Finite Size Effects in Chemical Bonding: From Small Clusters to Solids

Unraveling Hydrogen Adsorption on Transition Metal-Doped [Mo3S13]2- Clusters: Insights from Density Functional Theory Calculations

Molecular and dissociative hydrogen adsorption of transition metal (TM)-doped [Mo3S13]2- atomic clusters were investigated using density functional theory calculations. The introduced TM dopants form stable bonds with S atoms, preserving the geometric structure. The S-TM-S bridging bond emerges as the most stable configuration. The preferred adsorption sites were found to be influenced by various factors, such as the relative electronegativity, coordination number, and charge of the TM atom. Notably, the presence of these TM atoms remarkably improved the hydrogen adsorption activity. The dissociation of a single hydrogen molecule on TM[Mo3S13]2- clusters (TM = Sc, Cr, Mn, Fe, Co, and Ni) is thermodynamically and kinetically favorable compared to their bare counterparts. The extent of favorability monotonically depends on the TM impurity, with a maximum activation barrier energy ranging from 0.62 to 1.58 eV, lower than that of the bare cluster (1.69 eV). Findings provide insights for experimental research on hydrogen adsorption using TM-doped molybdenum sulfide nanoclusters, with potential applications in the field of hydrogen energy.

211At on gold nanoparticles for targeted radionuclide therapy application

Targeted alpha therapy (TAT) is a methodology that is being developed as a promising cancer treatment using the α-particle decay of radionuclides. This technique involves the use of heavy radioactive elements being placed near the cancer target area to cause maximum damage to the cancer cells while minimizing the damage to healthy cells. Using gold nanoparticles (AuNPs) as carriers, a more effective therapy methodology may be realized. AuNPs can be good candidates for transporting these radionuclides to the vicinity of the cancer cells since they can be labeled not just with the radionuclides, but also a host of other proteins and ligands to target these cells and serve as additional treatment options. Research has shown that astatine and iodine are capable of adsorbing onto the surface of gold, creating a covalent bond that is quite stable for use in experiments. However, there are still many challenges that lie ahead in this area, whether they be theoretical, experimental, and even in real-life applications. This review will cover some of the major developments, as well as the current state of technology, and the problems that need to be tackled as this research topic moves along to maturity. The hope is that with more workers joining the field, we can make a positive impact on society, in addition to bringing improvement and more knowledge to science.

Gold Nanoparticles for CO2 Electroreduction: An Optimum Defined by Size and Shape

Understanding the size-dependent behavior of nanoparticles is crucial for optimizing catalytic performance. We investigate the differences in selectivity of size-selected gold nanoparticles for CO2 electroreduction with sizes ranging from 1.5 to 6.5 nm. Our findings reveal an optimal size of approximately 3 nm that maximizes selectivity toward CO, exhibiting up to 60% Faradaic efficiency at low potentials. High-resolution transmission electron microscopy reveals different shapes for the particles and suggests that multiply twinned nanoparticles are favorable for CO2 reduction to CO. Our analysis shows that twin boundaries pin 8-fold coordinated surface sites and in turn suggests that a variation of size and shape to optimize the abundance of 8-fold coordinated sites is a viable path for optimizing the CO2 electrocatalytic reduction to CO. This work contributes to the advancement of nanocatalyst design for achieving tunable selectivity for CO2 conversion into valuable products.

Terrace-Rich Ultrathin PtCu Surface on Earth-Abundant Metal for Oxygen Reduction Reaction

The activity and stability of the platinum electrode toward the oxygen reduction reaction are size-dependent. Although small nanoparticles have high Pt utilization, the undercoordinated Pt sites on their surface are assumed to have too strong oxygen binding strength, thus often leading to compromised activity and surface instability. Herein, we report an extended nanostructured PtCu ultrathin surface to reduce the number of low-coordination sites without sacrificing the electrochemical active surface area (ECSA). The surface shows (111)-oriented characteristics, as proven by electrochemical probe reactions and spectroscopies. The PtCu surface brings over an order of magnitude increase in specific activity relative to commercial Pt/C and nearly 4-fold enhancement in ECSA compared to traditional thin films. Moreover, due to the weak absorption of air impurities (e.g., SO2, NO, CO) on highly coordinated sites, the catalyst displays enhanced contaminant tolerance compared with nanoparticulate Pt/C. This work promises a broad screening of extended nanostructured surface catalysts for electrochemical conversions.

