The Vital Role of Step-Edge Sites for Both CO Activation and Chain Growth on Cobalt Fischer–Tropsch Catalysts Revealed through First-Principles-Based Microkinetic Modeling Including Lateral Interactions

Understanding the effect of adsorption sites of CO at cobalt surface on its reactivity with H2/H by DFT calculations

Cobalt (Co) is widely used in Fischer-Tropsch synthesis (FTS), converting synthesis gas, carbon monoxide + hydrogen (CO + H2), to long-chain hydrocarbons. The adsorption of CO on the Co surface is the key step in FTS. In this work, the effect of CO adsorption sites on the reactions between CO and H2 was investigated by using density functional theory (DFT). The energetics and structures of the reactions between the adsorbed CO (CO*) and H2/adsorbed H2 (H2*)/adsorbed H atom (H*) were calculated. The results show that the reaction between CO* and H2 is initiated by the molecular adsorption of H2 on the Co surface. The reactions between CO* and H2*/H* are influenced by CO adsorption sites. For the reaction system of CO* + H2*, it has the lowest reaction barrier when CO is adsorbed at the hcp site, while for CO* + H*, it has the lowest reaction barrier when CO is adsorbed on the top site. Kinetic analysis indicates that to improve the reactivity of CO + H2 in FTS, the adsorption of CO should be controlled to favour the top and bridge sites. This article is part of the theme issue 'Celebrating the 15th anniversary of the Royal Society Newton International Fellowship'.

Fischer-Tropsch Synthesis for the Production of Sustainable Aviation Fuel: Formation of Tertiary Amines from Ammonia Contaminants

Fischer-Tropsch synthesis combined with product workup is a promising route toward synthetic aviation fuel from renewable hydrogen and carbon sources like biomass, CO2, and waste. Cost savings can be achieved by reducing the number of gas treatment steps in new plants, but the consequence of contaminants in the feed needs investigation. While feeding 2.6 ppmV ammonia to a Fischer-Tropsch reactor, it was shown that ammonia was predominantly chemically converted into organic amines, with most nitrogen found in the water phase (89%), followed by heavy wax (7%) and light wax (1%). The concentration difference between water and light wax was shown to be due to the post-condensation separation of amines on polarity. Amines up to a chain length of 120 were detected in the heavy wax with MALDI-FT-ICR-MS, which, in combination with the high nitrogen content, suggests that amines have a similar chain growth probability compared to the main hydrocarbon products. Detailed product analysis with three independent analytical techniques showed that tertiary N,N-dimethylalkylamines were by far the most abundant amine class. This suggests that ammonia is decomposed on the cobalt surface and, potentially as a dimethylamine fragment, incorporated in the growing chain. Further evidence was obtained from the abundance of trimethylamine and from the reconciled nitrogen product analysis up to C100, which showed that the amine product distribution followed from naphtha onward the same ASF kinetics as alkanes and oxygenates while being distinctively different from the alkene distribution. The presented findings provide further avenues for studies of the Fischer-Tropsch reaction mechanism and indicate the opportunity of cost saving on gas treatment, while further validation is required to assess the impact on hydrocracking and product quality.

Multivariate Bayesian Optimization of CoO Nanoparticles for CO2 Hydrogenation Catalysis

The hydrogenation of CO2 holds promise for transforming the production of renewable fuels and chemicals. However, the challenge lies in developing robust and selective catalysts for this process. Transition metal oxide catalysts, particularly cobalt oxide, have shown potential for CO2 hydrogenation, with performance heavily reliant on crystal phase and morphology. Achieving precise control over these catalyst attributes through colloidal nanoparticle synthesis could pave the way for catalyst and process advancement. Yet, navigating the complexities of colloidal nanoparticle syntheses, governed by numerous input variables, poses a significant challenge in systematically controlling resultant catalyst features. We present a multivariate Bayesian optimization, coupled with a data-driven classifier, to map the synthetic design space for colloidal CoO nanoparticles and simultaneously optimize them for multiple catalytically relevant features within a target crystalline phase. The optimized experimental conditions yielded small, phase-pure rock salt CoO nanoparticles of uniform size and shape. These optimized nanoparticles were then supported on SiO2 and assessed for thermocatalytic CO2 hydrogenation against larger, polydisperse CoO nanoparticles on SiO2 and a conventionally prepared catalyst. The optimized CoO/SiO2 catalyst consistently exhibited higher activity and CH4 selectivity (ca. 98%) across various pretreatment reduction temperatures as compared to the other catalysts. This remarkable performance was attributed to particle stability and consistent H* surface coverage, even after undergoing the highest temperature reduction, achieving a more stable catalytic species that resists sintering and carbon occlusion.

