Neural Network-Assisted Development of High-Entropy Alloy Catalysts: Decoupling Ligand and Coordination Effects

High-entropy energy materials: challenges and new opportunities

“…In the energy field, ML approach can also be applied to optimize compositions and structures of HEMs for electrocatalysts in fuel cells, 182 CO 2 conversion 121 and oxygen catalysis. 50,183…”

Bayesian Optimization of High‐Entropy Alloy Compositions for Electrocatalytic Oxygen Reduction**

“…[7,8] Combinatorial exploration of vast alloy composition spaces has been actively used as at ool in experimental catalyst discovery for av ariety of reactions and constituent elements, [9][10][11][12][13][14][15][16] and efficient sampling of catalyst materials has also progressed. [17] However,a st he number of constituent elements increases,t he number of possible compositions grows combinatorially large and individual point testing cannot be accomplished within realistic time scales (see Modeling the catalytic activity of highly diverse and complex surfaces is still in its infancy with only af ew studies conducted, [1,3,4,20,21] and modeling of other aspects relevant for catalysis,such as surface stability under reaction conditions,is also being investigated. [22,23] We propose away to estimate the number of experiments needed using am odel that has been found to correctly predict experimental trends for electrocatalytic ORR across hundreds of different alloy compositions within the Ag-Ir-Pd-Pt-Ru system.…”

“…Modeling the catalytic activity of highly diverse and complex surfaces is still in its infancy with only a few studies conducted, [1, 3, 4, 20, 21] and modeling of other aspects relevant for catalysis, such as surface stability under reaction conditions, is also being investigated [22, 23] . We propose a way to estimate the number of experiments needed using a model that has been found to correctly predict experimental trends for electrocatalytic ORR across hundreds of different alloy compositions within the Ag‐Ir‐Pd‐Pt‐Ru system [4] .…”

Tailoring lattice strain in ultra-fine high-entropy alloys for active and stable methanol oxidation

“…Note that after high-temperature treatment, the achieved smaller bond length of Pt-Pt (2.58 Å) in HEA-700 would lead to a weaker adsorption of CO, indicating a high CO tolerance and promoting methanol oxidation. Moreover, as reported in our previous study, the adsorption sites of HEAs are very complex, including ligand effect (spatial arrangement of different elements) and coordination effect (different crystal facets and defects) due to the nature of high entropy [56]. In the current work, 16 surface Pt atoms are considered with different ligand environments, as shown in Fig.…”