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dc.contributor.authorIglesias, Diego
dc.contributor.authorHaddad, Dina
dc.contributor.authorSans, Victor
dc.date.accessioned2023-10-13T10:06:08Z
dc.date.available2023-10-13T10:06:08Z
dc.date.issued2022-12-01
dc.identifier.citationIGLESIAS, Diego; HADDAD, Dina; SANS, Victor. Recent Developments in Process Digitalisation for Advanced Nanomaterial Syntheses. Chemistry‐Methods, 2022, vol. 2, no 12, p. e202200031.ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/204474
dc.description.abstractDigitalisation and industry 4.0 are set to profoundly change the way chemical and materials discovery and development work. The integration of multiple enabling technologies such as flow synthesis, automation, analytics, and real-time reaction control lead to highly efficient, productive, data-driven discovery and synthetic protocols. For instance, the development of flow chemistry enables the fine control and automation of process parameters such as flow rates, temperature, and pressure, which inherently enhances process efficiency. Flow chemistry presents a more sustainable means of manufacturing in terms of waste minimisation, as it enables the integration of synthetic processes with downstream processing. Furthermore, it allows the integration of analytical techniques to provide in situ process monitoring of large amounts of process and product data. The application of Artificial Intelligence (AI) and/or Machine Learning (ML) techniques allows rapid decision making that can optimise existing processes, and it has also been applied in the discovery of novel materials, synthetic pathways and chemicals. All this is contributing to an effective digitalisation of chemical and material synthetic processes from the laboratory to large-scale industrial deployment. This paper presents recent developments in the effective digitalisation of chemical synthetic processes which integrates continuous flow synthesis, analytics and artificial intelligence technologies. Specifically, this paper illustrates the emerging trend of process digitalisation through the advanced syntheses of materials with catalytic, optical and optoelectronic applications.ca_CA
dc.format.extent9 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherWileyca_CA
dc.rights© 2022 The Authors. Published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.ca_CA
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/ca_CA
dc.subjectcontinuous-flowca_CA
dc.subjectdigitalisationca_CA
dc.subjectin-line analyticsca_CA
dc.subjectmachine learningca_CA
dc.subjectprocess automationca_CA
dc.titleRecent Developments in Process Digitalisation for Advanced Nanomaterial Synthesesca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1002/cmtd.202200031
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA
project.funder.nameGeneralitat Valenciana. Center for Forestry Research & Experimentation (CIEF)ca_CA
project.funder.nameMinisterio de Ciencia, Innovación y Universidades (Spain)ca_CA
project.funder.nameUniversitat Jaume Ica_CA
oaire.awardNumberCIDEGENT/2018/036ca_CA
oaire.awardNumberPID2020-119628RB-C33ca_CA
oaire.awardNumberUJI-B2020-44ca_CA


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© 2022 The Authors. Published by Wiley-VCH GmbH. This is an open access
article under the terms of the Creative Commons Attribution License, which
permits use, distribution and reproduction in any medium, provided the
original work is properly cited.
Excepto si se señala otra cosa, la licencia del ítem se describe como: © 2022 The Authors. Published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.