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The identification of the stable phases in alloy materials is challenging because composition affects the structural stability of different intermediate phases. Computational simulation, via multiscale modelling approaches, can significantly accelerate the exploration of phase space and help to identify stable phases. Here, we apply such new approaches to understand the complex phase diagram of binary alloys of PdZn, with the relative stability of structural polymorphs considered through application of density functional theory coupled with cluster expansion (CE). The experimental phase diagram has several competing crystal structures, and we focus on three different closed-packed phases that are commonly observed for PdZn, namely the face-centred cubic (FCC), body-centred tetragonal (BCT) and hexagonal close packed (HCP), to identify their respective stability ranges. Our multiscale approach confirms a narrow range of stability for the BCT mixed alloy, within the Zn concentration range from 43.75% to 50%, which aligns with experimental observations. We subsequently use CE to show that the phases are competitive across all concentrations, but with the FCC alloy phase favoured for Zn concentrations below 43.75%, and that the HCP structure favoured for Zn-rich concentrations. Our methodology and results provide a platform for future investigations of PdZn and other close-packed alloy systems with multiscale modelling techniques., (Creative Commons Attribution license.)

The reaction mechanism of direct CO 2 hydrogenation to methanol is investigated in detail on Pd (111), (100) and (110) surfaces using density functional theory (DFT), supporting investigations into emergent Pd-based catalysts. Hydrogen adsorption and surface mobility are firstly considered, with high-coordination surface sites having the largest adsorption energy and being connected by diffusion channels with low energy barriers. Surface chemisorption of CO 2 , forming a partially charged CO 2 δ - , is weakly endothermic on a Pd (111) whilst slightly exothermic on Pd (100) and (110), with adsorption enthalpies of 0.09, -0.09 and -0.19 eV, respectively; the low stability of CO 2 δ - on the Pd (111) surface is attributed to negative charge accumulating on the surface Pd atoms that interact directly with the CO 2 δ - adsorbate. Detailed consideration for sequential hydrogenation of the CO 2 shows that HCOOH hydrogenation to H 2 COOH would be the rate determining step in the conversion to methanol, for all surfaces, with activation barriers of 1.41, 1.51, and 0.84 eV on Pd (111), (100) and (110) facets, respectively. The Pd (110) surface exhibits overall lower activation energies than the most studied Pd (111) and (100) surfaces, and therefore should be considered in more detail in future Pd catalytic studies.

The development and application of trimetallic nanoparticles continues to accelerate rapidly as a result of advances in materials design, synthetic control, and reaction characterization. Following the technological successes of multicomponent materials in automotive exhausts and photovoltaics, synergistic effects are now accessible through the careful preparation of multielement particles, presenting exciting opportunities in the field of catalysis. In this review, we explore the methods currently used in the design, synthesis, analysis, and application of trimetallic nanoparticles across both the experimental and computational realms and provide a critical perspective on the emergent field of trimetallic nanocatalysts. Trimetallic nanoparticles are typically supported on high-surface-area metal oxides for catalytic applications, synthesized via preparative conditions that are comparable to those applied for mono- and bimetallic nanoparticles. However, controlled elemental segregation and subsequent characterization remain challenging because of the heterogeneous nature of the systems. The multielement composition exhibits beneficial synergy for important oxidation, dehydrogenation, and hydrogenation reactions; in some cases, this is realized through higher selectivity, while activity improvements are also observed. However, challenges related to identifying and harnessing influential characteristics for maximum productivity remain. Computation provides support for the experimental endeavors, for example in electrocatalysis, and a clear need is identified for the marriage of simulation, with respect to both combinatorial element screening and optimal reaction design, to experiment in order to maximize productivity from this nascent field. Clear challenges remain with respect to identifying, making, and applying trimetallic catalysts efficiently, but the foundations are now visible, and the outlook is strong for this exciting chemical field.

We report a detailed Density Functional Theory (DFT) based investigation of the structure and stability of bulk and surface structures for the Group 10-12 elements Pd, Cu and Zn, considering the effect of the choice of exchange-correlation density functional and computation parameters. For the initial bulk structures, the lattice parameter and cohesive energy are calculated, which are then augmented by calculation of surface energies and work functions for the lower-index surfaces. Of the 22 density functionals considered, we highlight the mBEEF density functional as providing the best overall agreement with experimental data. The optimal density functional choice is applied to the study of higher index surfaces for the three metals, and Wulff constructions performed for nanoparticles with a radius of 11 nm, commensurate with nanoparticle sizes commonly employed in catalytic chemistry. For Pd and Cu, the low-index (111) facet is dominant in the constructed nanoparticles, covering ∼50% of the surface, with (100) facets covering a further 10 to 25%; however, non-negligible coverage from higher index (332), (332) and (210) facets is also observed for Pd, and (322), (221) and (210) surfaces are observed for Cu. In contrast, only the (0001) and (10-10) facets are observed for Zn. Overall, our results highlight the need for careful validation of computational settings before performing extensive density functional theory investigations of surface properties and nanoparticle structures of metals.