Prediction of Yellowing of Polystyrene Materials under Natural Weathering Exposures  

作　　者：Caixia Li Peixing Li Caixia Li;Peixing Li(School of Mathematic, Sun Yat-sen University, Guangzhou, China;Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou, China)

机构地区：[1]School of Mathematic, Sun Yat-sen University, Guangzhou, China [2]Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou, China

出　　处：《Applied Mathematics》2024年第12期834-839,共6页应用数学(英文)

摘　　要：The polystyrene (PS) materials tend to yellow over time. The yellowing phenomenon is an indicator of the material’s reduced performance and structural integrity. In the natural environment, sunlight is a major contributor to the yellowing, and elevated temperatures can accelerate the chemical reactions that lead to yellowing. The natural environmental factors are difficult to control, making it challenging to predict the yellowing process accurately. In this paper, we established a model to quantify the relationship between the yellowing index and key factors, solar radiation and temperature, from outdoor monitored climatic data. The model is trained and tested by the datasets collected from atmospheric exposure test stations located in Guangzhou and Qionghai. Same kinds of PS materials were exposed to external natural environments at the stations for one year. The parameters were estimated by least squares method. The results indicated that the model fits training and testing datasets well with R2 of 0.980 and 0.985, respectively.The polystyrene (PS) materials tend to yellow over time. The yellowing phenomenon is an indicator of the material’s reduced performance and structural integrity. In the natural environment, sunlight is a major contributor to the yellowing, and elevated temperatures can accelerate the chemical reactions that lead to yellowing. The natural environmental factors are difficult to control, making it challenging to predict the yellowing process accurately. In this paper, we established a model to quantify the relationship between the yellowing index and key factors, solar radiation and temperature, from outdoor monitored climatic data. The model is trained and tested by the datasets collected from atmospheric exposure test stations located in Guangzhou and Qionghai. Same kinds of PS materials were exposed to external natural environments at the stations for one year. The parameters were estimated by least squares method. The results indicated that the model fits training and testing datasets well with R2 of 0.980 and 0.985, respectively.

关 键 词：POLYSTYRENE Ageing YELLOWING Least Squares Method Arrhenius Equation Natural Weathering Exposures 

分 类 号：O63[理学—高分子化学]