I presented my work on reductive chlorine loss of L6Cl12 linker in Zr-L6Cl12-MOF

I presented my work on accelerated design of in-plane ordered MAX phases using high-throughput DFT calculations

The Artificial Intelligence for Materials Science (AIMS) meeting was hosted by National Institute of Science and Technology (NIST). The theme of the meeing was the application of Artificial-intelligence (AI) tools such as machine-learning, deep-learning and various optimization techniques to accelerate materials discovery. 

Presentation video

2022 MaRDA Meeting

The aim of this year's MaRDA meeting is a taking a deep dive into the MGI 2.0 strategic plan, and connecting researchers within the field. I presented a poster on the accelerated discovery of in-plane ordered MAX phases (i-MAX). This type of material is of particular interest because its magnetic properties and the superior electrochemical properties of its 2D derivatives, dubbed i-MXenes. In this work, I performed high-throughput DFT calculation of the stabilities of compounds within the OQMD framwork with different M, M', A and X elemental combinations. The I successfully identified many compounds that are thermodynamically stable but have not yet been experimentally synthesized.