Cargando…

Capturing chemical intuition in synthesis of metal-organic frameworks

We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal-organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As...

Descripción completa

Detalles Bibliográficos
Autores principales: Moosavi, Seyed Mohamad, Chidambaram, Arunraj, Talirz, Leopold, Haranczyk, Maciej, Stylianou, Kyriakos C., Smit, Berend
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358622/
https://www.ncbi.nlm.nih.gov/pubmed/30710082
http://dx.doi.org/10.1038/s41467-019-08483-9
_version_ 1783392032259047424
author Moosavi, Seyed Mohamad
Chidambaram, Arunraj
Talirz, Leopold
Haranczyk, Maciej
Stylianou, Kyriakos C.
Smit, Berend
author_facet Moosavi, Seyed Mohamad
Chidambaram, Arunraj
Talirz, Leopold
Haranczyk, Maciej
Stylianou, Kyriakos C.
Smit, Berend
author_sort Moosavi, Seyed Mohamad
collection PubMed
description We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal-organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date. We illustrate the importance of quantifying this chemical intuition for the synthesis of novel materials.
format Online
Article
Text
id pubmed-6358622
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-63586222019-02-04 Capturing chemical intuition in synthesis of metal-organic frameworks Moosavi, Seyed Mohamad Chidambaram, Arunraj Talirz, Leopold Haranczyk, Maciej Stylianou, Kyriakos C. Smit, Berend Nat Commun Article We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal-organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date. We illustrate the importance of quantifying this chemical intuition for the synthesis of novel materials. Nature Publishing Group UK 2019-02-01 /pmc/articles/PMC6358622/ /pubmed/30710082 http://dx.doi.org/10.1038/s41467-019-08483-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Moosavi, Seyed Mohamad
Chidambaram, Arunraj
Talirz, Leopold
Haranczyk, Maciej
Stylianou, Kyriakos C.
Smit, Berend
Capturing chemical intuition in synthesis of metal-organic frameworks
title Capturing chemical intuition in synthesis of metal-organic frameworks
title_full Capturing chemical intuition in synthesis of metal-organic frameworks
title_fullStr Capturing chemical intuition in synthesis of metal-organic frameworks
title_full_unstemmed Capturing chemical intuition in synthesis of metal-organic frameworks
title_short Capturing chemical intuition in synthesis of metal-organic frameworks
title_sort capturing chemical intuition in synthesis of metal-organic frameworks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358622/
https://www.ncbi.nlm.nih.gov/pubmed/30710082
http://dx.doi.org/10.1038/s41467-019-08483-9
work_keys_str_mv AT moosaviseyedmohamad capturingchemicalintuitioninsynthesisofmetalorganicframeworks
AT chidambaramarunraj capturingchemicalintuitioninsynthesisofmetalorganicframeworks
AT talirzleopold capturingchemicalintuitioninsynthesisofmetalorganicframeworks
AT haranczykmaciej capturingchemicalintuitioninsynthesisofmetalorganicframeworks
AT stylianoukyriakosc capturingchemicalintuitioninsynthesisofmetalorganicframeworks
AT smitberend capturingchemicalintuitioninsynthesisofmetalorganicframeworks