SOURCE-LINKED INTELLIGENCE

Materials map for microstructures of inorganic materials

CORDIS · observation · Publication date unknown

Materials map for microstructures of inorganic materials Machine learning (ML) is an emerging tool to accelerate the materials discovery, a crucial part of the global competitiveness of Europe. Conventional materials discovery has been based on voyages of chemists and materials scientists in the materials space. They have navigated themselves according to their experience-based maps in their brains to find novel materials from innumerable candidate materials. Then, how can novice researchers navigate themselves? The project SPECIALS (materialS maP for microstructurEs of inorganiC materIALS) will provide a map by leveraging expertise of the host and the experienced researcher (ER): inorganic chemistry, physical chemistry, and computer science. The project approach is distinct from the conventional ML approaches: the ER will focus on microstructures of target materials, because functionalities of the inorganic materials are microstructure-depend

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

236340

unit

EUR