Predicting Adsorption Properties of Catalytic Descriptors on Bimetallic Nanoalloys with Site-Specific Precision

Bimetallic nanoparticles present a vastly tunable structural and compositional design space rendering them promising materials for catalytic and energy applications. Yet it remains an enduring challenge to efficiently screen candidate alloys with atomic level specificity while explicitly accounting for their inherent stabilities under reaction conditions. Herein, by leveraging correlations between binding energies of metal adsorption sites and metal–adsorbate complexes, we predict adsorption energies of typical catalytic descriptors (OH*, CH3*, CH*, and CO*) on bimetallic alloys with site-specific resolution. We demonstrate that our approach predicts adsorption energies on top and bridge sites of bimetallic nanoparticles having generic morphologies and chemical environments with errors between 0.09 and 0.18 eV. By forging a link between the inherent stability of an alloy and the adsorption properties of catalytic descriptors, we can now identify active site motifs in nanoalloys that possess targeted catalytic descriptor values while being thermodynamically stable under working conditions

Microkinetic Modeling of Propene Combustion on a Stepped, Metallic Palladium Surface and the Importance of Oxygen Coverage

Better emission control of internal combustion engines can be achieved by more efficient catalytic hydrocarbon combustion at low temperatures. For a knowledge-based design of suitable catalyst candidates, a promising approach integrates theoretical models with experimental benchmarks. Studying catalytic hydrocarbon combustion theoretically is challenging, however, since hydrocarbon reaction networks are complex: even simple C2 combustion reactions include hundreds of possible elementary steps. Herein, we present a paradigm to address this challenge by (1) supplementing experimental insights with extensive density functional theory studies to derive a proxy combustion reaction network; (2) using machine learning-enhanced transition state search to rigorously scan reaction coordinates; and (3) combining ab initio thermodynamics, microkinetic modeling, and a degree of rate control analysis to unveil adsorbate coverage effects and rate-limiting reaction steps. Our systematic approach permits modeling a reaction as complex as propene combustion on palladium while maintaining the computationally efficient mean-field approximation. Using a partially oxygen-covered palladium surface model, which includes adsorbate–adsorbate interactions, we predict experimentally measured rates within 2 orders of magnitude without parameter fitting. The corresponding degree of rate control analysis yields that the second and penultimate dehydrogenation step in the reaction network limit the rate of propene combustion on palladium

Microkinetic Modeling of Propene Combustion on a Stepped, Metallic Palladium Surface and the Importance of Oxygen Coverage

Better emission control of internal combustion engines can be achieved by more efficient catalytic hydrocarbon combustion at low temperatures. For a knowledge-based design of suitable catalyst candidates, a promising approach integrates theoretical models with experimental benchmarks. Studying catalytic hydrocarbon combustion theoretically is challenging, however, since hydrocarbon reaction networks are complex: even simple C2 combustion reactions include hundreds of possible elementary steps. Herein, we present a paradigm to address this challenge by (1) supplementing experimental insights with extensive density functional theory studies to derive a proxy combustion reaction network; (2) using machine learning-enhanced transition state search to rigorously scan reaction coordinates; and (3) combining ab initio thermodynamics, microkinetic modeling, and a degree of rate control analysis to unveil adsorbate coverage effects and rate-limiting reaction steps. Our systematic approach permits modeling a reaction as complex as propene combustion on palladium while maintaining the computationally efficient mean-field approximation. Using a partially oxygen-covered palladium surface model, which includes adsorbate–adsorbate interactions, we predict experimentally measured rates within 2 orders of magnitude without parameter fitting. The corresponding degree of rate control analysis yields that the second and penultimate dehydrogenation step in the reaction network limit the rate of propene combustion on palladium

Tuning the Work Function of MXene via Surface Functionalization

MXenes, a class of two-dimensional materials, have garnered significant attention due to their versatile surface chemistry and customizable properties. In this study, we investigate the work function (WF) tuning capabilities of MXene Ti3C2Tx, where Tx denotes the surface termination, synthesized via both conventional hydrogen fluoride-etched and recently reported molten salt-etched routes. When MXene samples are subjected to gas phase reactions, WF variations exceeding 0.6 eV are achieved, highlighting the potential for precise WF control. Notably, the WF increases from ∼4.23 eV (in N-doped MXene etched using molten salt) to ∼4.85 eV (N-doped MXene etched using HF). Complementary density functional theory (DFT) calculations reveal WF tuning across a >1 eV range via modification of the surface with different terminal groups (bare metal, F*, O*, N*, and Cl*). These changes in WF are attributed to surface termination modifications and the formation of TiO2 and TiN phases during annealing. DFT calculations further unveil an inverse correlation between the WF and the electron affinity of surface terminations. The findings from this comprehensive study provide insights into the tunable WF of MXenes, paving the way for their potential applications as interfacial layers in photovoltaic, energy conversion, and storage technologies

Revealing the Synergy between Oxide and Alloy Phases on the Performance of Bimetallic In–Pd Catalysts for CO₂ Hydrogenation to Methanol

