Artificial neural network prediction of glass transition temperature of polymers
โ Scribed by Wanqiang Liu; Chenzhong Cao
- Publisher
- Springer
- Year
- 2009
- Weight
- 181 KB
- Volume
- 287
- Category
- Article
- ISSN
- 0340-255X
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Polymeric materials are finding increasing application in commercial optical communication systems. Taking advantage of techniques from the field of artificial intelligence, the goal of our research is to construct systems that can computationally design polymer formulations, including polymer optic
The classical free volume theory is modified semi-empirically to derive an expression useful for predicting the glass transition temperatures (T~) for compatible polymer blends. This equation produccs values of T~ in better agreement than those from the Kelley-Bueche equation with the dilatomctric d