High performing machine learning for novel catalyst design (MLNovCat)


Main funder

Funder's project number351583


Funds granted by main funder (€)

  • 230 664,00


Funding program


Project timetable

Project start date01/01/2022

Project end date31/12/2024


Summary

Development of new machine learning solvers and data-driven models on GPU infrastructure with applications to novel electrocatalyst design.


Principal Investigator


Other persons related to this project (JYU)


Primary responsible unit


Follow-up groups

Profiling areaNanoscience Center (Department of Physics PHYS, JYFL) (Faculty of Mathematics and Science) (Department of Chemistry CHEM) (Department of Biological and Environmental Science BIOENV) NSC


Related publications and other outputs


Related research datasets


Last updated on 2023-29-08 at 14:52