THE EFFECT OF TEMPERATURE ON THE CHARACTERISTICS OF A p-n JUNCTION DIODE WITH DIFFERENT DOPING CONCENTRATIONS

ABSTRACT

Today, silicon-based devices are widely used in almost all industries. Because silicon is sensitive to the environment, that is, to temperature, the development of temperature-resistant diodes is an important task. Therefore, in this paper, the effect of temperature on the characteristics of silicon-based p-n junction diodes with different input concentrations was studied by modeling. It was found that the temperature dependence of the characteristics of the diode with the input concentration in the n field 1e17 cm^-3 and the input concentration in the p field 1e16 cm^-3 is good.

АННОТАЦИЯ

Сегодня устройства на основе кремния широко используются практически во всех отраслях промышленности. Поскольку кремний чувствителен к окружающей среде, то есть к температуре, разработка термостойких диодов является важной задачей. Поэтому в данной работе методом моделирования исследовано влияние температуры на характеристики диодов с p-n переходом на основе кремния с различной концентрацией на входе. Установлено, что температурная зависимость характеристик диода при входной концентрации в n-поле 1e17 см^-3 и входной концентрации в p-поле 1e16 см^-3 является хорошей.

Keywords: diode, silicon, p-n, modeling, introduction.

Ключевые слова: диод, кремний, p-n, моделирование, внедрение.

INTRODUCTION

Most semiconductor devices are made of homogeneous semiconductors (different current carriers). In the special case, a homogeneous semiconductor consists of one p-type sphere and another n-type single crystal [1].

A volumetric charge layer is formed at the separation boundary of the p and n - domains of such a homogeneous semiconductor, an internal electric field is formed at the boundary of these domains, and this layer is called the electron-cavity transition or p-n junction [2]. The principle of operation of many semiconductor devices and integrated circuits is based on p-n junction properties.

Let's look at the mechanism of the formation of the electron-cavity transition. For simplicity, we get the number of electrons in the n-field and the number of holes in the p-field. In addition, each field has a small amount of non-core charge carriers [3]. At room temperature, the concentration of acceptor negative ions in the p-type semiconductor is n-p, the concentration of donor positive ions in the n-type semiconductor is n, and the concentration of Nd electrons is n [4]. Therefore, due to the significant difference in the concentration of electrons and cavities between the p- and n-domains, when these domains combine, the diffusion of electrons into the p-domain and the cavities into the n-domain begins.

As a result of diffusion, the concentration of electrons at the boundary of the n-field is less than the concentration of positive donor ions, and the field begins to charge positively. At the same time, the concentration of pores at the boundary of the p-domain decreases, and it begins to be negatively charged due to ionic charges compensated by the acceptor input. Circles with positive and negative signs represent donor and acceptor ions, respectively.

The two volumetric charge layers formed are called p-n junctions. This layer is depleted by mobile charge carriers. Therefore, its specific resistance is much higher than the p- and n-field resistances. In some literatures, this layer is called the impoverished or n-field.

Volumetric charges have different signals and form an electric field of voltage E at the p-n junction. For the main charge carriers, this field acts as a brake and prevents them from moving freely along the p-n junction.

MATERIALS AND METHODS

The purpose of modeling is to solve the following practical problems:

1) systematic analysis of the interaction between complex object variables;

2) structural and indicative identification of the object;

3) long-term forecasting of processes qualitatively (incompletely) or quantitatively (comprehensively);

4) decision making and planning.

Systematic analysis of the interaction of variables is performed before the work of identifying the object. This not only allows you to find a set of characteristic variables, but also to divide them into output quantities and influencing factors.

Output quantities are given in the identification, which requires finding the structure of all elements and evaluating the indicators. As a result of identification, the laws of the object under investigation are revealed. In the identification of less accurate data, it is possible to identify 9 ways of affecting the object and solve the problem of short-term prediction.

Only short-term predictions can be made through human intuition. This explains why people can predict the weather without any differential equations.

Accurate quantitative forecasting of inaccurate data is solved using special, self-guided modeling methods.

