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Atomically precise materials engineering through deep learning

CORDIS · observation · Publication date unknown

Atomically precise materials engineering through deep learning Modern technology demands ever-increasing precision in materials engineering, especially in the creation of novel advanced materials where atomic structure dictates function. Traditional on-surface chemical synthesis allows the controlled formation of molecular structures, but lacks the precision to build molecules atom-by-atom. Scanning Probe Microscopy (SPM) has been a game- changer in nanoscale materials engineering by allowing high-resolution imaging and the ability to study and manipulate individual molecules. However, the manual manipulation of molecules using SPM remains painstakingly slow in large-scale engineering - automation is the essential breakthrough required for progress. ARCADE will solve this by creating a multi-component deep learning infrastructure to achieve the required SPM control. This revolutionary approach will enable three breakthrough functionali

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recordType

award

status

SIGNED

region

EU

value

2498394

unit

EUR