Understanding the atomic-level process of CO-adsorption-driven surface segregation of Pd in (AuPd)147 bimetallic nanoparticles

Precise solid-phase synthesis of CoFe@FeOx nanoparticles for efficient polysulfide regulation in lithium/sodium-sulfur batteries

Complex metal nanoparticles distributed uniformly on supports demonstrate distinctive physicochemical properties and thus attract a wide attention for applications. The commonly used wet chemistry methods display limitations to achieve the nanoparticle structure design and uniform dispersion simultaneously. Solid-phase synthesis serves as an interesting strategy which can achieve the fabrication of complex metal nanoparticles on supports. Herein, the solid-phase synthesis strategy is developed to precisely synthesize uniformly distributed CoFe@FeOx core@shell nanoparticles. Fe atoms are preferentially exsolved from CoFe alloy bulk to the surface and then be carburized into a FexC shell under thermal syngas atmosphere, subsequently the formed FexC shell is passivated by air, obtaining CoFe@FeOx with a CoFe alloy core and a FeOx shell. This strategy is universal for the synthesis of MFe@FeOx (M = Co, Ni, Mn). The CoFe@FeOx exhibits bifunctional effect on regulating polysulfides as the separator coating layer for Li-S and Na-S batteries. This method could be developed into solid-phase synthetic systems to construct well distributed complex metal nanoparticles.

Bimetallic Sites for Catalysis: From Binuclear Metal Sites to Bimetallic Nanoclusters and Nanoparticles

Heterogeneous bimetallic catalysts have broad applications in industrial processes, but achieving a fundamental understanding on the nature of the active sites in bimetallic catalysts at the atomic and molecular level is very challenging due to the structural complexity of the bimetallic catalysts. Comparing the structural features and the catalytic performances of different bimetallic entities will favor the formation of a unified understanding of the structure-reactivity relationships in heterogeneous bimetallic catalysts and thereby facilitate the upgrading of the current bimetallic catalysts. In this review, we will discuss the geometric and electronic structures of three representative types of bimetallic catalysts (bimetallic binuclear sites, bimetallic nanoclusters, and nanoparticles) and then summarize the synthesis methodologies and characterization techniques for different bimetallic entities, with emphasis on the recent progress made in the past decade. The catalytic applications of supported bimetallic binuclear sites, bimetallic nanoclusters, and nanoparticles for a series of important reactions are discussed. Finally, we will discuss the future research directions of catalysis based on supported bimetallic catalysts and, more generally, the prospective developments of heterogeneous catalysis in both fundamental research and practical applications.

Dynamical Study of Adsorbate-Induced Restructuring Kinetics in Bimetallic Catalysts Using the PdAu(111) Model System

Dynamic restructuring of bimetallic catalysts plays a crucial role in their catalytic activity and selectivity. In particular, catalyst pretreatment with species such as carbon monoxide and oxygen has been shown to be an effective strategy for tuning the surface composition and morphology. Mechanistic and kinetic understanding of such restructuring is fundamental to the chemistry and engineering of surface active sites but has remained challenging due to the large structural, chemical, and temporal degrees of freedom. Here, we combine time-resolved temperature-programmed infrared reflection absorption spectroscopy, ab initio thermodynamics, and machine-learning molecular dynamics to uncover previously unidentified timescale and kinetic parameters of in situ restructuring in Pd/Au(111), a highly relevant model system for dilute Pd-in-Au nanoparticle catalysts. The key innovation lies in utilizing CO not only as a chemically sensitive probe of surface Pd but also as an agent that induces restructuring of the surface. Upon annealing in vacuum, as-deposited Pd islands became encapsulated by Au and partially dissolved into the subsurface, leaving behind isolated Pd monomers on the surface. Subsequent exposure to 0.1 mbar CO enabled Pd monomers to repopulate the surface up to 373 K, above which complete Pd dissolution occurred by 473 K, with apparent activation energies of 0.14 and 0.48 eV, respectively. These restructuring processes occurred over the span of ∼1000 s at a given temperature. Such a minute-timescale dynamics not only elucidates the fluxional nature of alloy catalysts but also presents an opportunity to fine-tune the surface under moderate temperature and pressure conditions.