In2O3 has recently emerged as a promising catalyst for methanol synthesis from CO2. In this work, we present the promotional effect of Pd on this catalyst and investigate structure–performance relationships using in situ X-ray spectroscopy, ex situ characterization, and microkinetic modeling. Catalysts were synthesized with varying In:Pd ratios (1:0, 2:1, 1:1, 1:2, 0:1) and tested for methanol synthesis from CO2/H2 at 40 bar and 300 °C. In:Pd(2:1)/SiO2 shows the highest activity (5.1 μmol MeOH/gInPds) and selectivity toward methanol (61%). While all bimetallic catalysts had enhanced catalytic performance, characterization reveals methanol synthesis was maximized when the catalyst contained both In–Pd intermetallic compounds and an indium oxide phase. Experimental results and density functional theory suggest the active phase arises from a synergy between the indium oxide phase and a bimetallic In–Pd particle with a surface enrichment of indium. We show that the promotion observed in the In–Pd system is extendable to non precious metal containing binary systems, in particular In–Ni, which displayed similar composition–activity trends to the In–Pd system. Both palladium and nickel were found to form bimetallic catalysts with enhanced methanol activity and selectivity relative to that of indium oxide

Revealing the Synergy between Oxide and Alloy Phases on the Performance of Bimetallic In–Pd Catalysts for CO₂ Hydrogenation to Methanol

In2O3 has recently emerged as a promising catalyst for methanol synthesis from CO2. In this work, we present the promotional effect of Pd on this catalyst and investigate structure–performance relationships using in situ X-ray spectroscopy, ex situ characterization, and microkinetic modeling. Catalysts were synthesized with varying In:Pd ratios (1:0, 2:1, 1:1, 1:2, 0:1) and tested for methanol synthesis from CO2/H2 at 40 bar and 300 °C. In:Pd(2:1)/SiO2 shows the highest activity (5.1 μmol MeOH/gInPds) and selectivity toward methanol (61%). While all bimetallic catalysts had enhanced catalytic performance, characterization reveals methanol synthesis was maximized when the catalyst contained both In–Pd intermetallic compounds and an indium oxide phase. Experimental results and density functional theory suggest the active phase arises from a synergy between the indium oxide phase and a bimetallic In–Pd particle with a surface enrichment of indium. We show that the promotion observed in the In–Pd system is extendable to non precious metal containing binary systems, in particular In–Ni, which displayed similar composition–activity trends to the In–Pd system. Both palladium and nickel were found to form bimetallic catalysts with enhanced methanol activity and selectivity relative to that of indium oxide

Manipulating Intermediates at the Au–TiO₂ Interface over InP Nanopillar Array for Photoelectrochemical CO₂ Reduction

Photoelectrochemical (PEC) reduction of CO2 with H2O is a promising approach to convert solar energy and greenhouse gas into value-added chemicals or fuels. However, the exact role of structures and interfaces of photoelectrodes in governing the photoelectrocatalytic processes in terms of both activity and selectivity remains elusive. Herein, by systematically investigating the InP photocathodes with Au–TiO2 interfaces, we discover that nanostructuring of InP can not only enhance the photoresponse owing to increased light absorption and prolonged minority carrier lifetime, but also improve selectivity toward CO production by providing more abundant interfacial contact points between Au and TiO2 than planar photocathodes. In addition, theoretical studies on the Au–TiO2 interface demonstrate that the charge transfer between Au and TiO2, which is locally confined to the interface, strengthens the binding of the CO* intermediate on positively charged Au interfacial sites, thus improving CO2 photoelectroreduction to form CO. An optimal Au–TiO2/InP nanopillar-array photocathode exhibits an onset potential of +0.3 V vs reversible hydrogen electrode (RHE) and a Faradaic efficiency of 84.2% for CO production at −0.11 V vs RHE under simulated AM 1.5G illumination at 1 sun. The present findings of the synergistic effects of the structure and interface on the photoresponse and selectivity of a photoelectrode provide insights into the development of III–V semiconductor-based PEC systems for solar fuel generation

Strong Metal–Support Interaction Boosts Activity, Selectivity, and Stability in Electrosynthesis of H₂O₂

Noble metals have an irreplaceable role in catalyzing electrochemical reactions. However, large overpotential and poor long-term stability still prohibit their usage in many reactions (e.g., oxygen evolution/reduction). With regard to the low natural abundance, the improvement of their overall electrocatalytic performance (activity, selectivity, and stability) was urgently necessary. Herein, strong metal–support interaction (SMSI) was modulated through an unprecedented time-dependent mechanical milling method on Pd-loaded oxygenated TiC electrocatalysts. The encapsulation of Pd surfaces with reduced TiO2–x overlayers is precisely controlled by the mechanical milling time. This encapsulation induced a valence band restructuring and lowered the d-band center of surface Pd atoms. For hydrogen peroxide electrosynthesis through the two-electron oxygen reduction reaction (ORR), these electronic and geometric modifications resulted in optimal adsorption energies of reaction intermediates. Thus, SMSI phenomena not only enhanced electrocatalytic activity and selectivity but also created an encapsulating oxide overlayer that protected the Pd species, increasing its long-term stability. This SMSI induced by mechanical milling was also extended to other noble metal systems, showing great promise for the large-scale production of highly stable and tunable electrocatalysts