Theoretical Study of the Defects and Doping in Tuning the Electrocatalytic Activity of Graphene for CO2 Reduction

The application of graphene-based catalysts in the electrocatalytic CO2 reduction reaction (ECO2RR) for mitigating the greenhouse effect and energy shortage is a growing trend. The unique and extraordinary properties of graphene-based catalysts, such as low cost, high electrical conductivity, structural tunability, and environmental friendliness, have rendered them promising materials in this area. By doping heteroatoms or artificially inducing defects in graphene, its catalytic performance can be effectively improved. In this work, the mechanisms underlying the CO2 reduction reaction on 10 graphene-based catalysts were systematically studied. N/B/O-codoped graphene with a single-atom vacancy defect showed the best performance and substantial improvement in catalytic activity compared with pristine graphene. The specific roles of the doped elements, including B, N, and O, as well as the defects, are discussed in detail. By analysing the geometric and electronic structures of the catalysts, we showed how the doped heteroatoms and defects influence the catalytic reaction process and synergistically promoted the catalytic efficiency of graphene.

In silico characterization of nanoparticles

Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often require different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations.

The ABC of Generalized Coordination Numbers and Their Use as a Descriptor in Electrocatalysis

The quest for enhanced electrocatalysts can be boosted by descriptor-based analyses. Because adsorption energies are the most common descriptors, electrocatalyst design is largely based on brute-force routines that comb materials databases until an energetic criterion is verified. In this review, it is shown that an alternative is provided by generalized coordination numbers (denoted by CN ¯ $\overline {{\rm{CN}}} $ or GCN), an inexpensive geometric descriptor for strained and unstrained transition metals and some alloys. CN ¯ $\overline {{\rm{CN}}} $ captures trends in adsorption energies on both extended surfaces and nanoparticles and is used to elaborate structure-sensitive electrocatalytic activity plots and selectivity maps. Importantly, CN ¯ $\overline {{\rm{CN}}} $ outlines the geometric configuration of the active sites, thereby enabling an atom-by-atom design, which is not possible using energetic descriptors. Specific examples for various adsorbates (e.g., *OH, *OOH, *CO, and *H), metals (e.g., Pt and Cu), and electrocatalytic reactions (e.g., O₂  reduction, H₂  evolution, CO oxidation, and reduction) are presented, and comparisons are made against other descriptors.

The Accumulation of Electrical Energy Due to the Quantum-Dimensional Effects and Quantum Amplification of Sensor Sensitivity in a Nanoporous SiO2 Matrix Filled with Synthetic Fulvic Acid

A heterostructured nanocomposite MCM-41<SFA> was formed using the encapsulation method, where a silicon dioxide matrix-MCM-41 was the host matrix and synthetic fulvic acid was the organic guest. Using the method of nitrogen sorption/desorption, a high degree of monoporosity in the studied matrix was established, with a maximum for the distribution of its pores with radii of 1.42 nm. According to the results of an X-ray structural analysis, both the matrix and the encapsulate were characterized by an amorphous structure, and the absence of a manifestation of the guest component could be caused by its nanodispersity. The electrical, conductive, and polarization properties of the encapsulate were studied with impedance spectroscopy. The nature of the changes in the frequency behavior of the impedance, dielectric permittivity, and tangent of the dielectric loss angle under normal conditions, in a constant magnetic field, and under illumination, was established. The obtained results indicated the manifestation of photo- and magneto-resistive and capacitive effects. In the studied encapsulate, the combination of a high value of ε and a value of the tgδ of less than 1 in the low-frequency range was achieved, which is a prerequisite for the realization of a quantum electric energy storage device. A confirmation of the possibility of accumulating an electric charge was obtained by measuring the I-V characteristic, which took on a hysteresis behavior.

Metal-Support Interactions in Heterogeneous Catalysis: DFT Calculations on the Interaction of Copper Nanoparticles with Magnesium Oxide

Oxide supports play an important role in enhancing the catalytic properties of transition metal nanoparticles in heterogeneous catalysis. How extensively interactions between the oxide support and the nanoparticles impact the electronic structure as well as the surface properties of the nanoparticles is hence of high interest. In this study, the influence of a magnesium oxide support on the properties of copper nanoparticles with different size, shape, and adsorption sites is investigated using density functional theory (DFT) calculations. By proposing simple models to reduce the cost of the calculations while maintaining the accuracy of the results, we show using the nonreducible oxide support MgO as an example that there is no significant influence of the MgO support on the electronic structure of the copper nanoparticles, with the exception of adsorption directly at the Cu-MgO interface. We also propose a simplified methodology that allows us to reduce the cost of the calculations, while the accuracy of the results is maintained. We demonstrate in addition that the Cu nanowire model corresponds well to the nanoparticle model, which reduces the computational cost even further.