Decoding reactive structures in dilute alloy catalysts

Rational catalyst design is crucial toward achieving more energy-efficient and sustainable catalytic processes. Understanding and modeling catalytic reaction pathways and kinetics require atomic level knowledge of the active sites. These structures often change dynamically during reactions and are difficult to decipher. A prototypical example is the hydrogen-deuterium exchange reaction catalyzed by dilute Pd-in-Au alloy nanoparticles. From a combination of catalytic activity measurements, machine learning-enabled spectroscopic analysis, and first-principles based kinetic modeling, we demonstrate that the active species are surface Pd ensembles containing only a few (from 1 to 3) Pd atoms. These species simultaneously explain the observed X-ray spectra and equate the experimental and theoretical values of the apparent activation energy. Remarkably, we find that the catalytic activity can be tuned on demand by controlling the size of the Pd ensembles through catalyst pretreatment. Our data-driven multimodal approach enables decoding of reactive structures in complex and dynamic alloy catalysts.

Rational catalyst design is crucial toward achieving more energy-efficient and sustainable catalytic processes. Here the authors report a data-driven approach for understanding catalytic reactions mechanisms in dilute bimetallic catalysts by combining X-ray absorption spectroscopy with activity studies and kinetic modeling.

Predicting Segregation Energy in Single Atom Alloys Using Physics and Machine Learning

Single atom alloys (SAAs) show great promise as catalysts for a wide variety of reactions due to their tunable properties, which can enhance the catalytic activity and selectivity. To design SAAs, it is imperative for the heterometal dopant to be stable on the surface as an active catalytic site. One main approach to probe SAA stability is to calculate surface segregation energy. Density functional theory (DFT) can be applied to investigate the surface segregation energy in SAAs. However, DFT is computationally expensive and time-consuming; hence, there is a need for accelerated frameworks to screen metal segregation for new SAA catalysts across combinations of metal hosts and dopants. To this end, we developed a model that predicts surface segregation energy using machine learning for a series of SAA periodic slabs. The model leverages elemental descriptors and features inspired by the previously developed bond-centric model. The initial model accurately captures surface segregation energy across a diverse series of FCC-based SAAs with various surface facets and metal-host pairs. Following our machine learning methodology, we expanded our analysis to develop a new model for SAAs formed from FCC hosts with FCC, BCC, and HCP dopants. Our final, five-feature model utilizes second-order polynomial kernel ridge regression. The model is able to predict segregation energies with a high degree of accuracy, which is due to its physically motivated features. We then expanded our data set to test the accuracy of the five features used. We find that the retrained model can accurately capture E _seg trends across different metal hosts and facets, confirming the significance of the features used in our final model. Finally, we apply our pretrained model to a series of Ir- and Pd-based SAA cuboctahedron nanoparticles (NPs), ranging in size and FCC dopants. Remarkably, our model (trained on periodic slabs) accurately predicts the DFT segregation energies of the SAA NPs. The results provide further evidence supporting the use of our model as a general tool for the rapid prediction of SAA segregation energies. By creating a framework to predict the metal segregation from bulk surfaces to NPs, we can accelerate the SAA catalyst design while simultaneously unraveling key physicochemical properties driving thermodynamic stabilization of SAAs.

Tuning Catalytic Activity in Ultrathin Bimetallic Nanowires via Surface Segregation: Some Insights

The efficiency of heterogeneous catalysts critically depends on the nature of the surface. We present results on controlling the composition in ultrathin bimetallic AuPd. AuPd wires were grown using Au nanowire templates; the surface composition could be tuned by increasing the amount of Pd. Further, segregation of Pd to the surface could be induced in alloyed nanowires by annealing under a controlled CO atmosphere. Electrocatalytic activity of these bimetallic systems is assessed for the methanol oxidation reaction (MOR). While the MOR potential shows a monotonic increase with Pd content, the specific activity displays a typical volcano-type behavior. The CO-annealed nanowires show a lowering of potential owing to a higher Pd content on the surface while still maintaining the specific activity. These findings provide clear strategies to independently control the reaction potential and the activities of nanocatalysts. The experimental findings are well supported by the theoretical investigations using density functional theory (DFT) calculations.

