Sabatier principle of metal-support interaction for design of ultrastable metal nanocatalysts

Advances in Matrix-Supported Palladium Nanocatalysts for Water Treatment

Advanced catalysts are crucial for a wide range of chemical, pharmaceutical, energy, and environmental applications. They can reduce energy barriers and increase reaction rates for desirable transformations, making many critical large-scale processes feasible, eco-friendly, energy-efficient, and affordable. Advances in nanotechnology have ushered in a new era for heterogeneous catalysis. Nanoscale catalytic materials are known to surpass their conventional macro-sized counterparts in performance and precision, owing it to their ultra-high surface activities and unique size-dependent quantum properties. In water treatment, nanocatalysts can offer significant promise for novel and ecofriendly pollutant degradation technologies that can be tailored for customer-specific needs. In particular, nano-palladium catalysts have shown promise in degrading larger molecules, making them attractive for mitigating emerging contaminants. However, the applicability of nanomaterials, including nanocatalysts, in practical deployable and ecofriendly devices, is severely limited due to their easy proliferation into the service environment, which raises concerns of toxicity, material retrieval, reusability, and related cost and safety issues. To overcome this limitation, matrix-supported hybrid nanostructures, where nanocatalysts are integrated with other solids for stability and durability, can be employed. The interaction between the support and nanocatalysts becomes important in these materials and needs to be well investigated to better understand their physical, chemical, and catalytic behavior. This review paper presents an overview of recent studies on matrix-supported Pd-nanocatalysts and highlights some of the novel emerging concepts. The focus is on suitable approaches to integrate nanocatalysts in water treatment applications to mitigate emerging contaminants including halogenated molecules. The state-of-the-art supports for palladium nanocatalysts that can be deployed in water treatment systems are reviewed. In addition, research opportunities are emphasized to design robust, reusable, and ecofriendly nanocatalyst architecture.

Quantitatively Determining Surface-Adsorbate Properties from Vibrational Spectroscopy with Interpretable Machine Learning

Learning microscopic properties of a material from its macroscopic measurables is a grand and challenging goal in physical science. Conventional wisdom is to first identify material structures exploiting characterization tools, such as spectroscopy, and then to infer properties of interest, often with assistance of theory and simulations. This indirect approach has limitations due to the accumulation of errors from retrieving structures from spectral signals and the lack of quantitative structure-property relationship. A new pathway directly from spectral signals to microscopic properties is highly desirable, as it would offer valuable guidance toward materials evaluation and design via spectroscopic measurements. Herein, we exploit machine-learned vibrational spectroscopy to establish quantitative spectrum-property relationships. Key interaction properties of substrate-adsorbate systems, including adsorption energy and charge transfer, are quantitatively determined directly from Infrared and Raman spectroscopic signals of the adsorbates. The machine-learned spectrum-property relationships are presented as mathematical formulas, which are physically interpretable and therefore transferrable to a series of metal/alloy surfaces. The demonstrated ability of quantitative determination of hard-to-measure microscopic properties using machine-learned spectroscopy will significantly broaden the applicability of conventional spectroscopic techniques for materials design and high throughput screening under operando conditions.

Emerging single atom catalysts in gas sensors

Single atom catalysts (SACs) offer unprecedented opportunities for high-efficiency reactions taking place in many important fields of catalytic processes, electrochemistry, and photoreactions. Due to their maximized atomic utilization and unique electronic and chemical properties, SACs can provide high activity and excellent selectivity for gas adsorption and electron transport, leveraging SACs that enhance the detection sensitivity and selectivity to target gases. In the past few years, SACs including both noble (Pt, Pd, Au, etc.) and non-noble (Mn, Ni, Zn etc.) metals have been demonstrated to be very useful in optimizing sensing performances. However, a comprehensive review on this topic is still missing. Herein, we summarize the synthesis technologies of SACs that are applicable to gas sensors. The electronic and chemical interactions between SACs and host sensing materials, which are crucial to sensor functions, are discussed. Then, we highlight the application progress of various SACs in gas sensors. Prospects in the creation of new sensing materials with emerging SACs and versatile supports are also present. Finally, the challenges and prospects of SACs in the future development of sensors are analyzed.

Polymer Photoelectrodes for Solar Fuel Production: Progress and Challenges

Converting solar energy to fuels has attracted substantial interest over the past decades because it has the potential to sustainably meet the increasing global energy demand. However, achieving this potential requires significant technological advances. Polymer photoelectrodes are composed of earth-abundant elements, e.g. carbon, nitrogen, oxygen, hydrogen, which promise to be more economically sustainable than their inorganic counterparts. Furthermore, the electronic structure of polymer photoelectrodes can be more easily tuned to fit the solar spectrum than inorganic counterparts, promising a feasible practical application. As a fast-moving area, in particular, over the past ten years, we have witnessed an explosion of reports on polymer materials, including photoelectrodes, cocatalysts, device architectures, and fundamental understanding experimentally and theoretically, all of which have been detailed in this review. Furthermore, the prospects of this field are discussed to highlight the future development of polymer photoelectrodes.

