Вклад распределенного эффекта Пельтье в эффективность ветви термоэлектрического охладителя

An attempt is made to calculate the contribution of the distributed Peltier effect to the efficiency of the branch of the thermoelement Z for various types of impurity distribution. For this purpose, the boundary problem of thermal balance in the branch of the thermoelectric element was solved numerically, taking into account the distributed Peltier effect. The case of non-degenerate charge carriers was considered within the framework of the standard two-band model. The parameters of charge carriers were selected close to thermoelectrics based on bismuth and antimony tellurides. As the calculation in the framework of the two-zone model showed, the use of the distributed Peltier effect leads only to partial absorption of Joule heat, which contributes to an increase in the overall efficiency of the branch. In this case, the Z parameter along a significant part of the branch takes values significantly less than the maximum value

Investigation of features for prediction modeling of nano-scale conduction with time-dependent calculation of electron wave packet

The model to predict the electron transmission probability from the random impurity distribution in a two-dimensional nanowire system by combining the time evolution of the electron wave function and machine learning is proposed. We have shown that the intermediate state of the time evolution calculation is a great advantage for efficient modeling by machine learning. The features for machine learning are extracted by analyzing the time variation of the electron density distribution using time evolution calculations. Consequently, the prediction error of the model is improved by performing machine learning based on the features. The proposed method provides a useful perspective for analyzing the motion of electrons in nanoscale semiconductors.

Ratio of structural impurity distribution in diamond crystals and kimberlite pipe diamond potentiak (case study of Arkhangelsk region and Yakutia)

IR spectroscopy was used to compare diamonds from 12 pipes, Arkhangelsk region. Based on positive correlation between average N and H values in diamonds from various deposits, it was found that crystals from low-grade diamond pipes are relatively enriched in hydrogen compared with diamonds from Lomonosov and Grib deposits. In terms of structural impurity distribution, Arkhangelsk deposit diamonds differ from Yakutian diamonds; it could be due to various composition of compared diamonds’ source matter and thermodynamic conditions of their growth. It is shown that hydrogen is a negative factor of diamond potential in both Yakutian and Arkhangelsk diamonds. This can partly be explained by impuri-ty blocking effect on diamond crystal growth.

MATHEMATICAL EQUATION FOR IMPURITY DISTRIBUTION AFTER SECOND PASS OF ZONE REFINING

A mathematical equation has been derived that describes impurity distribution in ingot after second pass of zone refining. While an exponential impurity distribution is calculated by a simplified model after first pass, second pass is described by mixed linear - exponential model. Relationship of transformed impurity concentration is constant over whole length of semi-infinite ingot for first pass. However, it has linear trend for second pass. Last part of molten zone at infinity solidifies differently and can be described mathematically as directional crystallization. A mathematical tool devised for second pass of zone refining can be tried to be used for derivation of functions of more complex models that would describe impurity distribution in more realistic way compared to simplified approach. Such models could include non-constant distribution coefficient and/or shrinking or widening molten zone over a length of ingot.

The Distribution Trend of Boron Atoms in Semiconductor Silicon under High Temperature

The ProENGINEER software is used to build a geometric model for the whole process cavity and internal structure and conduct the internal dynamic simulation of cavity with different diffusion temperatures of 1,000°C, 1,050°C, 1,100°C and 1,150°C, and different diffusion time of 5 min, 10 min, 15 min and 20 min. Analyze the process control indexes by combining with specific thermal diffusion test, and study the relationship between hydrodynamic parameters and diffusion uniformity, Comprehensively investigate the effects of the diffusion temperature and diffusion time on doping, achieving the requirements of impurity distribution in materials.