High-Throughput Screening of Alloy Catalysts for Dry Methane Reforming

Unbounding the Future: Designing NiAl-Based Catalysts for Dry Reforming of Methane

Dry reforming of methane (DRM), the catalytic conversion of CH4 and CO2 into syngas (H2+CO), is an important process closely correlated to the environment and chemical industry. NiAl-based catalysts have been reported to exhibit excellent activity, low cost, and environmental friendliness. At the same time, the rapid deactivation caused by carbon deposition, Ni sintering, and phase transformation exerts great challenges for its large-scale applications. This review summarizes the recent advances in NiAl-based catalysts for DRM, particularly focusing on the strategies to construct efficient and stable NiAl-based catalysts. Firstly, the thermodynamics and elementary steps of DRM, including the activation of reactants and coke formation and elimination, are summarized. The roles of Al2O3 and its mixed oxides as the support, and the influences of the promoters employed in NiAl-based catalysts over the DRM performance, are then illustrated. Finally, the design of anti-coking and anti-sintering NiAl-based catalysts for DRM is suggested as feasible and promising by tailoring the structure and states of Ni and the modification of Al-based supports including small Ni size, high Ni dispersion, proper basicity, strong metal-support interaction (SMSI), active oxygen species as well as high phase stability.

Discovery of Alloy Catalysts Beyond Pd for Selective Hydrogenation of Reformate via First-Principle Screening with Consideration of H-Coverage

The highly selective hydrogenation to remove olefins is a significant refining approach for the reformate. Herein, a library of transition metal for reformate hydrogenation is tested experimentally to validate the predictive level of catalytic activity from our theoretical framework, which combines ab initio calculations and microkinetic modeling, with consideration of surface H-coverage effect on hydrogenation kinetics. The favorable H coverage of specific alloy surface under relevant hydrogenation condition, is found to be determined by its corresponding alloy composition. Besides, olefin hydrogenation rate is determined as a function of two descriptors, i.e. H coverage and binding energies of atomic hydrogen, paving the way to computationally screen on metal component in the periodic table. Evaluation of 172 bimetallic alloys based on the activity volcano map, as well as benzene hydrogenation rate, identifies prospective superior candidates and experimentally confirms that Zn3Ir1 outperforms pure Pd catalysts for the selective hydrogenation refining of reformate. The insights into H-coverage-related microkinetic modelling have enabled us to both theoretically understand experimental findings and identify novel catalysts, thus, bridging the gap between first-principle simulations and industrial applications. This work provides useful guidance for experimental catalyst design, which can be easily extended to other hydrogenation reaction.

AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS)

Zero-carbon energy and negative emission technologies are crucial for achieving a carbon neutral future, and nanomaterials have played critical roles in advancing such technologies. More recently, due to the explosive growth in data, the adoption and exploitation of artificial intelligence (AI) as part of the materials research framework have had a tremendous impact on the development of nanomaterials. AI has enabled revolutionary next-generation paradigms to significantly accelerate all stages of material discovery and facilitate the exploration of the enormous design space. In this review, we summarize recent advancements of AI applications in nanomaterials discovery, with a special emphasis on the selected applications of AI and nanotechnology for the net-zero emission future including the development of solar cells, hydrogen energy, battery materials for renewable energy, and CO₂ capture and conversion materials for carbon capture, utilization and storage (CCUS) technologies. In addition, we discuss the limitations and challenges of current AI applications in this area by identifying the gaps that exist in current development. Finally, we present the prospect for future research directions in order to facilitate the large-scale applications of artificial intelligence for advancements in nanomaterials.

Highly Active Ni-Ru Bimetallic Catalyst Integrated with MFI Zeolite-Loaded Cerium Zirconium Oxide for Dry Reforming of Methane

The dry reforming of methane (DRM) is a new potential technology that converts two major greenhouse gases into useful chemical feedstocks. The main challenge faced by this process is maintaining the catalyst with high catalytic activity and long-term stability. Here, a simple and effective preparation route for the synthesis of functional nanomolecular sieve catalysts (NiRu_xCZZ5) from kaolinite tailings was developed for dry reforming of methane with CO₂. The silica monoliths with flower-like spherical and micropore structures (ZSM-5) were prepared by crystal growth method, and the metal components were loaded by ultrasonic-assisted impregnation method. The NiRu_0.5CZZ5 catalyst exhibited excellent catalytic performance (maxmium CO₂ and CH₄ conversions up to 100 and 95.6%, respectively) and very good stability (up to 100h). The interfacial confinement and the strong support interaction are principally responsible for the excellent catalytic activity of the catalyst. The in situ DRIFTS was used to elucidate the possible carbon conversion steps, and stable surface intermediates were also identified.

