Metal oxides by Design

In this project we will develop the first structured database for metal-oxide porous materials (POMzites), this database will contain new data and knowledge in the area of self-assembly of oxide materials. The database will accelerate the generation of new all-inorganic metal oxide framework materials and, it will provide new information as to how the aggregation of such materials occurs. Computationally exploring the combinatorial space generated by the self-assembly of known metal oxides to predict new ones is a challenging task. The research in LVN-group aims to discover new tailored metal oxide materials using inverse design. The new materials will be targeted from the beginning searching for a real-world application (e.g. redox flow batteries, memory devices, porosity, selectivity, etc.). With the final aim of achieving rational design of prospective oxide materials we will apply deep generative models to this class of materials.