Effect of MgO(100) support on structure and properties of Pd and Pt nanoparticles with 49-155 atoms

Balancing Activity and Stability through Compositional Engineering of Ternary PtNi-Au Alloy ORR Catalysts

Achieving the optimal balance between cost-efficiency and stability of oxygen reduction reaction (ORR) catalysts is currently among the key research focuses aiming at reaching a broader implementation of proton-exchange membrane fuel cells (PEMFCs). To address this challenge, we combine two well-established strategies to enhance both activity and stability of platinum-based ORR catalysts. Specifically, we prepare ternary PtNi-Au alloys, where each alloying element plays a distinct role: Ni reduces costs and boosts ORR activity, while Au enhances stability. A systematic comparative analysis of the activity-stability relationship for compositionally tuned PtNi-Au model layers, prepared by magnetron co-sputtering, was conducted using a diverse range of complementary characterization techniques and electrochemistry, supported by density functional theory calculations. Our study reveals that a progressive increase of the Au concentration in the Pt50Ni50 alloy from 3 to 15 at % leads to opposing catalyst activity and stability trends. Specifically, we observe a decrease in the ORR activity accompanied by an increase in catalyst stability, manifested in the suppression of both Pt and Ni dissolution. Despite the reduced activity compared to PtNi, the PtNi-Au alloy with 15 at % Au still exhibits nearly three times the activity of monometallic Pt. It also demonstrates a significantly improved dissolution stability relative to that of the PtNi alloy and even monometallic Pt. These findings provide valuable insights into the intricate balance between activity and stability in multimetallic ORR catalysts, paving the way for the design of cost-effective and durable materials for PEMFCs.

High-Temperature Behavior of Pd/MgO Catalysts Prepared via Various Sol-Gel Approaches

A series of Pd/MgO catalysts based on nanocrystalline MgO were prepared via different sol-gel approaches. In the first two cases, palladium was introduced during the gel preparation, followed by drying it in supercritical or ambient conditions. In the third case, aerogel-prepared MgO was impregnated with an ethanol solution of Pd(NO3)2. The prepared catalysts differ in particle size and oxidation state of palladium. The catalytic performance and thermal stability of the samples were examined in a model reaction of CO oxidation at prompt thermal aging conditions. The as-prepared and aged materials were characterized by low-temperature nitrogen adsorption, UV-vis spectroscopy, X-ray photoelectron spectroscopy, transmission electron microscopy, and ethane hydrogenolysis testing reaction. The highest initial activity (T50 = 103 °C) was demonstrated by the impregnated sample, containing Pd0 particles of 3 nm in size. The lowest T50 value (215 °C) after aging at 1000 °C was demonstrated by the impregnated Pd/MgO-WI sample. The high-temperature behavior of the catalysts was found to be affected by the initial oxidation state and dispersion of Pd. Two deactivation mechanisms, such as the agglomeration of Pd particles and migration of small Pd species into the bulk of the MgO support with the formation of Pd-MgO solid solutions, were discussed.

Determining the chemical ordering in nanoalloys by considering atomic coordination types

The energetically most favorable chemical ordering of bimetallic nanoparticles can be characterized by combining global optimization algorithms and surrogate energy models. The latter approximate the energy of nanoalloys relying on structural descriptors, training models, and data. Here, we systematically evaluate the performance of highly data-efficient topological descriptors [Kozlov et al., Chem. Sci. 6, 3868 (2015)] for predicting the energies of metal nanoalloys with different chemical orderings. We also introduce a new descriptor based on atomic coordination types, which results in a less data-efficient and interpretable approach, but improves the general accuracy and the quantification of orderings in the inner parts of nanoparticles. The capacity of both the original and new approaches in combination with a basin hopping algorithm is illustrated by generating convex hulls of PdZn nanoalloys and predicting the resulting active surface site distribution as a function of particle composition. Finally, we show how these approaches can be combined with machine-learning adsorption models in electrocatalysis studies for a fast evaluation of the reactivity landscape of targeted nanoalloys.

Effects of Zr dopants on properties of PtNi nanoparticles for ORR catalysis: A DFT modeling

Pt-based alloys, such as Pt3Ni, are among the best electrocatalysts for oxygen reduction reaction (ORR) in polymer electrolyte membrane fuel cells. Doping of PtNi alloys with Zr was shown to enhance the durability of the operating ORR catalysts. Rationalizing these observations is hindered by the absence of atomic-level data for these tri-metallic materials, even when not exposed to the fuel cell operation conditions. This study aims at understanding structure-property relations in Zr-doped PtNi nanoparticles as a key to their ORR function. In particular, we calculated, using a method based on density functional theory, the most stable chemical orderings of pristine and Zr-doped Pt3Ni particles containing over 400 atoms. We thus clarify (i) preferential location and charge states of Zr atoms in the Pt3Ni NPs; (ii) effect of doping Zr atoms on the stability of the Pt skin of the Pt3Ni NPs; (iii) charge redistribution induced by Zr dopants; (iv) layer-by-layer atomic ordering in the Pt3Ni/Zr NPs with the increasing Zr content; and (v) effect of Zr atoms on the adsorption energies of O and OH species as indicators of the ORR activity.

