Bioplastic design using multitask deep neural networks
Biodegradable polyhydroxyalkanoates are promising replacements for non-degradable plastics. Here, neural network property predictors are applied to a search space of approximately 1.4 million candidates, identifying 14 polyhydroxyalkanoates that could replace widely used petroleum-based plastics.
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-12-01
|
| Series: | Communications Materials |
| Online Access: | https://doi.org/10.1038/s43246-022-00319-2 |
| _version_ | 1811190240859127808 |
|---|---|
| author | Christopher Kuenneth Jessica Lalonde Babetta L. Marrone Carl N. Iverson Rampi Ramprasad Ghanshyam Pilania |
| author_facet | Christopher Kuenneth Jessica Lalonde Babetta L. Marrone Carl N. Iverson Rampi Ramprasad Ghanshyam Pilania |
| author_sort | Christopher Kuenneth |
| collection | DOAJ |
| description | Biodegradable polyhydroxyalkanoates are promising replacements for non-degradable plastics. Here, neural network property predictors are applied to a search space of approximately 1.4 million candidates, identifying 14 polyhydroxyalkanoates that could replace widely used petroleum-based plastics. |
| first_indexed | 2024-04-11T14:46:55Z |
| format | Article |
| id | doaj.art-3c9921783df34dd3ab1b366c1b850d84 |
| institution | Directory Open Access Journal |
| issn | 2662-4443 |
| language | English |
| last_indexed | 2024-04-11T14:46:55Z |
| publishDate | 2022-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Materials |
| spelling | doaj.art-3c9921783df34dd3ab1b366c1b850d842022-12-22T04:17:35ZengNature PortfolioCommunications Materials2662-44432022-12-013111010.1038/s43246-022-00319-2Bioplastic design using multitask deep neural networksChristopher Kuenneth0Jessica Lalonde1Babetta L. Marrone2Carl N. Iverson3Rampi Ramprasad4Ghanshyam Pilania5Materials Science and Technology Division, Los Alamos National LaboratoryBioscience Division, Los Alamos National LaboratoryBioscience Division, Los Alamos National LaboratoryChemistry Division, Los Alamos National LaboratorySchool of Materials Science and Engineering, Georgia Institute of TechnologyMaterials Science and Technology Division, Los Alamos National LaboratoryBiodegradable polyhydroxyalkanoates are promising replacements for non-degradable plastics. Here, neural network property predictors are applied to a search space of approximately 1.4 million candidates, identifying 14 polyhydroxyalkanoates that could replace widely used petroleum-based plastics.https://doi.org/10.1038/s43246-022-00319-2 |
| spellingShingle | Christopher Kuenneth Jessica Lalonde Babetta L. Marrone Carl N. Iverson Rampi Ramprasad Ghanshyam Pilania Bioplastic design using multitask deep neural networks Communications Materials |
| title | Bioplastic design using multitask deep neural networks |
| title_full | Bioplastic design using multitask deep neural networks |
| title_fullStr | Bioplastic design using multitask deep neural networks |
| title_full_unstemmed | Bioplastic design using multitask deep neural networks |
| title_short | Bioplastic design using multitask deep neural networks |
| title_sort | bioplastic design using multitask deep neural networks |
| url | https://doi.org/10.1038/s43246-022-00319-2 |
| work_keys_str_mv | AT christopherkuenneth bioplasticdesignusingmultitaskdeepneuralnetworks AT jessicalalonde bioplasticdesignusingmultitaskdeepneuralnetworks AT babettalmarrone bioplasticdesignusingmultitaskdeepneuralnetworks AT carlniverson bioplasticdesignusingmultitaskdeepneuralnetworks AT rampiramprasad bioplasticdesignusingmultitaskdeepneuralnetworks AT ghanshyampilania bioplasticdesignusingmultitaskdeepneuralnetworks |