TCAD software was widely used in the modeling of semiconductor devices [5]. In this paper, the effect of temperature on the volt-ampere characteristic of a diode was studied using the Silvaco TCAD program.

The geometric model of the diode was created and tested in the Atlas module itself. Also, the volt-ampere characteristics of the diode at different temperatures were obtained by repeatedly re-instructing the Atlas module.

RESULTS AND DISCUSSION

The dimensions of the p- and n-bands in the diode are the same 1 μm. The input concentration was changed from 1e17 to 1e18 in the n field and from
1e16 cm^-3 to 1e18 cm^-3 in the p field. Figure 1 shows the effect of temperature on the anode current of a silicon-based p-n junction diode with different input concentrations.

Figure 1. Temperature dependence of the anode current of a p-n junction silicon diode with different doping concentrations

The temperature dependence of the anode current is improved when the input concentration is 1e17 cm^-3 in the n field and 1e16 cm^-3 in the p field. The worst results were observed when the input concentration was 1e18 cm^-3 in n and
1e18 cm^-3 in p. Since the current in the graph is on a logarithmic scale, the temperature dependence of the current is exponential. The result obtained by this numerical method was also consistent with the analytical formula of the diode. That is, the result proved to be theoretically correct.

The effect of temperature on semiconductor devices is mainly analyzed by the change in temperature of the kinetic characteristics of the charge carriers. Figure 2 shows the temperature dependence of the motion of the electrons, which are the main charge carriers of type 2N. It was found that the mobility of electrons decreases as the input concentration and temperature increase. This is because the amount of phonons increases as the temperature rises. As the concentration of phonons increases, the probability of phono-electron scattering also increases.

Figure 2. Temperature dependence of the mobility of electrons in silicon with different doping concentrations

In silicon, the motions of electrons and cavities differ, and the effect of temperature on them also varies. Therefore, Figure 3 shows the temperature dependence of the mobility of cavities, which are the main charge carriers in p-type silicon at different concentrations.

Figure 3. Temperature dependence of the mobility of pits in silicon with different input concentrations

CONCLUSION

There is an increase and decrease in the motion of the electrons at a temperature of 250 k, but the temperature in the cavities decreases functionally. As in electrons, the mobility of cavities decreases with increasing input concentration. This is because the input atom becomes an ion after losing an electron or capturing an additional electron. The ion can be positive or negative. Depending on the sign of the ion, it is possible to distinguish between the electron or the cell holding ion. As the temperature increases, the anode current increases as the mobility of the charge carriers decreases. This is due to the thermo generation of the charge carriers.

References:

1. Gulomov, J., Aliev, R. Study of the Temperature Coefficient of the Main Photoelectric Parameters of Silicon Solar Cells with Various Nanoparticles (2021). Journal Nano- and Electronic Physics, 13(4), 04033-1 - 04033-5.
2. Gulomov J. and Aliev R., “Analyzing periodical textured silicon solar cells by the TCAD modeling,” Scientific and Technical Journal of Information Technologies, Mechanics and Optics, vol. 21, no. 5, pp. 626–632, Oct. 2021, doi: 10.17586/2226-1494-2021-21-5-626-632.
3. Gulomov, J., & Aliev, R. (2021c). Numerical analysis of the effect of illumination intensity on photoelectric parameters of the silicon solar cell with various metal nanoparticles. Nanosystems: Physics, Chemistry, Mathematics, 12(5), 569–574. https://doi.org/10.17586/2220-8054-2021-12-5-569-574.
4. Gulomov, J., & Aliev, R. (2021d). The Way of the Increasing Two Times the Efficiency of Silicon Solar Cell. Physics and Chemistry of Solid State, 22(4), 756–760. https://doi.org/10.15330/PCSS.22.4.756-760.
5. Gulomov, J., & Aliev, R. (2021a). Influence of the Angle of Incident Light on the Performance of Textured Silicon Solar Cells. Journal of Nano- and Electronic Physics, 13(6), 06036-1-06036–5. https://doi.org/10.21272/JNEP.13(6).06036.