Bias free multiobjective active learning for materials design and discovery
Identifying optimal materials in multiobjective optimization problems represents a challenge for new materials design approaches. Here the authors develop an active-learning algorithm to optimize the Pareto-optimal solutions successfully applied to the in silico polymer design for a dispersant-based...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-04-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-22437-0 |
| _version_ | 1818736761270960128 |
|---|---|
| author | Kevin Maik Jablonka Giriprasad Melpatti Jothiappan Shefang Wang Berend Smit Brian Yoo |
| author_facet | Kevin Maik Jablonka Giriprasad Melpatti Jothiappan Shefang Wang Berend Smit Brian Yoo |
| author_sort | Kevin Maik Jablonka |
| collection | DOAJ |
| description | Identifying optimal materials in multiobjective optimization problems represents a challenge for new materials design approaches. Here the authors develop an active-learning algorithm to optimize the Pareto-optimal solutions successfully applied to the in silico polymer design for a dispersant-based application. |
| first_indexed | 2024-12-18T00:42:17Z |
| format | Article |
| id | doaj.art-5e35ebe9396e4369baa0deb7485d7deb |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-18T00:42:17Z |
| publishDate | 2021-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-5e35ebe9396e4369baa0deb7485d7deb2022-12-21T21:26:52ZengNature PortfolioNature Communications2041-17232021-04-0112111010.1038/s41467-021-22437-0Bias free multiobjective active learning for materials design and discoveryKevin Maik Jablonka0Giriprasad Melpatti Jothiappan1Shefang Wang2Berend Smit3Brian Yoo4Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL)BASF CorporationBASF CorporationLaboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL)BASF CorporationIdentifying optimal materials in multiobjective optimization problems represents a challenge for new materials design approaches. Here the authors develop an active-learning algorithm to optimize the Pareto-optimal solutions successfully applied to the in silico polymer design for a dispersant-based application.https://doi.org/10.1038/s41467-021-22437-0 |
| spellingShingle | Kevin Maik Jablonka Giriprasad Melpatti Jothiappan Shefang Wang Berend Smit Brian Yoo Bias free multiobjective active learning for materials design and discovery Nature Communications |
| title | Bias free multiobjective active learning for materials design and discovery |
| title_full | Bias free multiobjective active learning for materials design and discovery |
| title_fullStr | Bias free multiobjective active learning for materials design and discovery |
| title_full_unstemmed | Bias free multiobjective active learning for materials design and discovery |
| title_short | Bias free multiobjective active learning for materials design and discovery |
| title_sort | bias free multiobjective active learning for materials design and discovery |
| url | https://doi.org/10.1038/s41467-021-22437-0 |
| work_keys_str_mv | AT kevinmaikjablonka biasfreemultiobjectiveactivelearningformaterialsdesignanddiscovery AT giriprasadmelpattijothiappan biasfreemultiobjectiveactivelearningformaterialsdesignanddiscovery AT shefangwang biasfreemultiobjectiveactivelearningformaterialsdesignanddiscovery AT berendsmit biasfreemultiobjectiveactivelearningformaterialsdesignanddiscovery AT brianyoo biasfreemultiobjectiveactivelearningformaterialsdesignanddiscovery |