Phase Segregation in PdCu Alloy Nanoparticles During CO Oxidation Reaction at Atmospheric Pressure

Bimetallic nanoparticle (NP) catalysts are widely used in many heterogeneous gas-based reactions because they often outperform their monometallic counterparts. During these reactions, NPs often undergo structural changes, which impact their catalytic activity. Despite the important role of the structure in the catalytic activity, many aspects of how a reactive gaseous environment affects the structure of bimetallic nanocatalysts are still lacking. Here, using gas-cell transmission electron microscopy (TEM), it is shown that during a CO oxidation reaction over PdCu alloy NPs, the selective oxidation of Cu causes the segregation of Cu and transforms the NPs into Pd-CuO NPs. The segregated NPs are very stable and have high activity for the conversion of CO into CO2 . Based on the observations, the segregation of Cu from Cu-based alloys during a redox reaction is likely to be general and may have a positive impact on the catalytic activity. Hence, it is believed that similar insights based on direct observation of the reactions under relevant reactive conditions are critical both for understanding and designing high-performance catalysts.

Identifying the Structure of Supported Metal Catalysts Using Vibrational Fingerprints from Ab Initio Nanoscale Models

Identifying active sites of supported noble metal nanocatalysts remains challenging, since their size and shape undergo changes depending on the support, temperature, and gas mixture composition. Herein, the anharmonic infrared spectrum of adsorbed CO is simulated using density functional theory (DFT) to gain insight into the nature of Pd nanoparticles (NPs) supported on ceria. The authors systematically determine how the simulated infrared spectra are affected by CO coverage, NP size (0.5-1.5 nm), NP morphology (octahedral, icosahedral), and metal-support contact angle, by exploring a diversity of realistic models inspired by ab initio molecular dynamics. The simulated spectra are then used as a spectroscopic fingerprint to characterize nanoparticles in a real catalyst, by comparison with in-situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) experiments. Truncated octahedral NPs with an acute Pd-ceria angle reproduce most of the measurements. In particular, the authors isolate features characteristic of CO adsorbed at the metal-support interface appearing at low frequencies, both seen in simulation and experiment. This work illustrates the strong need for realistic models to provide a robust description of the active sites, especially at the interface of supported metal nanocatalysts, which can be highly dynamic and evolve considerably during reaction.

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.

Unravelling Morphological and Topological Energy Contributions of Metal Nanoparticles

Metal nanoparticles (NPs) are ubiquitous in many fields, from nanotechnology to heterogeneous catalysis, with properties differing from those of single-crystal surfaces and bulks. A key aspect is the size-dependent evolution of NP properties toward the bulk limit, including the adoption of different NP shapes, which may bias the NP stability based on the NP size. Herein, the stability of different Pd_n NPs (n = 10–1504 atoms) considering a myriad of shapes is investigated by first-principles energy optimisation, leading to the determination that icosahedron shapes are the most stable up to a size of ca. 4 nm. In NPs larger than that size, truncated octahedron shapes become more stable, yet a presence of larger {001} facets than the Wulff construction is forecasted due to their increased stability, compared with (001) single-crystal surfaces, and the lower stability of {111} facets, compared with (111) single-crystal surfaces. The NP cohesive energy breakdown in terms of coordination numbers is found to be an excellent quantitative tool of the stability assessment, with mean absolute errors of solely 0.01 eV·atom⁻¹, while a geometry breakdown allows only for a qualitative stability screening.

AgPd, AuPd, and AuPt Nanoalloys with Ag- or Au-Rich Compositions: Modeling Chemical Ordering and Optical Properties

