Accelerated discovery of 3D printing materials using data-driven multiobjective optimization
Name
sciadv.abf7435.pdf
Description
Published version
Size
808.63 KB
Format
Adobe PDF
Checksum (MD5)
29f5e7ff662a5cd308d6789e7d0c0ead
Author(s)
Erps, Timothy
Foshey, Michael
Luković, Mina Konaković
Shou, Wan
Goetzke, Hanns Hagen
Dietsch, Herve
Stoll, Klaus
von Vacano, Bernhard
Matusik, Wojciech
Date Issued
2021
Journal
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Citation
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).
Version
Final published version
Abstract
Machine learning can aid the discovery of useful 3D printing material formulations.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1126/SCIADV.ABF7435
