When a heterogeneous catalyst is active, it forms metastable structures that constantly transform into each other. These structures contribute differently to the catalytic function. Here we show the role of different metastable oxygen species on a Ni catalyst during dry reforming of methane by combining environmental scanning electron microscopy, near ambient pressure X-ray photoelectron spectroscopy, on-line product detection and computer vision. We highlight the critical role of dissociative CO₂ adsorption in regulating the oxygen content of the catalyst and in CH₄ activation. We also discover rate oscillations during dry reforming of methane resulting from the sequential transformation of metastable oxygen species that exhibit different catalytic properties: atomic surface oxygen, subsurface oxygen and bulk NiO_x. The imaging approach allowed the localization of fluctuating surface regions that correlated directly with catalytic activity. The study highlights the importance of metastability and operando analytics in catalysis science and provides impetus towards the design of catalytic systems.

In recent years, the catalytic dry reforming of methane (DRM) has increasingly come into academic focus. The interesting aspect of this reaction is seemingly the conversion of CO₂ and methane, two greenhouse gases, into a valuable synthesis gas (syngas) mixture with an otherwise unachievable but industrially relevant H₂/CO ratio of one. In a possible scenario, the chemical conversion of CO₂ and CH₄ to syngas could be used in consecutive reactions to produce synthetic fuels, with combustion to harness the stored energy. Although the educts of DRM suggest a superior impact of this reaction to mitigate global warming, its potential as a chemical energy converter and greenhouse gas absorber has still to be elucidated. In this review article, we will provide insights into the industrial maturity of this reaction and critically discuss its applicability as a cornerstone in the energy transition. We derive these insights from assessing the current state of research and knowledge on DRM. We conclude that the entire industrial process of syngas production from two greenhouse gases, including heating with current technologies, releases at least 1.23 moles of CO₂ per mol of CO₂ converted in the catalytic reaction. Furthermore, we show that synthetic fuels derived from this reaction exhibit a negative carbon dioxide capturing efficiency which is similar to burning methane directly in the air. We also outline potential applications and introduce prospective technologies toward a net-zero CO₂ strategy based on DRM.

Ammonia is industrially produced by the Haber-Bosch process over a fused, multi-promoted iron-based catalyst. Current knowledge about the reaction has been derived from model systems of reduced structural complexity, impeding any clear-cut structure-activity correlation relevant for the industrial counterpart. Here, we unveil the structural evolution of complex, technical, multi-promoted ammonia synthesis catalysts by operando scanning electron microscopy and near-ambient pressure X-ray photoelectron spectroscopy. We highlight that the activation is the critical step in which the catalyst is formed and decode the pivotal role of the promoters. We discover that the active structure consists of a nanodispersion of Fe covered by mobile K-containing adsorbates, so called “ammonia K”. The porous catalyst is stabilized by mineral cementitious phases containing oxides of Al, Si, Ca, and Fe. The synergism between the different promoters contributes simultaneously to the structural stability, hierarchical architecture, catalytic activity, and poisoning resistance. The confluence of these aspects is the key for the superior performance of technical catalyst formulations.

Frustrated phase transitions represent the ideal working state of a heterogeneous catalyst. These states exist within a narrow parameter window, making them difficult to stabilize. Here, it is shown for the selective oxidation of 2‐propanol to acetone over Co ₃ O ₄ spinels that the addition of water extends the stability regime of the relevant frustrated phase transition. This conclusion is based on results obtained from multi‐modal experiments, including operando scanning electron microscopy (OSEM), near ambient pressure X‐ray photoelectron spectroscopy (NAP‐XPS), transmission electron microscopy (TEM), and computer vision analysis. It is found that the most selective state for acetone formation coincides with a dynamic spinel structure that fluctuates through reversible redox processes. At elevated temperatures, this metastable state undergoes a complete phase transition into the rock‐salt CoO phase characterized by low acetone selectivity. This process is found to be mediated by the generation of mobile vacancies. The addition of water vapor mitigates vacancy mobility and stabilizes the selective, but thermodynamically frustrated, state. As such, the study conceptualizes a strategy to extend the lifetime of a catalyst during reaction by the adequate addition of a co‐reactant.

In catalysis research, the amount of microscopy data acquired when imaging dynamic processes is often too much for non-automated quantitative analysis. Developing machine learned segmentation models is challenged by the requirement of high-quality annotated training data. We thus substitute expert-annotated data with a physics-based sequential synthetic data model. We study environmental SEM (ESEM) data collected from isopropanol oxidation to acetone over cobalt oxide. Upon applying a temperature program during the reaction a phase transition occurs, reducing the catalyst selectivity towards acetone. This is accompanied on the μm ESEM by the formation of cracks between the pores of the catalyst surface. We aim to generate synthetic data to train a neural network capable of semantic segmentation (pixel-wise labelling) of this ESEM data. This analysis will lead to insights into this phase transition. To generate synthetic data that approximates this transition, our algorithm composes the ESEM images of the room-temperature catalyst with dynamically evolving synthetic cracks satisfying physical construction principles, gathered from qualitative knowledge accessible in the ESEM data. We mimic the surface crack growth propagation along surface paths, avoiding close vicinity to nearby pores. This physics-based approach results in a lowered rate of false positives compared to a random approach.