Negative cooperativity upon hydrogen bond-stabilized O2 adsorption in a redox-active metal–organic framework
Metal-organic frameworks (MOF) can mimic biological systems in the way they interact with molecular oxygen. Drawing inspiration from biological O2 carriers, hydroxo species have been introduced in the Co(OH)2(BBTA) MOF to stabilize cobalt(III)-superoxo species by hydrogen bonding. Additionally, O2-binding weakens in this material as a function of loading, a property called negative cooperativity. This property is typical of enzymes, but it had never been observed in extended framework materials before this study. This unprecedented behavior extends the tunable properties that can be used to design metal–organic frameworks for adsorption-based applications.
Jenny Vitillo, Ph.D., at the time of the research a post-doctoral associate in the Professor Laura Gagliardi's group and now an assistant professor at the University of Insubria, Italy, and Varinia Bernales, Ph.D., at the time of the research a post-doctoral associate in the Professor Laura Gagliardi's group and now a scientist at Dow Chemicals, Italy, performed periodic density functional and wave function-based calculations to identify the different factors responsible for the complex mechanism of O2 adsorption in Co(OH)2(BBTA). Besides reproducing the experimental results and providing support for their interpretation, her calculations allowed her to correlate the decrease in O2 binding with two factors: (i) the decreasing availability of hydroxo species with O2 coverage and (ii) the modification induced by O2 not only on the electronic properties of the cobalt atoms.
This research, "Negative cooperativity upon hydrogen bond-stabilized O2 adsorption in a redox-active metal–organic framework," was published in Nature Communications.
The research was performed as a collaboration between the groups of Professor Laura Gagliardi and Professor Jeff Long from the University of California, Berkeley and was funded by the Nanoporous Materials Genome Center.This research is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-17ER16362 (Predictive Hierarchical Modeling of Chemical Separations and Transformations in Functional Nanoporous Materials: Synergy of Electronic Structure Theory, Molecular Simulations, Machine Learning, and Experiment) and was previously supported by DE-FG02-12ER16362 (Nanoporous Materials Genome: Methods and Software to Optimize Gas Storage, Separations, and Catalysis).