Genesis of Active Pt/CeO2 Catalyst for Dry Reforming of Methane by Reduction and Aggregation of Isolated Platinum Atoms into Clusters

Atomically dispersed metal catalysts offer the advantages of efficient metal utilization and high selectivities for reactions of technological importance. Such catalysts have been suggested to be strong candidates for dry reforming of methane (DRM), offering prospects of high selectivity for synthesis gas without coke formation, which requires ensembles of metal sites and is a challenge to overcome in DRM catalysis. However, investigations of the structures of isolated metal sites on metal oxide supports under DRM conditions are lacking, and the catalytically active sites remain undetermined. Data characterizing the DRM reaction-driven structural evolution of a cerium oxide-supported catalyst, initially incorporating atomically dispersed platinum, and the corresponding changes in catalyst performance are reported. X-ray absorption and infrared spectra show that the reduction and agglomeration of isolated cationic platinum atoms to form small platinum clusters/nanoparticles are necessary for DRM activity. Density functional theory calculations of the energy barriers for methane dissociation on atomically dispersed platinum and on platinum clusters support these observations. The results emphasize the need for in-operando experiments to assess the active sites in such catalysts. The inferences about the catalytically active species are suggested to pertain to a broad class of catalytic conversions involving the rate-limiting dissociation of light alkanes.

Bulk-like Pt(100)-oriented Ultrathin Surface: Combining the Merits of Single Crystals and Nanoparticles to Boost Oxygen Reduction Reaction

Single crystal surfaces with highly coordinated sites very often hold high specific activities toward oxygen reduction reaction (ORR) and others. Transposing their high specific activity to practical high-surface-area electrocatalysts remains challenging. Here, ultrathin Pt(100) alloy surface is constructed via epitaxial growth. The surface shows 3.1-6.9 % compressive strain and bulk-like characteristics as demonstrated by site-probe reactions and different spectroscopies. Its ORR activity exceeds that of bulk Pt₃ Ni(100) and Pt(111) and presents a 19-fold increase in specific activity and a 13-fold increase in mass activity relative to commercial Pt/C. Moreover, the electrochemically active surface area (ECSA) is increased by 4-fold compared to traditional thin films (e.g. NSTF), which makes the catalyst more tolerant to voltage loss at high current densities under fuel cell operation. This work broadens the family of extended surface catalysts and highlights the knowledge-driven approach in the development of advanced electrocatalysts.

Boosting Benzene Oxidation with a Spin-State-Controlled Nuclearity Effect on Iron Sub-Nanocatalysts

A fundamental understanding of the nature of nuclearity effects is important for the rational design of superior sub-nanocatalysts with low nuclearity, but remains a long-standing challenge. Using atomic layer deposition, we precisely synthesized Fe sub-nanocatalysts with tunable nuclearity (Fe₁ -Fe₄ ) anchored on N,O-co-doped carbon nanorods (NOC). The electronic properties and spin configuration of the Fe sub-nanocatalysts were nuclearity dependent and dominated the H₂ O₂ activation modes and adsorption strength of active O species on Fe sites toward C-H oxidation. The Fe₁ -NOC single atom catalyst exhibits state-of-the-art activity for benzene oxidation to phenol, which is ascribed to its unique coordination environment (Fe₁ N₂ O₃ ) and medium spin state (t_2g ⁴ e_g ¹ ); turnover frequencies of 407 h^-1 at 25 °C and 1869 h^-1 at 60 °C were obtained, which is 3.4, 5.7, and 13.6 times higher than those of Fe dimer, trimer, and tetramer catalysts, respectively.

Copper-Based Catalysts for Electrochemical Reduction of Carbon Dioxide to Ethylene

Electrochemical reduction of CO₂ into high energy density multi-carbon chemicals or fuels (e. g., ethylene) via new renewable energy storage has extraordinary implications for carbon neutrality. Copper (Cu)-based catalysts have been recognized as the most promising catalysts for the electrochemical reduction of CO₂ to ethylene (C₂ H₄ ) due to their moderate CO adsorption energy and moderate hydrogen precipitation potential. However, the poor selectivity, low current density and high overpotential of the CO₂ RR into C₂ H₄ greatly limit its industrial applications. Meanwhile, the complex reaction mechanism is still unclear, which leads to blindness in the design of catalysts. Herein, we systematically summarized the latest research, proposed possible conversion mechanisms and categorized the general strategies to adjust of the structure and composition for CO₂ RR, such as tip effect, defect engineering, crystal plane catalysis, synergistic effect, nanoconfinement effect and so on. Eventually, we provided a prospect of the future challenges for further development and progress in CO₂ RR. Previous reviews have summarized catalyst designs for the reduction of CO₂ to multi-carbon products, while lacking in targeting C₂ H₄ alone, an important industrial feedstock. This Review mainly aims to provide a comprehensive understanding for the design strategies and challenges of electrocatalytic CO₂ reduction to C₂ H₄ through recent researches and further propose some guidelines for the future design of copper-based catalysts for electroreduction of CO₂ to C₂ H₄ .

