Mechanistic study of Cu-Ni bimetallic catalysts supported by graphene derivatives for hydrogenation of CO2 to methanol

Inverse design of promising electrocatalysts for CO2 reduction via generative models and bird swarm algorithm

Directly generating material structures with optimal properties is a long-standing goal in material design. Traditional generative models often struggle to efficiently explore the global chemical space, limiting their utility to localized space. Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties. Applied to the design of alloy electrocatalysts for CO2 reduction (CO2RR), MAGECS generates over 250,000 structures, achieving a 2.5-fold increase in high-activity structures (35%) compared to random generation. Five predicted alloys- CuAl, AlPd, Sn2Pd5, Sn9Pd7, and CuAlSe2 are synthesized and characterized, with two showing around 90% Faraday efficiency for CO2RR. This work highlights the potential of MAGECS to revolutionize functional material development, paving the way for fully automated, artificial intelligence-driven material design.

Bimetallic CuPd nanoparticles supported on ZnO or graphene for CO2 and CO conversion to methane and methanol

Carbon dioxide (CO2) and carbon monoxide (CO) hydrogenation to methane (CH4) or methanol (MeOH) is a promising pathway to reduce CO2 emissions and to mitigate dependence on rapidly depleting fossil fuels. Along these lines, a series of catalysts comprising copper (Cu) or palladium (Pd) nanoparticles (NPs) supported on zinc oxide (ZnO) as well as bimetallic CuPd NPs supported on ZnO or graphene were synthesized via various methodologies. The prepared catalysts underwent comprehensive characterization via high-resolution transmission electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDX) mapping, electron energy loss spectroscopy (EELS), X-ray diffraction (XRD), hydrogen temperature-programmed reduction and desorption (H2-TPR and H2-TPD), and deuterium temperature-programmed desorption (D2O-TPD). In the CO2 hydrogenation process carried out at 20 bar and elevated temperatures (300 to 500 °C), Cu, Pd, and CuPd NPs (<5 wt% loading) supported on ZnO or graphene predominantly yielded CH4 as the primary product, with CO generated as a byproduct via the reverse water gas shift (RWGS) reaction. For CO hydrogenation between 400 and 500 °C, the CO conversion was at least 40% higher than the CO2 conversion, with CH4 and CO2 identified as the main products, the latter from water gas shift. Employing 90 wt% Cu on ZnO led to an enhanced CO conversion of 14%, with the MeOH yield reaching 10% and the CO2 yield reaching 4.3% at 230 °C. Overall, the results demonstrate that lower Cu/Pd loading (<5 wt%) supported on ZnO/graphene favored CH4 production, while higher Cu content (90 wt%) promoted MeOH production, for both CO2 and CO hydrogenation at high pressure.

Metal substrate engineering to modulate CO2 hydrogenation to methanol on inverse Zr3O6/CuPd catalysts

It is well known that the performance of some key catalytic reactions has a strong dependence on metal catalyst surfaces. In the current work, this concept is further extended to the CuPd alloy-supported zirconium oxide inverse catalyst for CO2 hydrogenation to methanol. A combined DFT and microkinetic simulation study reveal that both the metal substrate surface and the precise exposed Cu or Pd metal atoms on the substrate have a pivotal influence on the catalytic mechanism and performance of the inverse catalyst for CO2 hydrogenation to methanol. Herein, CuPd(100), (111), and (110) surfaces with either Cu and Pd terminations have been examined, which provided five metal substrates as support for the inverse catalyst. Three different mechanisms, including the formate pathway, RWGS + CO-hydro pathway, and CO2 direct activation pathway, are explored under the same conditions; they take place at the interfacial sites between the metal alloy and oxide. The calculations indicated that the inverse catalyst with the CuPd(100) substrate demonstrates better performance than those with CuPd(110) and (111) for both formate and RWGS + CO-hydro mechanisms. Conversely, the reaction pathway is more sensitive to exposed atoms on the metal substrate. The best inverse catalyst, Zr3O6/CuPd(100) with either Cu or Pd terminations, demonstrated a methanol formation TOF above 0.30 site-1 s-1 and the selectivity was above 90% at 573 K, as evaluated from microkinetic simulation. The coverage analysis indicates the most populated species is HCOO*, which is consistent with experimental reports. Both kinetic and thermodynamics control steps are identified from DRC analysis for the best performing catalysts. Overall, the current study confirms the catalytic performance of the inverse Zr3O6/CuPd catalyst and demonstrates the tunable effects of the metal alloy substrate, which can facilitate effective optimization.

