V.9, (2/3), pp.89-103; 1967, V.22, pp.685-692.

5. Ivanov J., J. Stefanov and J. Tasev, Year at the University "Prof. Dr. As. Zlatarov", Burgas, 2006, XXXV, book 1, p. 43 ( Иванов Ж., Ж. Стефанов и Ж. Тасев, Год на У-т "Проф.д-р Ас.Златаров", Бургас, 2006, XXXV, кн. 1, с. 43)

6. N.D. Denkov, K.G. Marinova, Antifoam effects of solid particles, oil drops and oil-solid compounds in aqueous foams. Chapter 10 in the book "Colloidal Particles at Liquid Interfaces" (B.P. Binks & T.S. Horozov, Eds.), Cambridge University Press, Cambridge, UK, 2006; pp. 383-444.

7. Kafarov V.V. Basics of Mass Transfer. Higher school, Moscow, 1972, p. 227. (Кафаров В.В. Основы массопередачи. Высшая школа, Москва, 1972, с. 227.)

8. Zuiderweg F. J., Marangoni effect in distillation of alcohol-water mixtures, Chem. Eng. Res. Des., Vol. 61, 388 (1983).

EXPLORING SOLAR CELLS BY PROGRAMMING LANGUAGES AND SSTANDART PROGRAMS

Khudoynazarov A.

Master student of renewable energy sources Andijan state university

Abstract

In this article provides information about digital modeling programs and programming languages, besides models and programs which are created based on them. Keywords: TCAD, solar cell, model, program

Until the twentieth century, there were two different methods of studying the object in science, theoretical and practical methods. In the middle of the twentieth century, computer technology flourished. This led

to a new approach to science and a new style of research. In the process of complex computing, it is preferable to use computer technology. Because it increases the speed and accuracy of the calculation.

Figure 1. 2D model of a silicon-based solar cell embedded in a nanoparticle generated in Sentaurus TCAD.

Computer modeling is a combination of theory and practice. There are many modeling programs. These include Synopsys's Sentaurus TCAD (Technology Computing Aided Design) and Silvaco Atlas TCAD, which are widely used in modeling semiconductor devices. In these modeling programs, TCL (Tool Command Language) is used to create the model [4]. This requires programming skills from the user. The advantage of this software package is the ability to create models in 3D and 2D. If we want to model a semiconductor device in 2D, we need to pay attention to the symmetry of the device. Suppose we want to create a model of a simple p-n transition solar cell [5]. In order to do this, we need to have knowledge about the process of making the solar cell, its structure, and the physical processes that take place inside it. But the results obtained in these modeling programs are very close to the results obtained in the experiment. That is, the error rate

is very low. Together with the staff of the Renewable Energy Sources Scientific Laboratory, we experimentally measured the photoelectric parameters of the solar cell and created a model of this solar cell using the Sentaurus TCAD [6]. The results obtained proved that the accuracy of the modeling program was in fact high. In addition, scientists around the world also acknowledge that the results obtained at the Sentaurus TCAD are close to reality. So far, we have modeled the construction of many solar cells using the Sentaurus TCAD [7]. A clear example of this is the model of a solar cell embedded in a nanoparticle (Figure 1) [1]. There are also purpose-built modeling programs. For example, the PVLighthouse online program is designed to model solar cells only. We use PVLighthouse's Wafer Ray Tracer module to determine the optical properties of textured and optically coated solar cells (Figure 2) [8].

Figure 2. Working window of Wafer Ray Tracer model inside PVlighthouse

We can model a whole system, not just one solar element. In this case, we mainly need knowledge of 3D graphics. That is, we need to create a 3D or 2D view of the system we want to model. One of the most widely used programs in engineering is Comsol Multiphysics. The reason this program is evolving is that it does not require knowledge of programming in use. We just need to create a 3D geometric model and the physical processes that take place in it. In our research, we used this program to model the flexo-photovoltaic effect on silicon-based solar cells. The ability to model semiconductor devices was created by adding the Semiconductors library in version 5.5 of Comsol Multiphysics, released on November 14, 2019.

We use programming languages to translate the sequence of actions we are thinking of into machine language. There are many programming languages. It makes sense to choose a programming language based

on the program we are creating. Today, programming languages have developed to such an extent that they are widely used in all fields. To study solar elements, we use C #, Python, and Visual Basic programming languages. These include Suntulip-AGAUz [3] for determining the optical properties of solar cells using the C # programming language, STGRAPH for processing the results obtained in the PVlighthouse, STTempera-ture for determining the effect of temperature on the kinetic characteristics of silicon-based solar cells, and a new We have developed STVertical [2] programs that determine the effect of geometric dimensions on the photoelectric and thermal properties of a 3D photoelectric power device. From the C # programming language, we develop programs for the Windows operating system with high graphics and fast calculations. For the first time, we created a new library for the C # programming language to make it easier to calculate the optical properties of solar elements. Another feature of

the C # programming language is that in Unity we can write a script so that the object obeys the laws of physics. Because Visual Basic is a syntax and functional language, we use it to perform simple calculations.

Python programming language has emerged as the highest level programming language to date. This is because it has open source and soda syntax. Python programming language is widely used in all fields. That's because it has so many libraries. There are PVlib and Solcore libraries for studying solar panels and modeling semiconductor solar cells. Fluctuations occur when we plot a graph of experimental results. Nonlinear regression is used in mathematical statistics to eliminate it and create a clear graph. One of the fastest growing areas of programming is Machine Learning. We use the Machine Learning algorithm in the Python programming language to determine the optimal values obtained in experiments.

In conclusion, the use of a software package for modeling in the study of semiconductor devices increases productivity and accuracy.

References

1. 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

2. 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

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. 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

5. 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

6. 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.

7. 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.

8. 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.

MANUFACTURE OF FLAT CELLULOSE ACETATE MEMBRANES

Movchaniuk O.M.

PhD in Technical science Igor Sikorsky Kyiv Polytechnic Institute, PeremohyAv., 37, Kyiv, 03056, Ukraine

ВИГОТОВЛЕННЯ ПЛОСКИХ АЦЕТАТЦЕЛЮЛОЗНИХ МЕМБРАН

Мовчанюк О.М.

кандидат технгчних наук КП1 iM. 1горя Сгкорського, пр-т Перемоги, 37, м. Кшв, 03056, Украна

Abstract

The article considers the fabrication of flat cellulose acetate membranes by the phase inversion method. The scheme of complex production of flat cellulose acetate membranes for reverse osmosis, ultrafiltration and microfiltration is presented. The composition of the molding solution, possible solvents of cellulose acetate, technological processes of production are considered.

Анотащя

В статп розглянуто виготовлення плоских ацетатцелюлозних мембран методом шверсп фаз. Представлено схему комплексного виробництва плоских ацетатцелюлозних мембран для зворотного осмосу, уль-траф№трацп i мжрофшьтрацп. Розглянуто склад формувального розчину, можливi розчинники ацетату целюлози, технолопчш процеси виробництва.

Keywords: cellulose acetate, solvents, molding solution, membranes.

Ключовi слова: ацетат целюлози, розчинники, формувальний розчин, мембрани.

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