Grand challenges on accelerating discovery in catalysis

• Published in: Catalysis today Vol. 387; pp. 140 - 142
• Main Authors: Toniato, Alessandra, Vaucher, Alain C., Laino, Teodoro
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-03-2022
• Subjects: Accelerated discovery; Automation; Catalysis; Data; Machine learning; Automation; Data; Catalysis; Accelerated discovery; Machine learning
• ISSN: 0920-5861; 1873-4308
• DOI: 10.1016/j.cattod.2021.10.001

Today, about 90% of all chemical processes employ in some stage catalysis with an enormous potential for additional impact in areas like energy, fuels, and production of high volume chemicals. The numerous societal challenges are demanding a dramatically faster pace in the discovery of new catalytic processes, which presents a multiplicity of intellectual and technological challenges. The development of new processes, chemical reactions or catalysts in shorter times requires to design, develop and apply new methods of investigation leveraging all the new emerging technologies. In this viewpoint, we will explore what we consider to be some of the most compelling actions to expand the use of digital technologies in catalysis.
[Display omitted]
•The field of chemistry requires new methods leveraging all emerging technologies.•Artificial intelligence and data are fundamental assets in the future of catalysis.•To accelerate the design of novel catalytic processes digital solutions are needed.•Inhomogeneity is still the great bottleneck in the process.