Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets
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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
|
| Series: | International Journal of Biomaterials |
| Online Access: | http://dx.doi.org/10.1155/2016/6273414 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832565377321664512 |
|---|---|
| author | Loreto M. Valenzuela Doyle D. Knight Joachim Kohn |
| author_facet | Loreto M. Valenzuela Doyle D. Knight Joachim Kohn |
| author_sort | Loreto M. Valenzuela |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-460c0f54796c40bdaa441bf10c3fbe06 |
| institution | Kabale University |
| issn | 1687-8787 1687-8795 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomaterials |
| spelling | doaj-art-460c0f54796c40bdaa441bf10c3fbe062025-02-03T01:08:00ZengWileyInternational Journal of Biomaterials1687-87871687-87952016-01-01201610.1155/2016/62734146273414Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training SetsLoreto M. Valenzuela0Doyle D. Knight1Joachim Kohn2Department of Chemical and Bioprocess Engineering, Research Center for Nanotechnology and Advanced Materials “CIEN-UC”, Pontificia Universidad Católica de Chile, Vicuña Mackenna 2860, Macul, 7820436 Santiago, ChileDepartment of Mechanical and Aerospace Engineering, Rutgers, The State University of New Jersey, New Brunswick, NJ 08854-8087, USANew Jersey Center for Biomaterials, Rutgers, The State University of New Jersey, 145 Bevier Road, Piscataway, NJ 08854, USAPrediction 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.http://dx.doi.org/10.1155/2016/6273414 |
| spellingShingle | Loreto M. Valenzuela Doyle D. Knight Joachim Kohn Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets International Journal of Biomaterials |
| title | Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets |
| title_full | Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets |
| title_fullStr | Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets |
| title_full_unstemmed | Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets |
| title_short | Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets |
| title_sort | developing a suitable model for water uptake for biodegradable polymers using small training sets |
| url | http://dx.doi.org/10.1155/2016/6273414 |
| work_keys_str_mv | AT loretomvalenzuela developingasuitablemodelforwateruptakeforbiodegradablepolymersusingsmalltrainingsets AT doyledknight developingasuitablemodelforwateruptakeforbiodegradablepolymersusingsmalltrainingsets AT joachimkohn developingasuitablemodelforwateruptakeforbiodegradablepolymersusingsmalltrainingsets |