Synergistic performance of a new bimetallic complex supported on magnetic nanoparticles for Sonogashira and C-N coupling reactions

This paper describes the synthesis of a novel Cu-Ni bimetallic system comprising of magnetic nanoparticles, as the core, and 4-amino-3,5-bis(pyridin-2-yl)-1,2,4-triazole (4-ABPT), as a conjugated bridge, between nickel and copper species. With low Cu and Ni loading (0.06 mol% Ni, 0.08 mol% Cu), the resulting Fe3O4@SiO2@4-ABPT/Cu-Ni showed to be a highly efficient catalyst for the Sonogashira and C-N cross-coupling reactions. The developed catalyst was well characterized by FT-IR, XRD, EDX-mapping, FE-SEM, TEM, ICP, VSM, TGA/DTG/DTA, LSV, and XPS techniques. Fe3O4@SiO2@4-ABPT/Cu-Ni nanocatalyst was compatible with a wide range of amines and aryl halides in the Sonogashira and C-N cross-coupling reactions and offered desired coupling products in high to excellent yields under palladium- and solvent-free conditions. Based on the XPS results, the 4-ABPT ligand can adjust electron transfer between Ni and Cu in Fe3O4@SiO2@4-ABPT/Cu-Ni, promoting the formation and stabilization of Cu+ and Ni3+ species. Electronic interactions and the synergistic effect between these metals increased the selectivity and activity of Fe3O4@SiO2@4-ABPT/Cu-Ni catalyst in the Sonogashira and C-N cross-coupling reactions compared with its monometallic counterparts. Additionally, the magnetic properties of Fe3O4@SiO2@4-ABPT/Cu-Ni facilitated its separation from the reaction mixture, promoting its reuse for several times with no significant loss in its catalytic activity or performance.

Adaptive Design of Alloys for CO2 Activation and Methanation via Reinforcement Learning Monte Carlo Tree Search Algorithm

Data-driven machine learning (ML) has earned remarkable achievements in accelerating materials design, while it heavily relies on high-quality data acquisition. In this work, we develop an adaptive design framework for searching for optimal materials starting from zero data and with as few DFT calculations as possible. This framework integrates automatic density functional theory (DFT) calculations with an improved Monte Carlo tree search via reinforcement learning algorithm (MCTS-PG). As a successful example, we apply it to rapidly identify the desired alloy catalysts for CO₂ activation and methanation within 200 MCTS-PG steps. To this end, seven alloy surfaces with high theoretical activity and selectivity for CO₂ methanation are screened out and further validated by comprehensive free energy calculations. Our adaptive design framework enables the fast computational exploration of materials with desired properties via minimal DFT calculations.

A Review on Green Hydrogen Valorization by Heterogeneous Catalytic Hydrogenation of Captured CO2 into Value-Added Products

The catalytic hydrogenation of captured CO2 by different industrial processes allows obtaining liquid biofuels and some chemical products that not only present the interest of being obtained from a very low-cost raw material (CO2) that indeed constitutes an environmental pollution problem but also constitute an energy vector, which can facilitate the storage and transport of very diverse renewable energies. Thus, the combined use of green H2 and captured CO2 to obtain chemical products and biofuels has become attractive for different processes such as power-to-liquids (P2L) and power-to-gas (P2G), which use any renewable power to convert carbon dioxide and water into value-added, synthetic renewable E-fuels and renewable platform molecules, also contributing in an important way to CO2 mitigation. In this regard, there has been an extraordinary increase in the study of supported metal catalysts capable of converting CO2 into synthetic natural gas, according to the Sabatier reaction, or in dimethyl ether, as in power-to-gas processes, as well as in liquid hydrocarbons by the Fischer-Tropsch process, and especially in producing methanol by P2L processes. As a result, the current review aims to provide an overall picture of the most recent research, focusing on the last five years, when research in this field has increased dramatically.

CO2 Hydrogenation Catalyzed by Graphene-Based Materials

In the context of an increased interest in the abatement of CO₂ emissions generated by industrial activities, CO₂ hydrogenation processes show an important potential to be used for the production of valuable compounds (methane, methanol, formic acid, light olefins, aromatics, syngas and/or synthetic fuels), with important benefits for the decarbonization of the energy sector. However, in order to increase the efficiency of the CO₂ hydrogenation processes, the selection of active and selective catalysts is of utmost importance. In this context, the interest in graphene-based materials as catalysts for CO₂ hydrogenation has significantly increased in the last years. The aim of the present paper is to review and discuss the results published until now on graphene-based materials (graphene oxide, reduced graphene oxide, or N-dopped graphenes) used as metal-free catalysts or as catalytic support for the thermocatalytic hydrogenation of CO₂. The reactions discussed in this paper are CO₂ methanation, CO₂ hydrogenation to methanol, CO₂ transformation into formic acid, CO₂ hydrogenation to high hydrocarbons, and syngas production from CO₂. The discussions will focus on the effect of the support on the catalytic process, the involvement of the graphene-based support in the reaction mechanism, or the explanation of the graphene intervention in the hydrogenation process. Most of the papers emphasized the graphene’s role in dispersing and stabilizing the metal and/or oxide nanoparticles or in preventing the metal oxidation, but further investigations are needed to elucidate the actual role of graphenes and to propose reaction mechanisms.