Directing reaction pathways via in situ control of active site geometries in PdAu single-atom alloy catalysts

The atomic scale structure of the active sites in heterogeneous catalysts is central to their reactivity and selectivity. Therefore, understanding active site stability and evolution under different reaction conditions is key to the design of efficient and robust catalysts. Herein we describe theoretical calculations which predict that carbon monoxide can be used to stabilize different active site geometries in bimetallic alloys and then demonstrate experimentally that the same PdAu bimetallic catalyst can be transitioned between a single-atom alloy and a Pd cluster phase. Each state of the catalyst exhibits distinct selectivity for the dehydrogenation of ethanol reaction with the single-atom alloy phase exhibiting high selectivity to acetaldehyde and hydrogen versus a range of products from Pd clusters. First-principles based Monte Carlo calculations explain the origin of this active site ensemble size tuning effect, and this work serves as a demonstration of what should be a general phenomenon that enables in situ control over catalyst selectivity.

Self-driven microstructural evolution of Au@Pd core-shell nanoparticles for greatly enhanced catalytic performance during methanol electrooxidation

The lack of direct insight into the microstructural evolution of catalytic materials under electrochemical polarization has inhibited the development of heterogeneous catalysts. By investigating a typical Au@Pd core-shell nanostructure, the present study discloses the microstructural evolution of heterogeneous catalytic materials during the methanol electrooxidation reaction (MOR). The electrocatalytic activity of the as-prepared Au@Pd_core-shell nanoparticles continuously increased during the first 100 successive voltammetry cycles of the MOR. Microstructural characterization studies revealed that during the MOR, an Au/Pd mixed bimetallic shell was formed by the self-driven microstructural evolution of the Au@Pd_core-shell nanoparticles. Both the experimental and calculation results indicated that the Au/Pd mixed bimetallic shell reduced the binding strength of OH^- and CO on the catalyst surface. The exposed Au atoms in the shell region also produced large-scale reactive ˙OH radicals that facilitated the oxidative removal of the adsorbed carbonaceous species from the adjacent Pd active sites.

Dynamic vs static behaviour of a supported nanoparticle with reaction-induced catalytic sites in a lattice model

Modern literature shows a rapidly growing interest to the supported nanocatalysts with dynamic behaviour under reaction conditions. This new frontier of heterogeneous catalysis is recognized as one of the most challenging and worthy of consideration from all possible angles. In this context, a previously suggested lattice model is used to get an insight, by means of kinetic Monte Carlo, into the influence of the mobility of reaction-induced catalytic sites of a two-dimensional supported nanoparticle on the system behaviour. The results speak in favour of feasibility of dynamic nanocatalysts with self-organized structures capable of robust functioning. This approach, from the macroscopic end, is believed to be a useful complement to ever developing experimental and first principle approaches.

In situ observations of the structural dynamics of platinum-cobalt-hydroxide nanocatalysts under CO oxidation

The structures, compositions and chemical states of metal catalysts are prone to dynamic changes in response to reaction conditions. In this work, a combination of in situ X-ray absorption fine structure spectroscopy and diffuse reflectance infrared Fourier transform spectroscopy has been used to monitor the temperature-dependent structural dynamics in bimetallic Pt-Co(OH)₂ nanocatalysts during CO oxidation. Alloying with electron-donating Co promotes the catalytic activity of metallic Pt for CO oxidation at low temperature. At elevated temperatures under an oxidation atmosphere, O₂ drives the segregation of the Pt-Co alloy into cobalt oxide and platinum metal, with the extent of alloying sharply decreasing from ∼30% at 300 K to 0 at 473 K. Reduction at high temperature could recover the formation of the Pt-Co alloy with the same alloying extent. The observed structural dynamics could be well correlated with the kinetic behavior of the catalysts. This work highlights the importance of tracking the dynamic structural changes of working catalysts for a correct understanding of their catalytic behavior.

Compositional effect of two-dimensional monodisperse AuPd bimetallic nanoparticle arrays fabricated by block copolymer nanopatterning on catalytic activity of CO oxidation

We present a straightforward approach for fabricating AuPd nanocatalysts based on self-assembled block copolymer nanopatterning. CO oxidation was carried out on AuPd alloy nanoparticles and the activity increased with increasing Pd content; this synergistic activity can be precisely tuned by varying the chemical composition. Theoretical calculations suggest that Pd clusters are required to bind and dissociate O2 for oxidation of coadsorbed CO molecules. Our results suggest that the geometric configuration of the Pd atoms on the surface are a key factor in the catalytic activity.