Tracking the Evolution of Single-Atom Catalysts for the CO2 Electrocatalytic Reduction Using Operando X-ray Absorption Spectroscopy and Machine Learning

Materials Containing Single-, Di-, Tri-, and Multi-Metal Atoms Bonded to C, N, S, P, B, and O Species as Advanced Catalysts for Energy, Sensor, and Biomedical Applications

Modifying the coordination or local environments of single-, di-, tri-, and multi-metal atom (SMA/DMA/TMA/MMA)-based materials is one of the best strategies for increasing the catalytic activities, selectivity, and long-term durability of these materials. Advanced sheet materials supported by metal atom-based materials have become a critical topic in the fields of renewable energy conversion systems, storage devices, sensors, and biomedicine owing to the maximum atom utilization efficiency, precisely located metal centers, specific electron configurations, unique reactivity, and precise chemical tunability. Several sheet materials offer excellent support for metal atom-based materials and are attractive for applications in energy, sensors, and medical research, such as in oxygen reduction, oxygen production, hydrogen generation, fuel production, selective chemical detection, and enzymatic reactions. The strong metal-metal and metal-carbon with metal-heteroatom (i.e., N, S, P, B, and O) bonds stabilize and optimize the electronic structures of the metal atoms due to strong interfacial interactions, yielding excellent catalytic activities. These materials provide excellent models for understanding the fundamental problems with multistep chemical reactions. This review summarizes the substrate structure-activity relationship of metal atom-based materials with different active sites based on experimental and theoretical data. Additionally, the new synthesis procedures, physicochemical characterizations, and energy and biomedical applications are discussed. Finally, the remaining challenges in developing efficient SMA/DMA/TMA/MMA-based materials are presented.

DFT Study on Effect of Metal Type and Coordination Environment on CO2 ECR to C1 Products over M-N-C Catalysts

Electrocatalytic reduction (ECR) of CO2 to chemical products is an important carbon emission reduction method. This work uses DFT to study the stability of N-doped graphene-supported four metal single-atom catalysts (M-N-C) and the effects of the coordination environment and metal centers on the selectivity of CO2 ECR to C1 products. The results show that Fe, Co, Ni, and Cu have good stability. The coordination environment has a significant modulating effect on product selectivity, and the change of the number of ligand nitrogen atoms will affect the size of the potential-limiting step of each product. When the number of nitrogen ligands is the same, the different metal centers of the M-N-C catalyst have a significant effect on the selectivity of different products. In addition, the introduction of nitrogen atom ligands can adjust the electronic structure of the graphene-supported metal center, increase the d-band center of most metals, and improve the reaction activity.

Electrochemical CO2 Activation and Valorization on Metallic Copper and Carbon-Embedded N-Coordinated Single Metal MNC Catalysts

The electrochemical reductive valorization of CO2, referred to as the CO2RR, is an emerging approach for the conversion of CO2-containing feeds into valuable carbonaceous fuels and chemicals, with potential contributions to carbon capture and use (CCU) for reducing greenhouse gas emissions. Copper surfaces and graphene-embedded, N-coordinated single metal atom (MNC) catalysts exhibit distinctive reactivity, attracting attention as efficient electrocatalysts for CO2RR. This review offers a comparative analysis of CO2RR on copper surfaces and MNC catalysts, highlighting their unique characteristics in terms of CO2 activation, C1/C2(+) product formation, and the competing hydrogen evolution pathway. The assessment underscores the significance of understanding structure-activity relationships to optimize catalyst design for efficient and selective CO2RR. Examining detailed reaction mechanisms and structure-selectivity patterns, the analysis explores recent insights into changes in the chemical catalyst states, atomic motif rearrangements, and fractal agglomeration, providing essential kinetic information from advanced in/ex situ microscopy/spectroscopy techniques. At the end, this review addresses future challenges and solutions related to today's disconnect between our current molecular understanding of structure-activity-selectivity relations in CO2RR and the relevant factors controlling the performance of CO2 electrolyzers over longer times, with larger electrode sizes, and at higher current densities.

Carbon Catalysts Empowering Sustainable Chemical Synthesis via Electrochemical CO2 Conversion and Two-Electron Oxygen Reduction Reaction

Carbon materials hold significant promise in electrocatalysis, particularly in electrochemical CO2 reduction reaction (eCO2 RR) and two-electron oxygen reduction reaction (2e- ORR). The pivotal factor in achieving exceptional overall catalytic performance in carbon catalysts is the strategic design of specific active sites and nanostructures. This work presents a comprehensive overview of recent developments in carbon electrocatalysts for eCO2 RR and 2e- ORR. The creation of active sites through single/dual heteroatom doping, functional group decoration, topological defect, and micro-nano structuring, along with their synergistic effects, is thoroughly examined. Elaboration on the catalytic mechanisms and structure-activity relationships of these active sites is provided. In addition to directly serving as electrocatalysts, this review explores the role of carbon matrix as a support in finely adjusting the reactivity of single-atom molecular catalysts. Finally, the work addresses the challenges and prospects associated with designing and fabricating carbon electrocatalysts, providing valuable insights into the future trajectory of this dynamic field.

