Over the past decade, a novel class of inorganic-organic porous materials, nowadays known as MOFs or Metal-Organic Frameworks, emerged as a new domain in solid state research. MOFs are tailor-made nanoporous materials formed by self-assembly of metal ions or clusters, linked together via a variety of bridging ligands. What was initially a scientific curiosity has transformed into a fully qualified field of research. Rapid developments and recent breakthroughs indeed have resulted in the discovery of close to 1000 different MOF structures, even if only a limited number have stable open structures with sufficiently large pores for applications. In order to achieve tailored dimensions of cages and tunnels, and to maximize surface areas, one method is to systematically vary the polyfunctional ligands in MOFs. It is well known that both the adsorption performance of such MOFs are strongly influenced by a combination of competitive adsorption and differences in transport properties.

The present project will focus on innovative classes of MOFs. Grand Canonical Monte Carlo (GCMC)/ Molecular Dynamics (MD) and Hybrid Osmotic Monte Carlo (HOMC) will be used to fully predict the selectivity and transport properties of several newly synthesized MOF materials with respect to different gas mixtures in presence of moisture. A special effort will be dedicated to implement ab initio forcefield in HOMC code to accurately describe the interactions between some guest molecules and the coordinatively unsaturated sites present at the surface of the MOFs.

This work will be performed in strong interactions with groups expert in synthesis of MOF and characterization of their adsorption performances.

The candidate has a strong expertise in molecular simulations applied to materials science.

Starting date: to be discussed

Postion for 1+1 year

Contact : Prof. G. Maurin, Institut Charles Gerhardt UMR CNRS 5253, Université Montpellier, France, email :[email protected], https://scholar.google.com/citations?hl=fr&user=QNfwyjgAAAAJ&view_op=list_works&sortby=pubdat