The particle size dependence of CO oxidation on model planar titania supported gold catalysts measured by parallel thermographic imaging

The dome of gold nanolized for catalysis

Gold is noble in bulk but turns out to be a superior catalyst at the nanoscale when supported on oxides, in particular titania. The critical thickness for activity, namely two-layer gold particles on titania, observed two decades ago represents one of the most influential mysteries in the recent history of heterogeneous catalysis. By developing a Bayesian optimization controlled global potential energy surface exploration tool with machine learning potential, here we determine the atomic structures of gold particles within ∼2 nm on a TiO2 surface. We show that the smallest stable Au nanoparticle is Au24 which is pinned on the oxygen-rich TiO2 and exhibits an unprecedented dome architecture made by a single-layer Au sheet but with an apparent two-atomic-layer height. Importantly, this has the highest activity for CO oxidation at room temperature. The physical origin of the high activity is the outstanding electron storage ability of the nano-dome, which activates the lattice oxygen of the oxide. The determined CO oxidation mechanism, the simulated rate and the fitted apparent energy barrier are consistent with known experimental facts, providing key evidence for the presence of both the high-activity Au dome and the low-activity close-packed Au particles in real catalysts. The future direction for the preparation of active and stable Au-based catalysts is thus outlined.

Infrared Thermography as a Powerful, Versatile, and Elegant Research Tool in Chemistry: Principles and Application to Catalysis and Adsorption

In this Review, diverse chemical problems that have been approached by means of infrared thermography (IRT) are covered in depth. Moreover, some novel steps forward in this field are made, described and discussed. Namely, the latest-generation IRT performance capabilities are harnessed in full; the initial phase of catalytic CO oxidation (called "fast ignition") is presented at the 0.01 s temporal resolution; at the same resolution, the thermal manifestation of the adsorption-desorption wave propagation after the gaseous reactant pulsed (0.6 s) wetting is exhibited. Furthermore, a radical difference in the thermal behavior of differently calcined γ-Al₂ O₃ supported Au catalysts, which underwent successive H₂ O and CO attacks, is demonstrated, and the generally accepted fact that the catalyst temperature reflects the catalytic activity is validated experimentally. It is shown that latest-generation IRT may serve as unique and highly informative research tool in chemistry.

High-throughput experimentation meets artificial intelligence: a new pathway to catalyst discovery

High throughput experimentation in heterogeneous catalysis provides an efficient solution to the generation of large datasets under reproducible conditions. Knowledge extraction from these datasets has mostly been performed using statistical methods, targeting the optimization of catalyst formulations. The combination of advanced machine learning methodologies with high-throughput experimentation has enormous potential to accelerate the predictive discovery of novel catalyst formulations that do not exist with current statistical design of experiments. This perspective describes selective examples ranging from statistical design of experiments for catalyst synthesis to genetic algorithms applied to catalyst optimization, and finally random forest machine learning using experimental data for the discovery of novel catalysts. Lastly, this perspective also provides an outlook on advanced machine learning methodologies as applied to experimental data for materials discovery.

Screening NOx Storage Performance—Demonstrating a High Throughput Approach for Evaluating Emission Control Catalysts under Transient Conditions

At hte the high throughput (HT) approach is applied in the field of environmental catalysis on a routine basis. Research programs for automotive applications require validated screening protocols for conditions relevant to engine exhaust as well as experimental measures to ensure quality control using statistical design of experiment. To illustrate the HT approach for a test protocol with dynamic feed switches in a 48-fold reactor, 15 model catalysts for lean NOx traps (LNT) were prepared and screened fresh and after 800 °C hydrothermal aging. In the fresh state, highest NOx efficiency was found at 350–450 °C. A ranking of BaO > SrO > CaO was found as the most active NOx storage components when used as dopants on alumina. 800 °C aging results in a severe performance loss. Using XRD and BET analysis, Pt sintering is identified as most likely cause. These findings agree well with results from conventional tests reported in the literature.