Recent advances in understanding and design of efficient hydrogen evolution electrocatalysts for water splitting: A comprehensive review

An unsustainable reliance on fossil fuels is the primary cause of the vast majority of greenhouse gas emissions, which in turn lead to climate change. Green hydrogen (H₂), which may be generated by electrolyzing water with renewable power sources, is a possible substitute for fossil fuels. On the other hand, the increasing intricacy of hydrogen evolution electrocatalysts that are presently being explored makes it more challenging to integrate catalytic theories, catalytic fabrication procedures, and characterization techniques. This review will initially present the thermodynamics, kinetics, and associated electrical and structural characteristics for HER electrocatalysts before highlighting design approaches for the electrocatalysts. Secondly, an in-depth discussion regarding the rational design, synthesis, mechanistic insight, and performance improvement of electrocatalysts is centered on both the intrinsic and extrinsic influences. Thirdly, the most recent technological advances in electrocatalytic water-splitting approaches are described. Finally, the difficulties and possibilities associated with generating extremely effective HER electrocatalysts for water-splitting applications are discussed.

Surface and Interface Coordination Chemistry Learned from Model Heterogeneous Metal Nanocatalysts: From Atomically Dispersed Catalysts to Atomically Precise Clusters

The surface and interface coordination structures of heterogeneous metal catalysts are crucial to their catalytic performance. However, the complicated surface and interface structures of heterogeneous catalysts make it challenging to identify the molecular-level structure of their active sites and thus precisely control their performance. To address this challenge, atomically dispersed metal catalysts (ADMCs) and ligand-protected atomically precise metal clusters (APMCs) have been emerging as two important classes of model heterogeneous catalysts in recent years, helping to build bridge between homogeneous and heterogeneous catalysis. This review illustrates how the surface and interface coordination chemistry of these two types of model catalysts determines the catalytic performance from multiple dimensions. The section of ADMCs starts with the local coordination structure of metal sites at the metal-support interface, and then focuses on the effects of coordinating atoms, including their basicity and hardness/softness. Studies are also summarized to discuss the cooperativity achieved by dual metal sites and remote effects. In the section of APMCs, the roles of surface ligands and supports in determining the catalytic activity, selectivity, and stability of APMCs are illustrated. Finally, some personal perspectives on the further development of surface coordination and interface chemistry for model heterogeneous metal catalysts are presented.

Optimal Icosahedral Copper-Based Bimetallic Clusters for the Selective Electrocatalytic CO2 Conversion to One Carbon Products

Electrochemical CO2 reduction reactions can lead to high value-added chemical and materials production while helping decrease anthropogenic CO2 emissions. Copper metal clusters can reduce CO2 to more than thirty different hydrocarbons and oxygenates yet they lack the required selectivity. We present a computational characterization of the role of nano-structuring and alloying in Cu-based catalysts on the activity and selectivity of CO2 reduction to generate the following one-carbon products: carbon monoxide (CO), formic acid (HCOOH), formaldehyde (H2C=O), methanol (CH3OH) and methane (CH4). The structures and energetics were determined for the adsorption, activation, and conversion of CO2 on monometallic and bimetallic (decorated and core@shell) 55-atom Cu-based clusters. The dopant metals considered were Ag, Cd, Pd, Pt, and Zn, located at different coordination sites. The relative binding strength of the intermediates were used to identify the optimal catalyst for the selective CO2 conversion to one-carbon products. It was discovered that single atom Cd or Zn doping is optimal for the conversion of CO2 to CO. The core@shell models with Ag, Pd and Pt provided higher selectivity for formic acid and formaldehyde. The Cu-Pt and Cu-Pd showed lowest overpotential for methane formation.

Density Functional Study of Size-Dependent Hydrogen Adsorption on Ag n Cr (n = 1-12) Clusters

Increasing interest has been paid for hydrogen adsorption on atomically controlled nanoalloys due to their potential applications in catalytic processes and energy storage. In this work, we investigate the interaction of H₂ with small-sized Ag _n Cr (n = 1-12) using density functional theory calculations. It is found that the cluster structures are preserved during the adsorption of H₂ either molecularly or dissociatively. Ag₃Cr-H₂, Ag₆Cr-H₂, and Ag₉Cr-H₂ clusters are identified to be relatively more stable from computed binding energies and second-order energy difference. The dissociation of adsorbed H₂ on Ag₂Cr, Ag₃Cr, Ag₆Cr, and Ag₇Cr clusters is favored both thermodynamically and kinetically. The dissociative adsorption is unlikely to occur because of a considerable energy barrier before reaching the final state for Ag₄Cr or due to energetic preferences for n = 1, 5, and 8-12 species. Comprehensive analysis shows that the geometric structure of clusters, the relative electronegativity, and the coordination number of the Cr impurity play a decisive role in determining the preferred adsorption configuration.

