Can We Predict Materials That Can Be Synthesised?

Szczypiński, Filip T.; Bennett, Steven; Jelfs, Kim E.

Abstract

The discovery of materials is an important element in the development of new technologies and abilities that can help humanity tackle many challenges. Materials discovery is frustratingly slow, with the large time and resource cost often providing only small gains in property performance. Furthermore, researchers are unwilling to take large risks that they will only know the outcome of months or years later. Computation is playing an increasing role in allowing rapid screening of large numbers of materials from vast search space to identify promising candidates for laboratory synthesis and testing. However, there is a problem, in that many materials computationally predicted to have encouraging properties cannot be readily realised in the lab. This minireview looks at how we can tackle the problem of confirming that hypothetical materials are synthetically realisable, through consideration of all the stages of the materials discovery process, from obtaining the components, reacting them to a material in the correct structure, through to processing into a desired form. In an ideal world, a material prediction would come with an associated ‘recipe’ for the successful laboratory preparation of the material. We discuss the opportunity to thus prevent wasted effort in experimental discovery programmes, including those using automation, to accelerate the discovery of novel materials.

Citation

Szczypiński, F. T., Bennett, S., & Jelfs, K. E. (2021). Can We Predict Materials That Can Be Synthesised?. Chemical Science, 12(3), 830-840. https://doi.org/10.1039/D0SC04321D

• Journal Article Type: Article
• Acceptance Date: Nov 25, 2020
• Online Publication Date: Dec 9, 2020
• Publication Date: Jan 21, 2021
• Deposit Date: Feb 18, 2025
• Journal: Chemical Science
• Print ISSN: 2041-6520
• Electronic ISSN: 2041-6539
• Publisher: Royal Society of Chemistry
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 3
• Pages: 830-840
• DOI: https://doi.org/10.1039/D0SC04321D
• Public URL: https://durham-repository.worktribe.com/output/3489162