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- Title
Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets.
- Authors
Valenzuela, Loreto M.; Knight, Doyle D.; Kohn, Joachim
- Abstract
Prediction of the dynamic properties of water uptake across polymer libraries can accelerate polymer selection for a specific application. We first built semiempirical models using Artificial Neural Networks and all water uptake data, as individual input. These models give very good correlations (R2>0.78 for test set) but very low accuracy on cross-validation sets (less than 19% of experimental points within experimental error). Instead, using consolidated parameters like equilibrium water uptake a good model is obtained (R2=0.78 for test set), with accurate predictions for 50% of tested polymers. The semiempirical model was applied to the 56-polymer library of L-tyrosine-derived polyarylates, identifying groups of polymers that are likely to satisfy design criteria for water uptake. This research demonstrates that a surrogate modeling effort can reduce the number of polymers that must be synthesized and characterized to identify an appropriate polymer that meets certain performance criteria.
- Subjects
BIODEGRADATION; POLYMERS; HYDRAULICS; MATHEMATICAL models; STATISTICAL correlation; ARTIFICIAL neural networks; TYROSINE
- Publication
International Journal of Biomaterials, 2016, p1
- ISSN
1687-8787
- Publication type
Article
- DOI
10.1155/2016/6273414