The role of Mo species in Ni-Mo catalysts for dry reforming of methane

The Ni-Mo catalyst has attracted significant attention due to its excellent coke-resistance in dry reforming of methane (DRM) reaction, but its detailed mechanism is still vague. Herein, Mo-doped Ni (Ni-Mo_x) and MoO_x adsorbed Ni surfaces (MoO_x@Ni) are employed to explore the DRM reaction mechanism and the effect of coke-resistance. Due to the electron donor effect of Mo, the antibonding states below the Fermi level between Ni and C increase and the adsorption of C decrease, thereby inhibiting the carbonization of Ni. On account of the strong Mo and O interaction, more O atoms gather around Mo, which inhibits the oxidation of Ni and may promote the formation of MoO_x species on the Ni-Mo catalyst. The presence of Mo-O species promotes the carbon oxidation, forming a unique redox cycle (MoO_x ↔ MoO_x-1) similar to the Mars-van Krevelen (MvK) mechanism, explaining the excellent anti-carbon deposition effect on the Ni-Mo catalyst.

Highly Efficient ZIF-67-Derived PtCo Alloy-CN Interface for Low-Temperature Aqueous-Phase Fischer-Tropsch Synthesis

Designing new materials for selective Fischer-Tropsch synthesis (FTS) is an elegant way to enhance local feedstock utilization like biomass and waste. In this approach, we have designed a thermally and chemically stable bimetallic PtCo/NC hybrid nanocomposite catalyst derived from a zeolitic imidazolate framework (ZIF-67, which contains cobalt as a metal center) through carbonization for low-temperature (413-473 K) aqueous-phase Fischer-Tropsch synthesis (AFTS). The selectivity of the desired range of hydrocarbons is adjusted using a highly dispersed PtCo bimetallic alloy, which facilitates extraordinary reduction of a metal oxide to active species by the synergic effect under the AFTS reaction conditions. The ZIF-derived catalyst tested in this study exhibited the highest activity to date for very low temperatures (433 K) in aqueous-phase Fischer-Tropsch synthesis with CO conversion rates between 0.61 and 1.20 mol_CO·mol_Co^-1·h^-1. Insights of the remarkable catalyst activity were examined by in situ X-ray photoelectron spectroscopy (XPS) studies corroborated by density functional theory (DFT) calculation. The bimetallic Co₃Pt (111) surface was found to be highly active for the C-C coupling reaction between surface-adsorbed C and CO, forming a CCO intermediate with a very low activation barrier (E_a = 0.37 eV), in comparison to the C-C coupling activation barrier obtained over the Co (111) surface (E_a = 0.87 eV). This unique approach and observations create a new path for developing next-generation advanced catalyst systems and processes for selective low-temperature FTS.

Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system.

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SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11244-021-01543-9.

DFT-Based Microkinetic Model Analysis of Dry Reforming of Methane over Ru7/CeO2(111) and Ru7/CeO2(110): Key Role of Surface Lattice Oxygen Vacancy

CeO2 supported metal cluster catalysts play the vital roles on dry reforming (DRM) reaction which convert greenhouse gases (CH4 and CO2) to syngas, but the mechanism of surface lattice oxygen...

The Effect of Preparation Method of Ni-Supported SiO2 Catalysts for Carbon Dioxide Reforming of Methane

Reforming methane to produce syngas is a subject that generates considerable interest. The process requires catalysts that possess high-performance active sites to activate stable C–H bonds. Herein, we report a facile synthetic strategy to prepare Ni-based catalysts by complexation–impregnation (Ni-G/SiO2-C) and precipitation–impregnation (Ni-G/SiO2-P) methods using glycine as a complexing agent. The particle size of Ni in both types of catalysts is decreased by adding glycine in the preparation process. Nevertheless, the preparation methods and amount of glycine play a significant role in the particle size and distribution of Ni over the Ni-based catalysts. The smaller particle size and narrower distribution of Ni were obtained in the Ni-G/SiO2-P catalyst. The catalysts were comparatively tested for carbon-dioxide reforming of methane (CDR). Ni-G/SiO2-P showed better CDR performance than Ni-G/SiO2-C and Ni/SiO2 and increased stability because of the smaller particle size and narrower distribution of Ni. Moreover, a high-performance Ni-based catalyst was prepared by optimizing the amount of glycine added. An unobservable deactivation was obtained over Ni-G-2/SiO2-P and Ni-G-3/SiO2-P for CDR during TOS = 20 h. Thus, a new promising method is described for the preparation of Ni-based catalysts for CDR.