Gold nanoparticles aggregation on graphene using Reactive force field: A molecular dynamic study

We examine the aggregation behavior of AuNPs of different sizes on graphene as function of temperature using molecular dynamic simulations with Reax Force Field. In addition, the consequences of such aggregation on the morphology of AuNPs and the charge transfer behavior of AuNP-Graphene hybrid structure are analyzed. The aggregation of AuNPs on graphene is confirmed from the center of mass distance calculation. The simulation results indicate that the size of AuNPs and temperature significantly affect the aggregation behavior of AuNPs on graphene. The strain calculation showed that shape of AuNPs changes due to the aggregation and the smaller size AuNPs on graphene exhibit more shape changes than larger AuNPs at all the temperatures studies in this work. The charge transfer calculation reveals that, the magnitude of charge transfer is higher for larger AuNPs-graphene composite when compared with smaller AuNPs-graphene composite. The charge transfer trend and the trends seen in the number of Au atoms directly in touch with graphene are identical. Hence, our results conclude that, quantity of Au atoms directly in contact with graphene during aggregation is primarily facilitates charge transfer between AuNPs and graphene. Our results on the size dependent strain and charge transfer characteristics of AuNPs will aid in the development of AuNPs-graphene composites for sensor applications.

Electrochemical hydrogen evolution on Pt-based catalysts from a theoretical perspective

Hydrogen evolution reaction (HER) by splitting water is a key technology toward a clean energy society, where Pt-based catalysts were long known to have the highest activity under acidic electrochemical conditions but suffer from high cost and poor stability. Here, we overview the current status of Pt-catalyzed HER from a theoretical perspective, focusing on the methodology development of electrochemistry simulation, catalytic mechanism, and catalyst stability. Recent developments in theoretical methods for studying electrochemistry are introduced, elaborating on how they describe solid-liquid interface reactions under electrochemical potentials. The HER mechanism, the reaction kinetics, and the reaction sites on Pt are then summarized, which provides an atomic-level picture of Pt catalyst surface dynamics under reaction conditions. Finally, state-of-the-art experimental solutions to improve catalyst stability are also introduced, which illustrates the significance of fundamental understandings in the new catalyst design.

Pt38 as a promising ethanol catalyst: a first principles study

This first-principles study predicts Pt₃₈ nanoparticles as a catalyst for ethanol reactions. Starting from the adsorption properties, we shed light on the effectiveness of Pt-based nanoclusters as ethanol catalysts. First, the ethanol adsorption on Pt₃₈ shows that the most stable site positions the molecule with the oxygen anchored on top of an edge, whereas CH₃ is oriented towards the facet and the molecule remains in trans-symmetry. The ethanol-oxygen adsorbed on top of a facet Pt-atom offers the least stable configuration and the longer Pt-O distance (2.318 Å), while the shorter Pt-O distance (2.237 Å) is found when ethanol is on top of an edge site and the molecule is vertically oriented with Gauche symmetry. A shorter Pt-O distance correlates with higher radial breathing of the nanoparticle after ethanol adsorption. Atomic charge redistribution is calculated on all the considered systems and cases. In any event, we show that the Pt-anchor receives a charge, whilst oxygen-ethanol donates electrons. Orbital analysis shows that Pt-anchors and ethanol-oxygen atoms primarily exchange p-charge. Energy barriers associated with the ethanol bond cleavage show that the C-C bond break is slightly more favourable on Pt₃₈ than on an extended Pt(111). In addition, we find that the cleavage of the hydroxyl O-H ethanol bond shows a higher energy barrier while the removal of an H-atom from the CH₃ group is easier. These three facts indicate that the Pt₃₈ nanoparticle enhances ethanol catalysis and hence is a good candidate for ethanol-based fuel cells.

Exploring the Potential Energy Surface of Pt6 Sub-Nano Clusters Deposited over Graphene

Catalytic systems based on sub-nanoclusters deposited over different supports are promising for very relevant chemical transformations such as many electrocatalytic processes as the ORR. These systems have been demonstrated to be very fluxional, as they are able to change shape and interconvert between each other either alone or in the presence of adsorbates. In addition, an accurate representation of their catalytic activity requires the consideration of ensemble effects and not a single structure alone. In this sense, a reliable theoretical methodology should assure an accurate and extensive exploration of the potential energy surface to include all the relevant structures and with correct relative energies. In this context, we applied DFT in conjunction with global optimization techniques to obtain and analyze the characteristics of the many local minima of Pt₆ sub-nanoclusters over a carbon-based support (graphene)-a system with electrocatalytic relevance. We also analyzed the magnetism and the charge transfer between the clusters and the support and paid special attention to the dependence of dispersion effects on the ensemble characteristics. We found that the ensembles computed with and without dispersion corrections are qualitatively similar, especially for the lowest-in-energy clusters, which we attribute to a (mainly) covalent binding to the surface. However, there are some significant variations in the relative stability of some clusters, which would significantly affect their population in the ensemble composition.

Enhanced oxygen reduction activity of size-selected platinum subnanocluster catalysts: Ptn (n = 3–9)

Ptn subnanoclusters (n = 3–9) on a carbon substrate exhibit 1.6–2.2 times higher activity than the standard Pt/C catalysts. EXAFS experiments and DFT calculations show plausible structures and energetics for reaction intermediates in the processes.

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.

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

Enhanced oxygen reduction activity of platinum subnanocluster catalysts through charge redistribution

Single-size platinum Pt6 subnanoclusters exhibit superior mass-specific and surface-specific activities for the oxygen reduction reaction. The enhanced activity is attributed to polarized electron distributions based on rigorous structure characterization by X-ray absorption fine structure spectroscopy and density functional theory.

