An Artificial Intelligence Platform for Accelerating Materials Discovery (AIPAM)

The project aims to develop software services to create and execute computational materials science workflows, with a primary focus on the integration of data structures that follow the FAIR data principle. The team will mature tools and services required to support materials science research and develop a webservice of artificial intelligence for materials scientists. This includes the development and integration of machine-learning-driven decision-making on models as well as automated and robotics assisted materials synthesis. We aim to accelerate de-risking and maturing the AiMater© pilot platform currently under development by the LPI team. The pilot platform and its components have been disclosed and protected via copyright by the IDTK. The project will enable to make full advantage of the Accelerated Materials Discovery capabilities and assets of HBKU-QEERI and Artificial Intelligence at HBKU-CSE to translate them into licensed and marketable products and solutions. It is strongly supported by existing facilities such as but not limited to QF and HBKU IT infrastructures and laboratories. It will also benefit from the collaboration with HBKU IT for the deployment of the platform to end users using state-of-the-art cloud hosting.

Hamad Bin Khalifa University (HBKU)