Computationally aided, entropy-driven synthesis of highly efficient and durable multi-elemental alloy catalysts

Area of Science:

• Materials Science
• Catalysis
• Computational Chemistry

Background:

• Multi-elemental alloy nanoparticles (MEA-NPs) offer vast potential for catalyst discovery.
• Synthesizing complex MEA-NP structures controllably remains a significant challenge.

Purpose of the Study:

• To develop a computationally guided strategy for designing and synthesizing efficient and durable MEA-NPs.
• To explore the application of these MEA-NPs in catalytic ammonia decomposition.

Main Methods:

• Utilized computational screening of millions of compositions.
• Employed density functional theory (DFT) for alloy formation prediction.
• Applied hybrid Monte Carlo and molecular dynamics for structural stability analysis.

Main Results:

• Successfully designed and rapidly synthesized entropy-driven MEA-NPs at high temperatures (1500 K, 0.5 s).
• Achieved excellent thermal stability in the synthesized MEA-NPs.
• Demonstrated outstanding catalytic performance for ammonia decomposition due to synergistic effects.

Conclusions:

• Computationally aided design and rapid synthesis of MEA-NPs are effective.
• These MEA-NPs exhibit superior catalytic activity and durability.
• The approach is broadly applicable for accelerating the discovery of new catalysts.