Self-Strained Platinum Clusters with Finite Size: High-Performance Catalysts with CO Tolerance for PEMFCs

Strained platinum-based materials with high performance have been regarded as the most promising electrocatalysts for proton exchange membrane fuel cells (PEMFCs) recently. Herein, self-strained platinum clusters with finite size (about 1 nm) are prepared by a combining liquid- and solid-phase UV irradiation cycle strategy. It started with a fresh H₂PtCl₆ solution irradiated by UV light and then mixed with a graphitized carbon, followed by the dried mixture being subjected to UV light to generate monodispersed Pt clusters on the carbon surface. The obtained platinum clusters feature narrower size distribution and higher loading on carbon, exhibiting significantly improved activity and durability, much higher than that of the-state-of-art commercial Pt/C for the oxygen reduction reaction. More importantly, the self-strained Pt clusters display a surprising CO tolerance, which can be attributed to the unique adaptive lattice compressive strain that triggers an electron enrichment phenomenon for the Pt clusters. Therefore, this stepwise UV irradiation method solves the long-standing problem of both wide size distribution and low loading of metal clusters fabricated by one-step photochemical reduction, providing a potential route for the synthesis of other metal clusters with strained structures.

Ultrasmall Ruthenium Nanoparticles with Boosted Antioxidant Activity Upregulate Regulatory T Cells for Highly Efficient Liver Injury Therapy

Nanozymes exhibiting antioxidant activity are beneficial for the treatment of oxidative stress-associated diseases. Ruthenium nanoparticles (RuNPs) with multiple enzyme-like activities have attracted growing attention, but the relatively low antioxidant enzyme-like activities hinder their practical biomedical applications. Here, a size regulation strategy is presented to significantly boost the antioxidant enzyme-like activities of RuNPs. It is found that as the size of RuNPs decreases to ≈2.0 nm (sRuNP), the surface-oxidized Ru atoms become dominant, thus possessing an unprecedentedly boosted antioxidant activity as compared to medium-sized (≈3.9 nm) or large-sized counterparts (≈5.9 nm) that are mainly composed of surface metallic Ru atoms. Notably, based on their antioxidant enzyme-like activities and ultrasmall size, sRuNP can not only sustainably ameliorate oxidative stress but also upregulate regulatory T cells in late-stage acetaminophen (APAP)-induced liver injury (ALI). Consequently, sRuNPs perform highly efficient therapeutic efficiency on ALI mice even when treated at 6 h after APAP intoxication. This strategy is insightful for tuning the catalytic performances of nanozymes for their extensive biomedical applications.

Synergistic Effects in the Activity of Nano-Transition-Metal Clusters Pt12M (M = Ir, Ru or Rh) for NO Dissociation

The dissociation of environmentally hazardous NO through dissociative adsorption on metallic clusters supported by oxides, is receiving growing attention. Building on previous research on monometallic M 13  clusters [J. Phys. Chem. C, 2019, 123(33), 20314-20318], this work considers bimetallic Pt 12 M (M = Rh, Ru or Ir) clusters. The adsorption energy and activation energy of NO dissociation on the clusters have been calculated in vacuum using Koh,-Sham DFT, while their trends were rationalized using reactivity indices such as molecular electrostatic potential and global Fermi softness. The results shown that doping of the Pt clusters lowered the adsorption energy as well as the activation energy for NO dissociation. Furthermore, reactivity indices were calculated as a first estimate of the performance of the clusters in realistic amorphous silica pores (MCM-41) through  ab initio  molecular dynamics simulations.

Toward size-dependent thermodynamics of nanoparticles from quantum chemical calculations of small atomic clusters: a case study of (B2O3)n

We present a method for obtaining canonical partition functions and, accordingly, temperature-dependent thermodynamics of arbitrary-sized (nano) particles from electronic structure calculations of the corresponding small size atomic clusters. The guiding idea here is to extrapolate the basic properties underlying the thermochemistry of clusters (electronic energies, rotational constants, and vibrational frequencies) rather than the thermodynamic functions themselves. The thus obtained scaling dependences for these basic properties expressed in a simple analytical form provide an efficient tool for fast evaluation of the size-selected thermochemical data for particles of any nuclearity. To exemplify the performance of the methodology, neutral stoichiometric boron oxide clusters are considered. To this end, the geometry and various physical properties of the energetically lowest-lying (B₂O₃)_n (n = 1,…,8) structures are found using density functional theory and the authors' multistage hierarchical procedure customized for global optimization of quite large cluster structures. With these data and based on the physically consistent scaling regularities for the principal cluster properties, the size-selected thermodynamic functions of boron oxide particles in the gas phase, such as enthalpy, entropy, and specific heat capacity, are derived. The variation of these characteristics with increasing cluster size is discussed in detail as well. To facilitate handling of the temperature and size dependences we have found here in further chemical kinetic and equilibrium modeling, the tabulated thermodynamic functions of interest are fitted for n = 1,…,1000 to the standard seven-parameter Chemkin polynomials.

