A first-principles-based high fidelity, high throughput approach for the design of high entropy alloys.

Here, we present a preselected small set of ordered structures (PSSOS) method, a first principles-based high fidelity (HF), high throughput (HT) approach, for fast screening of the large composition space of high entropy alloys (HEAs) to select the most energetically stable, single-phase HEAs. Taking quinary AlCoCrFeNi HEA as an example system, we performed PSSOS calculations on the formation energies and mass densities of 8801 compositions in both FCC and BCC lattices and selected five most stable FCC and BCC HEAs for detailed analysis. The calculation results from the PSSOS approach were compared with existing experimental and first-principles data, and the good agreement was achieved. We also compared the PSSOS with the special quasi-random structures (SQS) method, and found that with a comparable accuracy, the PSSOS significantly outperforms the SQS in efficiency, making it ideal for HF, HT calculations of HEAs.

Computational screening for effective Ge1-xSix nanowire photocatalyst.

We perform a comprehensive mapping of GeSi nanowire (NW) electronic band characteristics versus the alloy composition and the diameter (up to 3 nm) using hybrid density functional theory (DFT) calculations, the cluster expansion method and Monte Carlo simulations. We reveal that stable alloy GeSi NW configurations across compositions tend to exhibit asymmetric core-shell structures, which enhance spatial separation of the band edges, making them more effective for electron-hole charge separation as compared to conventional symmetric core-shell structures. More importantly, from the composition-size map of the NW band edges, we show that GeSi NWs with diameters below 3 nm are thermodynamically capable of photocatalysing water-splitting reactions (alkaline conditions) and CO2 reduction. In particular, NWs with diameters of 2 and 3 nm possess desirable properties for efficient photo-conversion; their bandgaps (1.4 to 2.0 eV) match well with the solar spectrum.

Nanoalloy electrocatalysis: simulating cyclic voltammetry from configurational thermodynamics with adsorbates.

We simulate the adsorption isotherms for alloyed nanoparticles (nanoalloys) with adsorbates to determine cyclic voltammetry (CV) during electrocatalysis. The effect of alloying on nanoparticle adsorption isotherms is provided by a hybrid-ensemble Monte Carlo simulation that uses the cluster expansion method extended to non-exchangeable coupled lattices for nanoalloys with adsorbates. Exemplified here for the hydrogen evolution reaction, a 2-dimensional CV is mapped for Pd-Pt nanoalloys as a function of both electrochemical potential and the global Pt composition, and shows a highly non-linear alloying effect on CV. Detailed features in CV arise from the interplay among the H-adsorption in multiple sites that is closely correlated with alloy configurations, which are in turn affected by the H-coverage. The origins of specific features in CV curves are assigned. The method provides a more complete means to design nanoalloys for electrocatalysis.

Configurational thermodynamics of alloyed nanoparticles with adsorbates.

Changes in the chemical configuration of alloyed nanoparticle (NP) catalysts induced by adsorbates under working conditions, such as reversal in core-shell preference, are crucial to understand and design NP functionality. We extend the cluster expansion method to predict the configurational thermodynamics of alloyed NPs with adsorbates based on density functional theory data. Exemplified with PdRh NPs having O-coverage up to a monolayer, we fully detail the core-shell behavior across the entire range of NP composition and O-coverage with quantitative agreement to in situ experimental data. Optimally fitted cluster interactions in the heterogeneous system are the key to enable quantitative Monte Carlo simulations and design.

Unveiling stable group IV alloy nanowires via a comprehensive search and their electronic band characteristics.

By means of density functional theory calculations, the cluster expansion method, and Monte Carlo simulations, we identify the stable spatial configurations (ground states) for [100] CSi, GeSi, and SnSi alloy nanowires (NWs) across compositions. In particular, we find that stable configurations of GeSiNWs and SnSiNWs exhibit core-shell segregation tendencies, while those of CSiNWs favor ordering. Moreover, we show compositional ranges where the band gaps are expected to vary linearly with composition, allowing predictable band gap fine-tuning. We also predict composition ranges where the spatial separation of near-band gap states are imminent, making it possible for electron-hole charge separation. By addressing both the issues of stability and the compositional trend of electronic band structure, our work should prove useful for designing alloy NWs of smaller dimensions.

A comprehensive search for stable Pt-Pd nanoalloy configurations and their use as tunable catalysts.

Using density-functional theory, we predict stable alloy configurations (ground states) for a 1 nm Pt-Pd cuboctahedral nanoparticle across the entire composition range and demonstrate their use as tunable alloy catalysts via hydrogen-adsorption studies. Unlike previous works, we use simulated annealing with a cluster expansion Hamiltonian to perform a rapid and comprehensive search that encompasses both high and low-symmetry configurations. The ground states show Pt(core)-Pd(shell) type configurations across all compositions but with specific Pd patterns. For catalysis studies at room temperatures, the ground states are more realistic structural models than the commonly assumed random alloy configurations. Using the ground states, we reveal that the hydrogen adsorption energy increases (decreases) monotonically with at. % Pt for the {111} hollow ({100} bridge) adsorption site. Such trends are useful for designing tunable Pd-Pt nanocatalysts for the hydrogen evolution reaction.