Rapid Bayesian optimisation for synthesis of short polymer fiber materials Li, Cheng, Rubín de Celis Leal, David, Rana, Santu, Gupta, Sunil, Sutti, Alessandra, Greenhill, Stewart, Slezak, Teo, Height, Murray and Venkatesh, Svetha 2017, Rapid Bayesian optimisation for synthesis of short polymer fiber materials, Scientific reports, vol. 7, pp. 1-10, doi: 10.1038/s41598-017-05723-0. Attached Files Name Description MIMEType Size Downloads li-rapidbayesian-2017.pdf Published version application/pdf 2.84MB 108 Title Rapid Bayesian optimisation for synthesis of short polymer fiber materials Author(s) Li, Cheng Rubín de Celis Leal, David Rana, Santu orcid.org/0000-0003-2247-850X Gupta, Sunil orcid.org/0000-0002-3308-1930 Sutti, Alessandra orcid.org/0000-0002-1793-3881 Greenhill, Stewart orcid.org/0000-0002-7585-9632 Slezak, Teo Height, Murray Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Journal name Scientific reports Volume number 7 Article ID 5683 Start page 1 End page 10 Total pages 10 Publisher Nature Publishing Group Place of publication London, Eng. Publication date 2017-07-18 ISSN 2045-2322 Keyword(s) Science & Technology Multidisciplinary Sciences Science & Technology - Other Topics Summary The discovery of processes for the synthesis of new materials involves many decisions about process design, operation, and material properties. Experimentation is crucial but as complexity increases, exploration of variables can become impractical using traditional combinatorial approaches. We describe an iterative method which uses machine learning to optimise process development, incorporating multiple qualitative and quantitative objectives. We demonstrate the method with a novel fluid processing platform for synthesis of short polymer fibers, and show how the synthesis process can be efficiently directed to achieve material and process objectives. Language eng DOI 10.1038/s41598-017-05723-0 HERDC Research category C1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2017, The Authors Free to Read? Yes Use Rights Persistent URL http://hdl.handle.net/10536/DRO/DU:30098043 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment Institute for Frontier Materials Centre for Pattern Recognition and Data Analytics (PRADA) Open Access Collection GTP Research Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Wed, 19 Jul 2017, 10:15:57 EST Thu, 20 Jul 2017, 05:00:25 EST Sat, 05 Aug 2017, 02:31:29 EST Sat, 12 Aug 2017, 02:30:22 EST Wed, 04 Oct 2017, 10:27:59 EST Thu, 05 Oct 2017, 05:03:23 EST Fri, 06 Oct 2017, 08:59:07 EST Fri, 06 Oct 2017, 09:06:33 EST Fri, 06 Oct 2017, 09:07:57 EST Tue, 31 Oct 2017, 13:23:34 EST Fri, 07 Sep 2018, 12:55:09 EST Filtered Full Citation counts:   Cited 29 times in TR Web of Science Cited 50 times in Scopus Search Google Scholar Access Statistics: 517 Abstract Views, 109 File Downloads  -  Detailed Statistics Created: Wed, 04 Oct 2017, 10:27:59 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.