The Changing Landscape of Materials Discovery

In this perspective, we will discuss the impact of some of the most recent advancements in materials discovery, particularly focusing on the role of robotics, artificial intelligence, and self-driving laboratories, as well as their implications for the Swiss research landscape. While it seems timely to aim for broad, revolutionary breakthroughs in this field, we argue that more incremental steps - such as, for example, fully automatic grinding of solid powders or fully automated Rietveld refinements - may have a more significant impact on materials discovery, at least in the short run. In the center of these considerations is how small, interdisciplinary groups can drive significant progress by contributing targeted innovations, such as e.g.robotic sample preparation or computational predictions. Additionally, given the large investments that are necessary for future infrastructures in materials discovery, we discuss the potential case for the establishment - in the long run - of a national infrastructure, a Swiss Materials Discovery Lab, to support automated material synthesis and advanced characterization, ultimately accelerating innovation in both academic and industrial settings.

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Publication Details

Journal
CHIMIA International Journal for Chemistry
Published
2024-12-18
DOI
https://doi.org/10.2533/chimia.2024.855
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
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article

The Changing Landscape of Materials Discovery

Fabian O. von Rohr
CHIMIA International Journal for Chemistry
Machine Learning in Materials Science
article

The Changing Landscape of Materials Discovery

Fabian O. von Rohr
article en

Abstract

In this perspective, we will discuss the impact of some of the most recent advancements in materials discovery, particularly focusing on the role of robotics, artificial intelligence, and self-driving laboratories, as well as their implications for the Swiss research landscape. While it seems timely to aim for broad, revolutionary breakthroughs in this field, we argue that more incremental steps - such as, for example, fully automatic grinding of solid powders or fully automated Rietveld refinements - may have a more significant impact on materials discovery, at least in the short run. In the center of these considerations is how small, interdisciplinary groups can drive significant progress by contributing targeted innovations, such as e.g.robotic sample preparation or computational predictions. Additionally, given the large investments that are necessary for future infrastructures in materials discovery, we discuss the potential case for the establishment - in the long run - of a national infrastructure, a Swiss Materials Discovery Lab, to support automated material synthesis and advanced characterization, ultimately accelerating innovation in both academic and industrial settings.

CHIMIA International Journal for ChemistryVol. 78(12)
University of Geneva (CH)
Industry, innovation and infrastructure
Openalex Percentile: Top 85%
Machine Learning in Materials Science
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The Changing Landscape of Materials Discovery — Fabian O. von Rohr · CHIMIA International Journal for Chemistry (2024) | TGRS Research Map | TGRS