Grain Boundary—A Route to Enhance Electrocatalytic Activity for Hydrogen Evolution Reaction

The electrocatalytic hydrogen evolution reaction (HER) of a given metal catalyst is intrinsically related to its electronic structure, which is difficult to alter for further improvement. Recently, it was discovered that the density of grain boundaries (GBs) is mechanistically of great importance for catalytic activity, implying that GBs are quantitatively correlated with the active sites in the HER. Here, by modeling the atomistic structure of GBs on a Au(110) surface, we find that HER performance is greatly enhanced by Au GBs, suggesting the feasibility of the HER mediated by GBs. The promoted HER performance is due to an increase in the capability of binding adsorbed hydrogen on the sites around GBs. A Au catalyst with a dominantly exposed (110) plane is synthesized, where considerable GBs exist for experimental verification. It is found that HER activity is inherently correlated with the density of the GBs in Au NPs. The improvement in HER activity can be elucidated from the geometrical and electronic points of view; the broken local spatial symmetry near a GB causes a decrease in the coordination numbers of the surface sites and the shift up of the d–band center, thereby reducing the limiting potential for each proton−electron transfer step. Our finding represents a promising means to further improve the HER activity of a catalyst.

Comparison of Vibration-Assisted Scratch Characteristics of SiC Polytypes (3C-, 4H- and 6H-SiC)

Single-crystal silicon carbide (SiC) is widely used because of its excellent properties. However, SiC is a typical hard and brittle material, and there are many challenges in realizing its high efficiency and high-precision machining. Grinding is the main method used to achieve the high-efficiency processing of SiC, but the contradiction between processing quality and processing efficiency is prominent. Vibration-assisted grinding is an effective method to realize high-efficiency and precision machining of SiC. To reveal the vibration-assisted grinding mechanism of SiC, the vibration-assisted nano-scratch process is studied using the molecular dynamics method, and the material removal process and damage formation mechanism in the vibration-assisted scratch are analyzed. Aiming at the three main structural crystal types, 3C-, 4H- and 6H-SiC, scratch simulations were carried out. The vibration-assisted scratch characteristics of SiC polytypes were evaluated from the perspectives of scratch force and the amorphous layer. It was found that the effects of vibration-assisted scratch on different crystal structures of SiC differ, and 3C-SiC is quite different from 4H- and 6H-SiC. Through vibration-assisted scratch simulations under different scratch conditions and vibration characteristics, the influence laws for machining parameters and vibration characteristic parameters were explored. It was found that increasing the frequency and amplitude was beneficial for improving the machining effect. This provides a basis for vibration-assisted grinding technology to be used in the high-efficiency precision machining of SiC.

Applications of Machine Learning in Alloy Catalysts: Rational Selection and Future Development of Descriptors

At present, alloys have broad application prospects in heterogeneous catalysis, due to their various catalytic active sites produced by their vast element combinations and complex geometric structures. However, it is the diverse variables of alloys that lead to the difficulty in understanding the structure-property relationship for conventional experimental and theoretical methods. Fortunately, machine learning methods are helpful to address the issue. Machine learning can not only deal with a large number of data rapidly, but also help establish the physical picture of reactions in multidimensional heterogeneous catalysis. The key challenge in machine learning is the exploration of suitable general descriptors to accurately describe various types of alloy catalysts, which help reasonably design catalysts and efficiently screen candidates. In this review, several kinds of machine learning methods commonly used in the design of alloy catalysts is introduced, and the applications of various reactivity descriptors corresponding to different alloy systems is summarized. Importantly, this work clarifies the existing understanding of physical picture of heterogeneous catalysis, and emphasize the significance of rational selection of universal descriptors. Finally, the development of heterogeneous catalytic descriptors for machine learning are presented.

Size and structure effects on platinum nanocatalysts: theoretical insights from methanol dehydrogenation

Methanol dehydrogenation on Pt nanoparticles was studied as a model reaction with the focus on size and structure effects employing the density functional theory approach. The effect of cluster morphology is manifested by the higher adsorption energy of COH_x intermediates on vertexes and edges of model nanoparticles compared to closely packed terraces. Moreover, due to the size effect, the adsorption sites of Pt₇₉ nanoparticles (1.2 nm in diameter) exhibit considerably higher adsorption activity than the same sites of Pt₂₀₁ (1.7 nm). Thus, particles with a size of about 1 nm are shown to be more active due to the superposition of two effects: (i) a higher surface fraction of low-coordinated adsorption sites and (ii) higher activity of these sites compared to particles with a size of about 2 nm.