A Review of Theoretical Studies on Carbon Monoxide Hydrogenation via Fischer-Tropsch Synthesis over Transition Metals

The increasing demand for clean fuels and sustainable products has attracted much interest in the development of active and selective catalysts for CO conversion to desirable products. This review maps the theoretical progress of the different facets of most commercial catalysts, including Co, Fe, Ni, Rh, and Ru. All relevant elementary steps involving CO dissociation and hydrogenation and their dependence on surface structure, surface coverage, temperature, and pressure are considered. The dominant Fischer-Tropsch synthesis mechanism is also explored, including the sensitivity to the structure of H-assisted CO dissociation and direct CO dissociation. Low-coordinated step sites are shown to enhance catalytic activity and suppress methane formation. The hydrogen adsorption and CO dissociation mechanisms are highly dependent on the surface coverage, in which hydrogen adsorption increases, and the CO insertion mechanism becomes more favorable at high coverages. It is revealed that the chain-growth probability and product selectivity are affected by the type of catalyst and its structure as well as the applied temperature and pressure.

CO2 Hydrogenation to Gasoline and Aromatics: Mechanistic and Predictive Insights from DFT, DRIFTS and Machine Learning

The emission of CO2 from fossil fuels is the largest driver of global climate change. To realize the target of a carbon-neutrality by 2050, CO2 capture and utilization is crucial. The efficient conversion of CO2 to C5+ gasoline and aromatics remains elusive mainly due to CO2 thermodynamic stability and the high energy barrier of the C-C coupling step. Herein, advances in mechanistic understanding via Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS), density functional theory (DFT), and microkinetic modeling are discussed. It further emphasizes the power of machine learning (ML) to accelerate the search for optimal catalysts. A significant effort has been invested into this field of research with volumes of experimental and characterization data, this study discusses how they can be used as input features for machine learning prediction in a bid to better understand catalytic properties capable of accelerating breakthroughs in the process.

Activating Molybdenum Carbide Nanoparticle Catalysts under Mild Conditions Using Thermally Labile Ligands

Transition-metal carbides are promising low-cost materials for various catalytic transformations due to their multifunctionality and noble-metal-like behavior. Nanostructuring transition-metal carbides offers advantages resulting from the large surface-area-to-volume ratios inherent in colloidal nanoparticle catalysts; however, a barrier for their utilization is removal of the long-chain aliphatic ligands on their surface to access active sites. Annealing procedures to remove these ligands require temperatures greater than the catalyst synthesis and catalytic reaction temperatures and may further result in coking or particle sintering that can reduce catalytic performance. One way to circumvent this problem is by replacing the long-chain aliphatic ligands with smaller ligands that can be easily removed through low-temperature thermolytic decomposition. Here, we present the exchange of native oleylamine ligands on colloidal α-MoC_1-x nanoparticles for thermally labile tert-butylamine ligands. Analyses of the ligand exchange reaction by solution ¹H NMR spectroscopy, FT-IR spectroscopy, and thermogravimetric analysis-mass spectrometry (TGA-MS) confirm the displacement of 60% of the native oleylamine ligands for the thermally labile tert-butylamine, which can be removed with a mild activation step at 250 °C. Catalytic site densities were determined by carbon monoxide (CO) chemisorption, demonstrating that the mild thermal treatment at 250 °C activates ca. 25% of the total binding sites, while the native oleylamine-terminated MoC_1-x nanoparticles showed no available surface binding sites after this low-temperature treatment. The mild pretreatment at 250 °C also shows distinctly different initial activities and postinduction period selectivities in the CO₂ hydrogenation reaction for the ligand exchanged MoC_1-x nanoparticle catalysts and the as-prepared material.

