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MIT research team finds most efficient oxygen evolution reaction catalyst yet; potential for hydrogen production and rechargeable metal-air batteries
28 October 2011
A team of MIT researchers lead by Prof. Yang Shao-Horn, in collaboration with Prof. John Goodenough from the University of Texas as Austin, has found one of the most effective catalysts yet discovered for the oxygen evolution reaction (OER) for use in water-splitting to produce hydrogen or in rechargeable metal-air batteries.
The new compound, composed of cobalt, iron and oxygen with other metals (Ba0.5Sr0.5Co0.8Fe0.2O3–δ, BSCF) catalyzes the OER in alkaline media with intrinsic activity that is at least an order of magnitude higher than the state-of-the-art iridium oxide catalyst. A paper on the research, which was supported by the US Department of Energy’s Hydrogen Initiative, the National Science Foundation, the Toyota Motor Corporation and the Chesonis Foundation, is published in the journal Science.
The design of cost-effective, highly active catalysts for energy storage applications is a critical element in the societal pursuit of sustainable energy. The oxygen evolution reaction (OER) in particular is an enabling process for many energy storage options such as direct-solar and electricity-driven water splitting (H2O → H2 + ½O2, and rechargeable metal-air batteries (MxO2 → Mx + O2). The OER kinetics are sluggish, however, even when facilitated by comparatively high activity, precious-metal containing catalysts. This limitation imposes a significant overpotential requirement, similar to the case of the oxygen reduction reaction (ORR) for fuel-cell applications.
...Here we report a distinct OER activity design principle, namely that a near-unity occupancy of the eg orbital of surface transition-metal ions and high covalency in bonding to oxygen can enhance the intrinsic OER activity of perovskite transition-metal oxides in alkaline solution (4OH– → O2 + 2H2O + 4e–). We further show that this design principle has predictive power, from which a highly active OER oxide catalyst was found. Our approach is based on a molecular orbital bonding framework.—Suntivich et al.
The team predicted the high activity of BSCF from a design principle established by the systematic examination of more than 10 transition-metal oxides, which showed that the intrinsic OER activity depends on a specific characteristic: the configuration of the outermost electron of transition metal ions. They used this information to predict the high reactivity of the new compound, which they then confirmed in lab tests.
We not only identified a fundamental principle [that governs the OER activity of different compounds], but also we actually found this new compound.—Yang Shao-Horn
Two catalysts are needed for such a reaction—one that liberates the hydrogen atoms, and another for the oxygen atoms—but the oxygen reaction has been the limiting factor in such systems.
Other groups, including one led by MIT’s Daniel Nocera, have focused on similar catalysts that can operate at low cost in ordinary water. (Earlier post.) But such reactions can occur with higher efficiency in alkaline solutions, which are required for the best previously known catalyst, iridium oxide, as well as for this new compound.
Shao-Horn and her collaborators are now working with Nocera, integrating their catalyst with his artificial leaf to produce a self-contained system to generate hydrogen and oxygen when placed in an alkaline solution. They will also be exploring different configurations of the catalyst material to better understand the mechanisms involved. Their initial tests used a powder form of the catalyst; now they plan to try thin films to better understand the reactions.
In addition, even though they have already found the highest rate of activity yet seen, they plan to continue searching for even more efficient catalyst materials.
Jin Suntivich, Kevin J. May, Hubert A. Gasteiger, John B. Goodenough, and Yang Shao-Horn (2011) A Perovskite Oxide Optimized for Oxygen Evolution Catalysis from Molecular Orbital Principles. Science DOI: 10.1126/science.1212858
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