Catalytic nanoparticles contain various sites: for instance, the sites C (center of a hexagonal facet; nine neighbors marked in yellow), E (edge between two hexagonal facets; seven neighbors in green) and K (kink, at the corner between three facets; six neighbors in purple). Atoms at edges and terraces appear in light and dark blue, respectively. Each site contributes differently to the total catalytic activity by virtue of its number of neighbors.
Catalysis is at the very heart of modern society. Using a catalyst, one can optimize the energy input or output of chemical reactions and drive them towards desired products. This simple idea has empowered humans to transform the world.
For instance, the European chemical industry, which largely relies on catalytic processes, generates an annual trade surplus of €50 billion (1). Apart from large economic profits, catalysis-based devices such as exhaust gas converters help mitigate the environmental damage of internal-combustion engines. Besides, fuel cells promise to power cars by simply combining hydrogen and oxygen. These cells are clean alternatives to decrease greenhouse gas emissions and end the world’s dependence on fossil fuels.
Catalysis currently faces tremendous challenges. Numerous industrial catalytic processes are not optimal yet, and new, highly active and stable catalysts are required for devices such as fuel cells to be commercially viable.
The question is thus how to find new catalysts, which are generally made of small particles with diameters in the range of nanometers or microns. Since the activity of particles depends on their size, shape and chemical composition (see figure), computational chemistry methodologies are often used to make atom-by-atom designs. Ideally, design routines should find the most active catalysts and outline the characteristics of optimal sites so that new, enhanced materials are created. However, current procedures can only determine the adsorption energetics of optimal catalysts, not their structure. In consequence, screening on large databases is needed to find materials that possess such energetics, and experimenters need to conduct numerous tests on the most active candidates.
Researchers from Leiden University (The Netherlands), Université de Lyon, the ENS de Lyon, UCB Lyon1, CNRS (France), Ruhr-Universität Bochum and Technische Universität München (Germany) have taken the atomic-scale design of catalysts to the next level (2). Their work has been published in the journal Science
Their design procedure, called “coordination-activity plot”, not only determines the adsorption properties of optimal active sites, but also outlines their structure. An additional advantage of this method is that it is based on one of the simplest concepts in chemistry: coordination numbers, which are a count of the atoms in the proximities of the active sites (see examples in the figure).
To test the accuracy of coordination-activity plots, the researchers designed computationally a new type of platinum catalysts to be used in fuel cells. The model catalysts were prepared experimentally through three different synthesis methods and found to display high catalytic activities in all cases.
This work starts a new paradigm in catalysis: the design of materials based on geometric rationales, which are more insightful than their energetic equivalents and facilitate the experimental implementation of computational designs.References:
(1) Chlorine Industry Review 2012-2013. Euro Chlor
, Belgium, 2013.
(2) Federico Calle-Vallejo, Jakub Tymoczko, Viktor Colic, Quang Huy Vu, Marcus D. Pohl, Karina Morgenstern, David Loffreda, Philippe Sautet, Wolfgang Schuhmann, Aliaksandr S. Bandarenka. Finding optimal surface sites on heterogeneous catalysts by counting nearest neighbors. Science