Bimetallic nanoparticles have a myriad of technological applications, but investigations of their chemical and physical properties are precluded due to their structural complexity. Here, the chemical ordering and optical properties of AgPd, AuPd, and AuPt nanoparticles have been studied computationally. One of the main aims was to clarify whether layered ordered phases similar to L1₁ one observed in the core of AgPt nanoparticles [Pirart J.; Nat. Commun.2019, 10, 1982] are also stabilized in other nanoalloys of coinage metals with platinum-group metals, or the remarkable ordering is a peculiarity only of AgPt nanoparticles. Furthermore, the effects of different chemical orderings and compositions of the nanoalloys on their optical properties have been explored. Particles with a truncated octahedral geometry containing 201 and 405 atoms have been modeled. For each particle, the studied stoichiometries of the Ag- or Au-rich compositions, ca. 4:1 for 201-atomic particles and ca. 3:1 for 405-atomic particles, corresponded to the layered structures L1₁ and L1₀ inside the monatomic coinage-metal skins. Density functional theory (DFT) calculations combined with a recently developed topological (TOP) approach [Kozlov S. M.; Chem. Sci.2015, 6, 3868-3880] have been performed to study the chemical ordering of the particles, whose optical properties have been investigated using the time-dependent DFT method. The obtained results revealed that the remarkable ordering L1₁ of inner atoms can be noticeably favored only in small AgPt particles and much less in AgPd ones, whereas this L1₁ ordering in analogous Au-containing nanoalloys is significantly less stable compared to other calculated lowest-energy orderings. Optical properties were found to be more dependent on the composition (concentration of two metals) than on the chemical ordering. Both Pt and Pd elements promote the quenching of the plasmon.

Pd Single-Atom Sites on the Surface of PdAu Nanoparticles: A DFT-Based Topological Search for Suitable Compositions

Structure of model bimetallic PdAu nanoparticles is analyzed aiming to find Pd:Au ratios optimal for existence of Pd1 single-atom surface sites inside outer Au atomic shell. The analysis is performed using density-functional theory (DFT) calculations and topological approach based on DFT-parameterized topological energy expression. The number of the surface Pd1 sites in the absence of adsorbates is calculated as a function of Pd concentration inside the particles. At low Pd contents none of the Pd atoms emerge on the surface in the lowest-energy chemical orderings. However, surface Pd1 sites become stable, when Pd content inside a Pd-Au particle reaches ca. 60%. Further Pd content increase up to almost pure Pd core is accompanied by increased concentration of surface Pd atoms, mostly as Pd1 sites, although larger Pd ensembles as dimers and linear trimers are formed as well. Analysis of the chemical orderings inside PdAu nanoparticles at different Pd contents revealed that enrichment of the subsurface shell by Pd with predominant occupation of its edge positions precedes emergence of Pd surface species.

Chemical and Laser Ablation Synthesis of Monometallic and Bimetallic Ni-Based Nanoparticles

The catalytic properties of nanoparticles depend on their size, shape and surface/defect structure, with the entire catalyst performance being governed by the corresponding distributions. Herein, we present two routes of mono- and bimetallic nanoparticle synthesis that enable control of the structural parameters, i.e., wet-chemical synthesis and laser ablation in liquid-phase. The latter is particularly suited to create defect-rich nanoparticles. Impregnation routes were applied to prepare Ni and NiCu nanoparticles, whereas nano- and femtosecond laser ablation in liquid-phase were employed to prepare Ni and NiAu nanoparticles. The effects of the Ni:Cu ratio in impregnation and of laser fluence and liquid-medium on laser ablation are discussed. The atomic structure and (surface) composition of the nanoparticles were characterized by electron microscopic (BF-TEM, DF-TEM, HRTEM) and spectroscopic/diffraction techniques (EDX, SAED, XPS, IR), complemented by theory (DFT). The chemically synthesized bimetallic NiCu nanoparticles initially had Cu-rich surfaces, which changed to Ni-rich upon reaction. For laser ablation, depending on conditions (fluence, type of liquid), highly defective, ordered, or core/shell-like nanoparticles were produced. The case studies highlight the specific benefits of each preparation method for catalyst synthesis and discuss the potential of nanoparticles produced by pulsed laser ablation for catalytic applications.

The effect of SnO2(110) supports on the geometrical and electronic properties of platinum nanoparticles

Abstract

While Pt-nanoparticles supported on SnO2 exhibit improved durability, a substantial detriment is observed on the Pt-nanoparticles’ activity toward the oxygen reduction reaction. A density functional theory method is used to calculate isolated, SnO2- and graphene-supported Pt-nanoparticles. Work function difference between the Pt-nanoparticles and SnO2 leads to electron donation from the nanoparticles to the support, making the outer-shell atoms of the supported nanoparticles more positively charged compared to unsupported nanoparticles. From an electrostatic point of view, nucleophilic species tend to interact more stably with less negatively charged Pt atoms blocking the active sites for the reaction to occur, which can explain the low activity of Pt-nanoparticles supported on SnO2. Introducing oxygen vacancies and Nb dopants on SnO2 decreases the support work function, which not only reduces the charge transferred from the Pt-nanoparticles to the support but also reverses the direction of the electrons flow making the surface Pt atoms more negatively charged. A similar effect is observed when using graphene, which has a lower work function than Pt. Thus, the blocking of the active sites by nucleophilic species decreases, hence increasing the activity. These results provide a clue to improve the activity by modifying the support work function and by selecting a support material with an appropriate work function to control the charge of the nanoparticle’s surface atoms.