Adatom Bonding Sites in a Nickel-Fe3 O4 (001) Single-Atom Model Catalyst and O2 Reactivity Unveiled by Surface Action Spectroscopy with Infrared Free-Electron Laser Light

Single-atom (SA) catalysis presently receives much attention with its promise to decrease the cost of the active material while increasing the catalyst's performance. However, key details such as the exact location of SA species and their stability are often unclear due to a lack of atomic level information. Here, we show how vibrational spectra measured with surface action spectroscopy (SAS) and density functional theory (DFT) simulations can differentiate between different adatom binding sites and determine the location of Ni and Au single atoms on Fe3 O4 (001). We reveal that Ni and Au adatoms selectively bind to surface oxygen ions which are octahedrally coordinated to Fe ions. In addition, we find that the Ni adatoms can activate O2 to superoxide in contrast to the bare surface and Ni in subsurface positions. Overall, we unveil the advantages of combining SAS and DFT for improving the understanding of single-atom catalysts.

Platinum clusters anchored on sulfur-doped ordered mesoporous carbon for chemoselective hydrogenation of halogenated nitroarenes

Chemoselective hydrogenation of unsaturated organic compounds is a significant research topic in the catalysis field. Herein, a sulfur-doped ordered mesoporous carbon (SMC) material was prepared to anchor ultrafine platinum (Pt) clusters for the chemoselective hydrogenation of halogenated nitroarenes. The confinement effect of the ordered pores and the strong metal-support interaction caused by Pt clusters and sulfur atoms, efficiently suppress the aggregation and regulate the electronic states of the ultrafine Pt clusters. Thus, the hydrogenation of parachloronitrobenzene (p-CNB) shows high selectivity catalyzed by the ultrafine Pt clusters with electron-rich states. Meanwhile, the catalytic performance of the hydrogenation reaction catalyzed by Pt/SMC is capable of being maintained after at least 5 cycles, and the catalytic universality can also be applied to different halogenated nitroarenes hydrogenation. Therefore, this study may promote the research into the construction of noble metal-based catalysts for chemoselective hydrogenation reactions in green and sustainable chemical processes.

Discovery of Electronic Structure and Interfacial Interaction Features in Catalytic Activity

The selective transformation of inert bonds (C-H, C-O, C-C, C-F, etc.) via various catalysts is one of the most challenging areas, with applications in organic synthesis, materials science, and biological and pharmaceutical chemistry. The catalytic performance of homogeneous and heterogeneous catalysts can be rationally controlled in two ways: (i) electronic structure modulation of the active site, such as the metal center, ligands, and coordination modes, to improve the catalytic activity and stability and (ii) tuning intermolecular or interfacial interactions to promoting the reaction kinetics by accelerating the transmission of electrons between the catalyst and solvents or support. The rational design of catalysts based on adjustable features, such as metal (monometallic or bimetallic) active sites, crystal phase, ligands, solvents, and supports for inert bond activation under mild conditions remains a challenge. This Perspective summarizes the features of electronic structures, interfacial interactions, and their effects on molecular catalysis, metal-organic frameworks (MOFs), and natural mineral catalysis. The discovery of efficient catalysts could be promoted using machine-learning methods with high-performance descriptors. More attention should be paid to high-throughput quantum-chemical computations and experiments, automatic searches of chemical reaction pathways, and efficient machine-learning or deep-learning methods to accelerate catalyst design and synthesis in the future.

Synergistic effect between 1D Co3S4/MoS2 heterostructures to boost the performance for alkaline overall water splitting

Reasonably designing and constructing the hetero-bimetal sulfides with high performance for oxygen/hydrogen evolution reaction (O/HER) in the alkaline electrolyte are promising but still challenging. Herein, the 1D Co3S4/MoS2 bimetallic sulfide...

Confinement of nano-gold in 3D hierarchically structured gadolinium-doped ceria mesocrystal: synergistic effect of chemical composition and structural hierarchy in CO and propane oxidation

Gadolinium-doped ceria hierarchical gold catalyst shows four-fold TOF increase compared to undoped non-hierarchical system, proving the synergistic effect of doping and structural hierarchy in propane oxidation.

Understanding and controlling the formation of surface anion vacancies for catalytic applications

Systematic computational efforts aimed at calculating surface anion vacancy formation energies as important descriptors of catalytic performance are summarized.