Closed-Loop Multitarget Optimization for Discovery of New Emulsion Polymerization Recipes

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F15%3A43900258" target="_blank" >RIV/60461373:22340/15:43900258 - isvavai.cz</a>
Result on the web
<a href="http://pubs.acs.org/doi/10.1021/acs.oprd.5b00210" target="_blank" >http://pubs.acs.org/doi/10.1021/acs.oprd.5b00210</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1021/acs.oprd.5b00210" target="_blank" >10.1021/acs.oprd.5b00210</a>

Result language
angličtina
Original language name
Closed-Loop Multitarget Optimization for Discovery of New Emulsion Polymerization Recipes
Original language description
Self-optimization of chemical reactions enables faster optimization of reaction conditions or discovery of molecules with required target properties. The technology of self-optimization has been expanded to discovery of new process recipes for manufacture of complex functional products. A new machine-learning algorithm, specifically designed for multiobjective target optimization with an explicit aim to minimize the number of "expensive" experiments, guides the discovery process. This "black-box" approach assumes no a priori knowledge of chemical system and hence particularly suited to rapid development of processes to manufacture specialist lowvolume, high-value products. The approach was demonstrated in discovery of process recipes for a semibatch emulsion copolymerization, targeting a specific particle size and full conversion.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
CI - Industrial chemistry and chemical engineering
OECD FORD branch
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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