Theoretical Study on Carbon Monoxide Adsorption on Unsupported and γ-Al2O3-Supported Silver Nanoparticles: Size, Shape, and Support Effects

Nanoparticles (NPs) supported on metal oxides exhibit high catalytic activities for various reactions. The shape and oxidation state of such NPs, which are related to the catalytic activity, are often determined by the support. Herein, we conducted a density functional theory study on isolated silver (Ag) NPs and two types of Ag-NPs supported on gamma-aluminum oxide (γ-Al₂O₃). First, carbon monoxide (CO) adsorption on the isolated Ag NPs was investigated for decahedra (D _5h ), icosahedra (I _h ), and cuboctahedra (O _h ) of various sizes. I _h and O _h NPs showed moderate size dependence, whereas D _5h NPs showed high size dependence when the height was below 1.4 nm. The enhancement of CO adsorption on D _5h NPs was attributed to the presence of superatomic states. Next, we performed geometrical optimization of Ag₅₄/γ-Al₂O₃(110) with a decahedral shape. Two types of structures were obtained: amorphous Ag₅₄(A) and locally fivefold symmetrical Ag₅₄(B) structures. Both NPs on γ-Al₂O₃(110) were found to be positively charged, but electron transfer to the support occurred only from the Ag atoms at the two bottom layers, and the upper part of NPs was relatively neutral. The enhancement of CO adsorption on Ag₅₄(B) disappeared due to loss of the high symmetry. In turn, the moderate size dependence of neutral isolated NPs can be applied.

Theoretical Investigation of the Size Effect on the Oxygen Adsorption Energy of Coinage Metal Nanoparticles

This study evaluates the finite size effect on the oxygen adsorption energy of coinage metal (Cu, Ag and Au) cuboctahedral nanoparticles in the size range of 13 to 1415 atoms (0.7–3.5 nm in diameter). Trends in particle size effects are well described with single point calculations, in which the metal atoms are frozen in their bulk position and the oxygen atom is added in a location determined from periodic surface calculations. This is shown explicitly for Cu nanoparticles, for which full geometry optimization only leads to a constant offset between relaxed and unrelaxed adsorption energies that is independent of particle size. With increasing cluster size, the adsorption energy converges systematically to the limit of the (211) extended surface. The 55-atomic cluster is an outlier for all of the coinage metals and all three materials show similar behavior with respect to particle size.

Graphic Abstract

The origin of the particle-size-dependent selectivity in 1-butene isomerization and hydrogenation on Pd/Al2O3 catalysts

The selectivity of 1-butene hydrogenation/isomerization on Pd catalysts is known to be particle size dependent. Here we show that combining well-defined model catalysts, atmospheric pressure reaction kinetics, DFT calculations and microkinetic modeling enables to rationalize the particle size effect based on the abundance and the specific properties of the contributing surface facets.

Screening of transition metal doped copper clusters for CO2 activation

Activation of CO₂ is the first step towards its reduction to more useful chemicals. Here we systematically investigate the CO₂ activation mechanism on Cu₃X (X is a first-row transition metal atom) using density functional theory computations. The CO₂ adsorption energies and the activation mechanisms depend strongly on the selected dopant. The dopant electronegativity, the HOMO-LUMO gap and the overlap of the frontier molecular orbitals control the CO₂ dissociation efficiency. Our calculations reveal that early transition metal-doped (Sc, Ti, V) clusters exhibit a high CO₂ adsorption energy, a low activation barrier for its dissociation, and a facile regeneration of the clusters. Thus, early transition metal-doped copper clusters, particularly Cu₃Sc, may be efficient catalysts for the carbon capture and utilization process.

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for example, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3-55 atoms with mean absolute errors in the range of 0.11-0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure-property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal-metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3-55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.

Magical Mathematical Formulas for Nanoboxes

Hollow nanostructures are at the forefront of many scientific endeavors. These consist of nanoboxes, nanocages, nanoframes, and nanotubes. We examine the mathematics of atomic coordination in nanoboxes. Such structures consist of a hollow box with n shells and t outer layers. The magical formulas we derive depend on both n and t. We find that nanoboxes with t = 2  or  3, or walls with only a few layers generally have bulk coordinated atoms. The benefits of low-coordination in nanostructures is shown to only occur when the wall thickness is much thinner than normally synthesized. The case where t = 1 is unique, and has distinct magic formulas. Such low-coordinated nanoboxes are of interest for a myriad variety of applications, including batteries, fuel cells, plasmonic, catalytic and biomedical uses. Given these formulas, it is possible to determine the surface dispersion of the nanoboxes. We expect these formulas to be useful in understanding how the atomic coordination varies with n and t within a nanobox.

