Abstract
The chalcogenide glass, GexSe1−x, has been widely used in advanced electronics and photonics. The onset temperature of glass transition, Tg, plays an important role in manufacturing processes and practical applications. To investigate the Tg, experimental methods to observe the glass transition step are commonly used, but the correlation between influencing factors and the Tg remains vague. In this study, we develop the multivariate linear regression (MLR) model to present the relationship between physical attributes and GexSe1−xTg. This simple model is highly accurate and contributes to rapid calculations of Tg. Compared with previous models that are more complicated in model construction and applications, the MLR model shows better performance and the direct statistical correlation between descriptors and the target variable.
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