Loading…

Prediction of Defect Formation Process in Lithium Fluoride Using Nonlinear Regression Analysis

In this paper, we proposed to use nonlinear regression analysis to study the regularities of defect formation in LiF. At different stages of exposure, the development of defects, colloids and voids on the surface of the lithium fluoride nanocrystals was investigated by method total current spectrosc...

Full description

Saved in:
Bibliographic Details
Main Authors: Kakhramonov, Alisher, Karimov, Mukhtorjon K., Kurbanov, Muzaffar.K., Saidov, Dilmurod Sh, Nazarova, Nargiza M., Halimov, Akbar S.
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we proposed to use nonlinear regression analysis to study the regularities of defect formation in LiF. At different stages of exposure, the development of defects, colloids and voids on the surface of the lithium fluoride nanocrystals was investigated by method total current spectroscopy. Electronic interaction with a lithium fluoride film of during the thermal annealing process that followed the formation of the vacancies, colloids, voids and defects that had been created by electron (e) irradiation were also subjected to thermal treatment. Based on the analysis of experimental research, it was shown that the formation of defects in lithium fluoride depends on temperature, irradiation, and impurity concentration. The physical regularity of the process of aggregation and desorption was determined, and a mathematical model of the temperature dependence of the concentration (voids intensity) of the V-center peak was obtained by the method of nonlinear regression analysis. The obtained regression model predicts the change in concentration depending on the temperature of the V-center peak at negative temperatures. The results obtained can be used to develop new methods for controlling defects in LiF and improving its properties.
ISSN:2473-8573
DOI:10.1109/APEIE59731.2023.10347657