Accelerated discovery of 3D printing materials using data-driven multiobjective optimization
<jats:p>Machine learning can aid the discovery of useful 3D printing material formulations.</jats:p>
| Main Authors: | , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2022
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| Online Access: | https://hdl.handle.net/1721.1/143789 |
| _version_ | 1826188909190578176 |
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| author | Erps, Timothy Foshey, Michael Luković, Mina Konaković Shou, Wan Goetzke, Hanns Hagen Dietsch, Herve Stoll, Klaus von Vacano, Bernhard Matusik, Wojciech |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Erps, Timothy Foshey, Michael Luković, Mina Konaković Shou, Wan Goetzke, Hanns Hagen Dietsch, Herve Stoll, Klaus von Vacano, Bernhard Matusik, Wojciech |
| author_sort | Erps, Timothy |
| collection | MIT |
| description | <jats:p>Machine learning can aid the discovery of useful 3D printing material formulations.</jats:p> |
| first_indexed | 2024-09-23T08:06:53Z |
| format | Article |
| id | mit-1721.1/143789 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T08:06:53Z |
| publishDate | 2022 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | dspace |
| spelling | mit-1721.1/1437892023-03-29T19:53:35Z Accelerated discovery of 3D printing materials using data-driven multiobjective optimization Erps, Timothy Foshey, Michael Luković, Mina Konaković Shou, Wan Goetzke, Hanns Hagen Dietsch, Herve Stoll, Klaus von Vacano, Bernhard Matusik, Wojciech Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science <jats:p>Machine learning can aid the discovery of useful 3D printing material formulations.</jats:p> 2022-07-18T12:42:05Z 2022-07-18T12:42:05Z 2021 2022-07-18T12:32:35Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/143789 Erps, Timothy, Foshey, Michael, Luković, Mina Konaković, Shou, Wan, Goetzke, Hanns Hagen et al. 2021. "Accelerated discovery of 3D printing materials using data-driven multiobjective optimization." Science Advances, 7 (42). en 10.1126/SCIADV.ABF7435 Science Advances Creative Commons Attribution NonCommercial License 4.0 https://creativecommons.org/licenses/by-nc/4.0/ application/pdf American Association for the Advancement of Science (AAAS) Science Advances |
| spellingShingle | Erps, Timothy Foshey, Michael Luković, Mina Konaković Shou, Wan Goetzke, Hanns Hagen Dietsch, Herve Stoll, Klaus von Vacano, Bernhard Matusik, Wojciech Accelerated discovery of 3D printing materials using data-driven multiobjective optimization |
| title | Accelerated discovery of 3D printing materials using data-driven multiobjective optimization |
| title_full | Accelerated discovery of 3D printing materials using data-driven multiobjective optimization |
| title_fullStr | Accelerated discovery of 3D printing materials using data-driven multiobjective optimization |
| title_full_unstemmed | Accelerated discovery of 3D printing materials using data-driven multiobjective optimization |
| title_short | Accelerated discovery of 3D printing materials using data-driven multiobjective optimization |
| title_sort | accelerated discovery of 3d printing materials using data driven multiobjective optimization |
| url | https://hdl.handle.net/1721.1/143789 |
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