Modified Energy Span Analysis Reveals Heterogeneous Catalytic Kinetics

Turning on Low-Temperature Catalytic Conversion of Biomass Derivatives through Teaming Pd1 and Mo1 Single-Atom Sites

On-purpose atomic scale design of catalytic sites, specifically active and selective at low temperature for a target reaction, is a key challenge. Here, we report teamed Pd1 and Mo1 single-atom sites that exhibit high activity and selectivity for anisole hydrodeoxygenation to benzene at low temperatures, 100-150 °C, where a Pd metal nanoparticle catalyst or a MoO3 nanoparticle catalyst is individually inactive. The catalysts built from Pd1 or Mo1 single-atom sites alone are much less effective, although the catalyst with Pd1 sites shows some activity but low selectivity. Similarly, less dispersed nanoparticle catalysts are much less effective. Computational studies show that the Pd1 and Mo1 single-atom sites activate H2 and anisole, respectively, and their combination triggers the hydrodeoxygenation of anisole in this low-temperature range. The Co3O4 support is inactive for anisole hydrodeoxygenation by itself but participates in the chemistry by transferring H atoms from Pd1 to the Mo1 site. This finding opens an avenue for designing catalysts active for a target reaction channel such as conversion of biomass derivatives at a low temperature where neither metal nor oxide nanoparticles are.

Computational Design of Catalysts with Experimental Validation: Recent Successes, Effective Strategies, and Pitfalls

Computation has long proven useful in understanding heterogeneous catalysts and rationalizing experimental findings. However, computational design with experimental validation requires somewhat different approaches and has proven more difficult. In recent years, there have been increasing successes in such computational design with experimental validation. In this Perspective, we discuss some of these recent successes and the methodologies used. We also discuss various design strategies more broadly, as well as approximations to consider and pitfalls to try to avoid when designing for experiment. Overall, computation can be a powerful and efficient tool in guiding catalyst design but must be combined with a strong fundamental understanding of catalysis science to be most effective in terms of both choosing the design methodology and choosing which materials to pursue experimentally.