Subnanoscale Platinum by Repeated UV Irradiation: From One and Few Atoms to Clusters for the Automotive PEMFC

The unaffordable costs of the automotive proton exchange membrane fuel cell (PEMFC), remaining a roadblock for commercial applications as an alternative to combustion engine vehicles, can be overcome partially by remarkably increasing the utilization of irreplaceable platinum (Pt). Herein, atomically precise Pt with scalable atoms ranging from 1 to 43 atoms, stabilized by a homemade carbon from white radish without any ligands, is prepared by a repeated UV irradiation method that is industrially scalable. Compared with the isolated Pt₁ in the form of Pt-N₄, octahedral Pt₆, and icosahedron Pt₁₃, the ordered Pt₄₃ cluster (∼0.75 nm) with higher metal coordination number displays much higher oxygen reduction reaction performance with a mass activity, which is about 1036% higher than that obtained by state-of-the-art Pt/C, an increase by a factor of ∼3.3 as compared with the DOE 2020 target (0.44 A mg_Pt^-1). The utilization rate of Pt atoms reaches up to 94.7%, much higher than that of Pt (2 nm, 56%), capable of further reducing the amount of platinum that is required for PEMFCs. Moreover, the cluster exhibits an outstanding stability due to the improved Pt vacancy formation energy raised by stronger atom interaction in the close-packed cluster. The cluster exhibits a unique finite size effect from self-tuned energy band and strain levels. A clear strain effect on the d-band center is first presented for pure Pt without distortion from ligands like a second metal. Therefore, the assembly of subnanometer Pt with atom alteration opens up new horizons in designing efficient platinum group metal (PGM) catalysts by reducing the size to subnanometer scale.

Computational Methods in Heterogeneous Catalysis

The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. We finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.

Supported Pt Nanoparticles on Mesoporous Titania for Selective Hydrogenation of Phenylacetylene

Semi-hydrogenation of alkynes to alkenes is one of the most important industrial reactions. However, it remains technically challenging to obtain high alkene selectivity especially at a high alkyne conversion because of kinetically favorable over hydrogenation. In this contribution, we show that supported ultrasmall Pt nanoparticles (2.5 nm) on mesoporous TiO₂ (Pt@mTiO₂) remarkably improve catalytic performance toward semi-hydrogenation of phenylacetylene. Pt@mTiO₂ is prepared by co-assembly of Pt and Ti precursors with silica colloidal templates via an evaporation-induced self-assembly process, followed by further calcination for thermal decomposition of Pt precursors and crystallization of mTiO₂ simultaneously. As-resultant Pt@mTiO₂ discloses a high hydrogenation activity of phenylacetylene, which is 2.5 times higher than that of commercial Pt/C. More interestingly, styrene selectivity over Pt@mTiO₂ remains 100% in a wide phenylacetylene conversion window (20–75%). The styrene selectivity is >80% even at 100% phenylacetylene conversion while that of the commercial Pt/C is 0%. The remarkable styrene selectivity of the Pt@mTiO₂ is derived from the weakened styrene adsorption strength on the atop Pt sites as observed by diffuse reflectance infrared Fourier transform spectroscopy with CO as a probe molecule (CO-DRIFTS). Our strategy provides a new avenue for promoting alkyne to alkene transformation in the kinetically unfavorable region through novel catalyst preparation.

Structure-Dependent Strain Effects

Density functional theory calculations of atomic and molecular adsorption on (111) and (100) metal surfaces reveal marked surface and structure dependent effects of strain. Adsorption in three-fold hollow sites is found to be destabilized by compressive strain whereas the reversed trend is commonly valid for adsorption in four-fold sites. The effects, which are qualitatively explained using a simple two-orbital model, provide insights on how to modify chemical properties by strain design.

Polyhedral Effects on the Mass Activity of Platinum Nanoclusters

We use a coordination-based kinetics model to look at the kinetics of the turnover frequency (TOF) for the oxygen reduction reaction (ORR) for platinum nanoclusters. Clusters of octahedral, cuboctahedral, cubic, and icosahedral shape and size demonstrate the validity of the coordination-based approach. The Gibbs adsorption energy is computed using an empirical energy model based on density functional theory (DFT), statistical mechanics, and thermodynamics. We calculate the coordination and size dependence of the Gibbs adsorption energy and apply it to the analysis of the TOF. The platinum ORR follows a Langmuir–Hinshelwood mechanism, and we model the kinetics using a thermodynamic approach. Our modeling indicates that the coordination, shape, and the Gibbs energy of adsorption all are important factors in replicating an experimental TOF. We investigate the effects of size and shape of some platinum polyhedra on the oxygen reduction reaction (ORR) and the effect on the mass activity. The data are modeled quantitatively using lognormal distributions. We provide guidance on how to account for the effects of different distributions due to shape when determining the TOF.