Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164443
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dc.contributor.authorLeong, Chang Jieen_US
dc.contributor.authorLow, Andre Kai Yuanen_US
dc.contributor.authorRecatala-Gomez, Joseen_US
dc.contributor.authorVelasco, Pablo Quijanoen_US
dc.contributor.authorVissol-Gaudin, Eleonoreen_US
dc.contributor.authorTan, Jin Daen_US
dc.contributor.authorRamalingam, Balamuruganen_US
dc.contributor.authorMade, Riko Ien_US
dc.contributor.authorPethe, Shreyas Dineshen_US
dc.contributor.authorSebastian, Saumyaen_US
dc.contributor.authorLim, Yee-Funen_US
dc.contributor.authorKhoo, Jonathan Zi Huien_US
dc.contributor.authorBai, Yangen_US
dc.contributor.authorCheng, Jayce Jian Weien_US
dc.contributor.authorHippalgaonkar, Kedaren_US
dc.date.accessioned2023-01-25T08:00:10Z-
dc.date.available2023-01-25T08:00:10Z-
dc.date.issued2022-
dc.identifier.citationLeong, C. J., Low, A. K. Y., Recatala-Gomez, J., Velasco, P. Q., Vissol-Gaudin, E., Tan, J. D., Ramalingam, B., Made, R. I., Pethe, S. D., Sebastian, S., Lim, Y., Khoo, J. Z. H., Bai, Y., Cheng, J. J. W. & Hippalgaonkar, K. (2022). An object-oriented framework to enable workflow evolution across materials acceleration platforms. Matter, 5(10), 3124-3134. https://dx.doi.org/10.1016/j.matt.2022.08.017en_US
dc.identifier.issn2590-2385en_US
dc.identifier.urihttps://hdl.handle.net/10356/164443-
dc.description.abstractProgress in data-driven self-driving laboratories for solving materials grand challenges has accelerated with the advent of machine learning, robotics, and automation, but they are usually designed with specific materials and processes in mind. To develop the next generation of materials acceleration platforms (MAPs), we propose a unified framework to enable collaboration between MAPs, leveraging on object-oriented programming principles using research groups around theworldthatwouldbeabletoeffectively evolveexperimentalworkflows.Wedemonstratetheframeworkvia three experimental case studies from disparate fields to illustrate theevolutionof,andseamlessintegrationbetween,workflows,promoting efficient resource utilization and collaboration. Moving forward, we project our framework on three other research areas that would benefit from such an evolving workflow. Through the wide adoption of our framework, we envision a collaborative, connected, global community of MAPs working together to solve scientific grand challenges.en_US
dc.description.sponsorshipAgency for Science, Technology and Research (A*STAR)en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.language.isoenen_US
dc.relationA1898b0043en_US
dc.relationNRF-NRFF13-2021-0011en_US
dc.relation.ispartofMatteren_US
dc.rights© 2022 Elsevier Inc. All rights reserved. This paper was published in Matter and is made available with permission of Elsevier Inc.en_US
dc.subjectEngineering::Materialsen_US
dc.titleAn object-oriented framework to enable workflow evolution across materials acceleration platformsen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Materials Science and Engineeringen_US
dc.contributor.organizationInstitute of Materials Research and Engineering, A*STARen_US
dc.identifier.doi10.1016/j.matt.2022.08.017-
dc.description.versionSubmitted/Accepted versionen_US
dc.identifier.issue10en_US
dc.identifier.volume5en_US
dc.identifier.spage3124en_US
dc.identifier.epage3134en_US
dc.subject.keywordsMAP6: Developmenten_US
dc.subject.keywordsData Drivenen_US
dc.description.acknowledgementWe acknowledge funding from Accelerated Materials Development for Manufacturing Program A1898b0043 at A*STAR via the AME Programmatic Fund by the Agency for Science, Technology and Research. K.H. also acknowledges funding from the NRF Fellowship NRF-NRFF13-2021- 0011.en_US
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