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Towards Predictive Synthesis of Inorganic Materials Using Network Science

Accelerating materials discovery is the cornerstone of modern technological competitiveness. Yet, the inorganic synthesis of new compounds is often an important bottleneck in this quest. Well-established quantum chemistry and experimental synthesis methods combined with consolidated network science...

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Detalles Bibliográficos
Autores principales: Aziz, Alex, Carrasco, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8724131/
https://www.ncbi.nlm.nih.gov/pubmed/34993176
http://dx.doi.org/10.3389/fchem.2021.798838
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author Aziz, Alex
Carrasco, Javier
author_facet Aziz, Alex
Carrasco, Javier
author_sort Aziz, Alex
collection PubMed
description Accelerating materials discovery is the cornerstone of modern technological competitiveness. Yet, the inorganic synthesis of new compounds is often an important bottleneck in this quest. Well-established quantum chemistry and experimental synthesis methods combined with consolidated network science approaches might provide revolutionary knowledge to tackle this challenge. Recent pioneering studies in this direction have shown that the topological analysis of material networks hold great potential to effectively explore the synthesizability of inorganic compounds. In this Perspective we discuss the most exciting work in this area, in particular emerging new physicochemical insights and general concepts on how network science can significantly help reduce the timescales required to discover new materials and find synthetic routes for their fabrication. We also provide a perspective on outstanding problems, challenges and open questions.
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spelling pubmed-87241312022-01-05 Towards Predictive Synthesis of Inorganic Materials Using Network Science Aziz, Alex Carrasco, Javier Front Chem Chemistry Accelerating materials discovery is the cornerstone of modern technological competitiveness. Yet, the inorganic synthesis of new compounds is often an important bottleneck in this quest. Well-established quantum chemistry and experimental synthesis methods combined with consolidated network science approaches might provide revolutionary knowledge to tackle this challenge. Recent pioneering studies in this direction have shown that the topological analysis of material networks hold great potential to effectively explore the synthesizability of inorganic compounds. In this Perspective we discuss the most exciting work in this area, in particular emerging new physicochemical insights and general concepts on how network science can significantly help reduce the timescales required to discover new materials and find synthetic routes for their fabrication. We also provide a perspective on outstanding problems, challenges and open questions. Frontiers Media S.A. 2021-12-21 /pmc/articles/PMC8724131/ /pubmed/34993176 http://dx.doi.org/10.3389/fchem.2021.798838 Text en Copyright © 2021 Aziz and Carrasco. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Chemistry
Aziz, Alex
Carrasco, Javier
Towards Predictive Synthesis of Inorganic Materials Using Network Science
title Towards Predictive Synthesis of Inorganic Materials Using Network Science
title_full Towards Predictive Synthesis of Inorganic Materials Using Network Science
title_fullStr Towards Predictive Synthesis of Inorganic Materials Using Network Science
title_full_unstemmed Towards Predictive Synthesis of Inorganic Materials Using Network Science
title_short Towards Predictive Synthesis of Inorganic Materials Using Network Science
title_sort towards predictive synthesis of inorganic materials using network science
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8724131/
https://www.ncbi.nlm.nih.gov/pubmed/34993176
http://dx.doi.org/10.3389/fchem.2021.798838
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