Reversible Structural Evolution of Metal-Nitrogen-Doped Carbon Catalysts During CO2 Electroreduction: An Operando X-ray Absorption Spectroscopy Study

Electrochemical CO2 reduction (CO2 RR) is a rising technology, aiming to reduce the energy sector dependence on fossil fuels and to produce carbon-neutral raw materials. Metal-nitrogen-doped carbons (M-N-C) are emerging, cost-effective catalysts for this reaction; however, their long-term stability is a major issue. To overcome this, understanding their structural evolution is crucial, requiring systematic in-depth operando studies. Here a series of M-N-C catalysts (M = Fe, Sn, Cu, Co, Ni, Zn) is investigated using operando X-ray absorption spectroscopy. It is found that the Fe-N-C and Sn-N-C are prone to oxide clusters formation even before CO2 RR. In contrast, the respective metal cations are singly dispersed in the as-prepared Cu-N-C, Co-N-C, Ni-N-C, and (Zn)-N-C. During CO2 RR, metallic clusters/nanoparticles reversibly formed in all catalysts, except for the Ni-N-C. This phenomenon, previously observed only in Cu-N-C, thus is ubiquitous in M-N-C catalysts. The competition between M-O and M-N interactions is an important factor determining the mobility of metal species in M-N-C. Specifically, the strong interaction between the Ni centers and the N-functional groups of the carbon support results in higher stability of the Ni single-sites, leading to the excellent performance of Ni-N-C in the CO2 to CO conversion, in comparison to other transition metals.

Migration and aggregation of Pt atoms on metal oxide-supported ceria nanodomes control reverse water gas shift reaction activity

Single-atom catalysts (SACs) are particularly sensitive to external conditions, complicating the identification of catalytically active species and active sites under in situ or operando conditions. We developed a methodology for tracing the structural evolution of SACs to nanoparticles, identifying the active species and their link to the catalytic activity for the reverse water gas shift (RWGS) reaction. The new method is illustrated by studying structure-activity relationships in two materials containing Pt SACs on ceria nanodomes, supported on either ceria or titania. These materials exhibited distinctly different activities for CO production. Multimodal operando characterization attributed the enhanced activity of the titania-supported catalysts at temperatures below 320 ˚C to the formation of unique Pt sites at the ceria-titania interface capable of forming Pt nanoparticles, the active species for the RWGS reaction. Migration of Pt nanoparticles to titania support was found to be responsible for the deactivation of titania-supported catalysts at elevated temperatures. Tracking the migration of Pt atoms provides a new opportunity to investigate the activation and deactivation of Pt SACs for the RWGS reaction.

Machine Learning Confirms the Formation Mechanism of a Single-Atom Catalyst via Infrared Spectroscopic Analysis

Single-atom catalysts (SACs) offer significant potential across various applications, yet our understanding of their formation mechanism remains limited. Notably, the pyrolysis of zeolitic imidazolate frameworks (ZIFs) stands as a pivotal avenue for SAC synthesis, of which the mechanism can be assessed through infrared (IR) spectroscopy. However, the prevailing analysis techniques still rely on manual interpretation. Here, we report a machine learning (ML)-driven analysis of the IR spectroscopy to unravel the pyrolysis process of Pt-doped ZIF-67 to synthesize Pt-Co3O4 SAC. Demonstrating a total Pearson correlation exceeding 0.7 with experimental data, the algorithm provides correlation coefficients for the selected structures, thereby confirming crucial structural changes with time and temperature, including the decomposition of ZIF and formation of Pt-O bonds. These findings reveal and confirm the formation mechanism of SACs. As demonstrated, the integration of ML algorithms, theoretical simulations, and experimental spectral analysis introduces an approach to deciphering experimental characterization data, implying its potential for broader adoption.

Single-Atom Heterogeneous Catalysts: Human- and AI-Driven Platform for Augmented Designs, Analytics and Reality-Enabled Manufacturing

Heterogeneous catalysts with targeted functionality can be designed with atomic precision, but it is challenging to retain the structure and performance upon the scaled-up manufacturing. Particularly challenging is to ensure the "atomic economy", where every catalytic site is most gainfully utilized. Given the emerging synergistic integration of human- and artificial intelligence (AI)-driven augmented designs (AD), augmented analytics (AA), and augmented reality manufacturing (AM) platforms, this minireview focuses on single-atom heterogeneous catalysts (SAHCs) and examines the current status, challenges, and future perspectives of translating atomic-level structural precision and data-driven discovery to next-generation industrial manufacturing. We critically examine the atomistic insights into structure-driven SAHCs functionality and discuss the opportunities and challenges on the way towards the synergistic human-AI collaborative data-driven platform capable of monitoring, analyzing, manufacturing, and retaining the atomic-scale structure and functions. Enhanced by the atomic-level AD, AA, and AM, evolving from the current high-throughput capabilities and digital materials manufacturing acceleration, this synergistic human-AI platform is promising to enable atom-efficient and atomically precise heterogeneous catalyst production.