Towards universal neural network potential for material discovery applicable to arbitrary combination of 45 elements

Computational material discovery is under intense study owing to its ability to explore the vast space of chemical systems. Neural network potentials (NNPs) have been shown to be particularly effective in conducting atomistic simulations for such purposes. However, existing NNPs are generally designed for narrow target materials, making them unsuitable for broader applications in material discovery. Here we report a development of universal NNP called PreFerred Potential (PFP), which is able to handle any combination of 45 elements. Particular emphasis is placed on the datasets, which include a diverse set of virtual structures used to attain the universality. We demonstrated the applicability of PFP in selected domains: lithium diffusion in LiFeSO4F, molecular adsorption in metal-organic frameworks, an order-disorder transition of Cu-Au alloys, and material discovery for a Fischer-Tropsch catalyst. They showcase the power of PFP, and this technology provides a highly useful tool for material discovery.

Enumerating Active Sites on Metal Nanoparticles: Understanding the Size Dependence of Cobalt Particles for CO Dissociation

Detailed understanding of structure sensitivity, a central theme in heterogeneous catalysis, is important to guide the synthesis of improved catalysts. Progress is hampered by our inability to accurately enumerate specific active sites on ubiquitous metal nanoparticle catalysts. We employ herein atomistic simulations based on a force field trained with quantum-chemical data to sample the shape of cobalt particles as a function of their size. Algorithms rooted in pattern recognition are used to identify surface atom arrangements relevant to CO dissociation, the key step in the Fischer-Tropsch (FT) reaction. The number of step-edge sites that can catalyze C-O bond scission with a low barrier strongly increases for larger nanoparticles in the range of 1-6 nm. Combined with microkinetics of the FT reaction, we can reproduce experimental FT activity trends. The stabilization of step-edge sites correlates with increasing stability of terrace nanoislands on larger nanoparticles.

A combined theoretical/experimental study highlighting the formation of carbides on Ru nanoparticles during CO hydrogenation

Formation of stable carbides during CO bond dissociation on small ruthenium nanoparticles (RuNPs) is demonstrated, both by means of DFT calculations and by solid state ¹³C NMR techniques. Theoretical calculations of chemical shifts in several model clusters are employed in order to secure experimental spectroscopic assignations for surface ruthenium carbides. Mechanistic DFT investigations, carried out on a realistic Ru₅₅ nanoparticle model (∼1 nm) in terms of size, structure and surface composition, reveal that ruthenium carbides are obtained during CO hydrogenation. Calculations also indicate that carbide formation via hydrogen-assisted hydroxymethylidyne (COH) pathways is exothermic and occurs at reasonable kinetic cost on standard sites of the RuNPs, such as 4-fold ones on flat terraces, and not only in steps as previously suggested. Another novel outcome of the DFT mechanistic study consists of the possible formation of μ₆ ruthenium carbides in the tip-B₅ site, similar examples being known only for molecular ruthenium clusters. Moreover, based on DFT energies, the possible rearrangement of the surface metal atoms around the same tip-site results in a μ-Ru atom coordinated to the remaining RuNP moiety, reminiscent of a pseudo-octahedral metal center on the NP surface.

First-principles microkinetic simulations revealing the scaling relations and structure sensitivity of CO2 hydrogenation to C1 & C2 oxygenates on Pd surfaces

CO₂ hydrogenation to alcohols and other oxygenates on Pd(211) and Pd(111) surfaces was studied by microkinetic modelling. Energy scaling relations on two surfaces were established. Activity plots as a function of reaction conditions were identified.

Reverse water-gas shift reaction over Pt/MoOx/TiO2: reverse Mars–van Krevelen mechanism via redox of supported MoOx

Pt/MoO_x/TiO₂ shows excellent catalytic performance for the reverse water-gas shift reaction at 250 °C via reverse Mars–van Krevelen mechanism.