Graphic abstract

Towards operando computational modeling in heterogeneous catalysis

An increased synergy between experimental and theoretical investigations in heterogeneous catalysis has become apparent during the last decade. Experimental work has extended from ultra-high vacuum and low temperature towards operando conditions. These developments have motivated the computational community to move from standard descriptive computational models, based on inspection of the potential energy surface at 0 K and low reactant concentrations (0 K/UHV model), to more realistic conditions. The transition from 0 K/UHV to operando models has been backed by significant developments in computer hardware and software over the past few decades. New methodological developments, designed to overcome part of the gap between 0 K/UHV and operando conditions, include (i) global optimization techniques, (ii) ab initio constrained thermodynamics, (iii) biased molecular dynamics, (iv) microkinetic models of reaction networks and (v) machine learning approaches. The importance of the transition is highlighted by discussing how the molecular level picture of catalytic sites and the associated reaction mechanisms changes when the chemical environment, pressure and temperature effects are correctly accounted for in molecular simulations. It is the purpose of this review to discuss each method on an equal footing, and to draw connections between methods, particularly where they may be applied in combination.

How to determine accurate chemical ordering in several nanometer large bimetallic crystallites from electronic structure calculations

The proposed method allows to efficiently determine the atomic arrangement in bimetallic nanoparticles based on electronic structure calculations and unravels the relationship between structural preferences of atoms and binding in nanoalloys.

Chemical and physical properties of binary metallic nanoparticles (nanoalloys) are to a great extent defined by their chemical ordering, i.e. the pattern in which atoms of the two elements are located in a given crystal lattice. The reliable determination of the lowest-energy chemical ordering is a challenge that impedes in-depth studies of several-nm large bimetallic particles. We propose a method to efficiently optimize the chemical ordering based solely on results of electronic structure (density functional) calculations. We show that the accuracy of this method is practically the same as the accuracy of the underlying quantum mechanical approach. This method, due to its simplicity, immediately reveals why one or another chemical ordering is preferred and unravels the nature of the binding within the nanoparticles. For instance, our results provide very intuitive understanding of why gold and silver segregate on low-coordinated sites in Pd₇₀Au₇₀ and Pd₇₀Ag₇₀ particles, while Pd₇₀Cu₇₀ exhibits matryoshka-like structure and Pd₇₀Zn₇₀ features Zn and Pd atoms arranged in layers. To illustrate the power of the new method we optimized the chemical ordering in much larger Pd₇₃₂Au₇₃₁, Pd₇₃₂Ag₇₃₁, Pd₇₃₂Cu₇₃₁, and Pd₇₃₂Zn₇₃₁ nanocrystals, whose size ∼4.4 nm is common for catalytic applications.

Revealing chemical ordering in Pt–Co nanoparticles using electronic structure calculations and X-ray photoelectron spectroscopy

Pt_YCo_1−Y-core@Co-rich-subsurface@Pt-shell structure is identified in several nm large Pt–Co particles using X-ray photoelectron spectroscopy and an optimization method based on density-functional calculations.

High sintering resistance of size-selected platinum cluster catalysts by suppressed Ostwald ripening

Employing rationally designed model systems with precise atom-by-atom particle size control, we demonstrate by means of combining noninvasive in situ indirect nanoplasmonic sensing and ex situ scanning transmission electron microscopy that monomodal size-selected platinum cluster catalysts on different supports exhibit remarkable intrinsic sintering resistance even under reaction conditions. The observed stability is related to suppression of Ostwald ripening by elimination of its main driving force via size-selection. This study thus constitutes a general blueprint for the rational design of sintering resistant catalyst systems and for efficient experimental strategies to determine sintering mechanisms. Moreover, this is the first systematic experimental investigation of sintering processes in nanoparticle systems with an initially perfectly monomodal size distribution under ambient conditions.

How absorbed hydrogen affects the catalytic activity of transition metals

Heterogeneous catalysis is commonly governed by surface active sites. Yet, areas just below the surface can also influence catalytic activity, for instance, when fragmentation products of catalytic feeds penetrate into catalysts. In particular, H absorbed below the surface is required for certain hydrogenation reactions on metals. Herein, we show that a sufficient concentration of subsurface hydrogen, H(sub) , may either significantly increase or decrease the bond energy and the reactivity of the adsorbed hydrogen, H(ad) , depending on the metal. We predict a representative reaction, ethyl hydrogenation, to speed up on Pd and Pt, but to slow down on Ni and Rh in the presence of H(sub) , especially on metal nanoparticles. The identified effects of subsurface H on surface reactivity are indispensable for an atomistic understanding of hydrogenation processes on transition metals and interactions of hydrogen with metals in general.