Promoted Glycerol Oxidation Reaction in an Interface-Confined Hierarchically Structured Catalyst

Confined catalysis in a 2D system is of particular interest owing to the facet control of the catalysts and the anisotropic kinetics of reactants, which suppress side reactions and improve selectivity. Here, a 2D-confined system consisting of intercalated Pt nanosheets within few-layered graphene is demonstrated. The strong metal-substrate interaction between the Pt nanosheets and the graphene leads to the quasi-2D growth of Pt with a unique (100)/(111)/(100) faceted structure, thus providing excellent catalytic activity and selectivity toward one-carbon (C1) products for the glycerol oxidation reaction. A hierarchically porous graphene architecture, grown on carbon cloth, is used to fabricate the confined catalyst bed in order to enhance the mass-diffusion limitation in interface-confined reactions. Owing to its unique 3D porous structure, this graphene-confined Pt catalyst exhibits an extraordinary mass activity of 2910 mA mg_Pt ^-1 together with a formate selectivity of 79% at 60 °C. This paves the way toward rational designs of heterogeneous catalysts for energy-related applications.

Ideal versus real: simulated annealing of experimentally derived and geometric platinum nanoparticles

Platinum nanoparticles find significant use as catalysts in industrial applications such as fuel cells. Research into their design has focussed heavily on nanoparticle size and shape as they greatly influence activity. Using high throughput, high precision electron microscopy, the structures of commercially available Pt catalysts have been determined, and we have used classical and quantum atomistic simulations to examine and compare them with geometric cuboctahedral and truncated octahedral structures. A simulated annealing procedure was used both to explore the potential energy surface at different temperatures, and also to assess the effect on catalytic activity that annealing would have on nanoparticles with different geometries and sizes. The differences in response to annealing between the real and geometric nanoparticles are discussed in terms of thermal stability, coordination number and the proportion of optimal binding sites on the surface of the nanoparticles. We find that annealing both experimental and geometric nanoparticles results in structures that appear similar in shape and predicted activity, using oxygen adsorption as a measure. Annealing is predicted to increase the catalytic activity in all cases except the truncated octahedra, where it has the opposite effect. As our simulations have been performed with a classical force field, we also assess its suitability to describe the potential energy of such nanoparticles by comparing with large scale density functional theory calculations.

DL_MG: A Parallel Multigrid Poisson and Poisson-Boltzmann Solver for Electronic Structure Calculations in Vacuum and Solution

The solution of the Poisson equation is a crucial step in electronic structure calculations, yielding the electrostatic potential-a key component of the quantum mechanical Hamiltonian. In recent decades, theoretical advances and increases in computer performance have made it possible to simulate the electronic structure of extended systems in complex environments. This requires the solution of more complicated variants of the Poisson equation, featuring nonhomogeneous dielectric permittivities, ionic concentrations with nonlinear dependencies, and diverse boundary conditions. The analytic solutions generally used to solve the Poisson equation in vacuum (or with homogeneous permittivity) are not applicable in these circumstances, and numerical methods must be used. In this work, we present DL_MG, a flexible, scalable, and accurate solver library, developed specifically to tackle the challenges of solving the Poisson equation in modern large-scale electronic structure calculations on parallel computers. Our solver is based on the multigrid approach and uses an iterative high-order defect correction method to improve the accuracy of solutions. Using two chemically relevant model systems, we tested the accuracy and computational performance of DL_MG when solving the generalized Poisson and Poisson-Boltzmann equations, demonstrating excellent agreement with analytic solutions and efficient scaling to ∼10⁹ unknowns and 100s of CPU cores. We also applied DL_MG in actual large-scale electronic structure calculations, using the ONETEP linear-scaling electronic structure package to study a 2615 atom protein-ligand complex with routinely available computational resources. In these calculations, the overall execution time with DL_MG was not significantly greater than the time required for calculations using a conventional FFT-based solver.

DFT calculation of oxygen adsorption on platinum nanoparticles: coverage and size effects

DFT calculations are used to simultaneously explore the effects of nanoparticle size and coverage for O adsorption on Pt nanoparticles.

Ethanol, O, and CO adsorption on Pt nanoparticles: effects of nanoparticle size and graphene support

DFT calculations reveal aspects of size and support effects for Pt nanoparticles on graphene interacting with O, CO and ethanol.

3D Analysis of Fuel Cell Electrocatalyst Degradation on Alternate Carbon Supports

Understanding the mechanisms associated with Pt/C electrocatalyst degradation in proton exchange membrane fuel cell (PEMFC) cathodes is critical for the future development of higher-performing materials; however, there is a lack of information regarding Pt coarsening under PEMFC operating conditions within the cathode catalyst layer. We report a direct and quantitative 3D study of Pt dispersions on carbon supports (high surface area carbon (HSAC), Vulcan XC-72, and graphitized carbon) with varied surface areas, graphitic character, and Pt loadings ranging from 5 to 40 wt %. This is accomplished both before and after catalyst-cycling accelerated stress tests (ASTs) through observations of the cathode catalyst layer of membrane electrode assemblies. Electron tomography results show Pt nanoparticle agglomeration occurs predominantly at junctions and edges of aggregated graphitized carbon particles, leading to poor Pt dispersion in the as-prepared catalysts and increased coalescence during ASTs. Tomographic reconstructions of Pt/HSAC show much better initial Pt dispersions, less agglomeration, and less coarsening during ASTs in the cathode. However, a large loss of the electrochemically active surface area (ECSA) is still observed and is attributed to accelerated Pt dissolution and nanoparticle coalescence. Furthermore, a strong correlation between Pt particle/agglomerate size and measured ECSA is established and is proposed as a more useful metric than average crystallite size in predicting degradation behavior across different catalyst systems.