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Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization.

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We developed a new method to find high entropy alloys (HEAs) for better electrocatalysis. This approach balances material activity, cost, and stability, discovering novel HEA catalysts for the oxygen reduction reaction.

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Area of Science:

  • Materials Science
  • Electrochemistry
  • Computational Materials Design

Background:

  • High entropy alloys (HEAs) show promise for electrocatalysis due to unique active site distributions that can overcome limitations of traditional catalysts.
  • Current virtual screening methods, like Bayesian optimization (BO), often prioritize catalytic activity alone, neglecting crucial factors like entropic stabilization.
  • This focus can lead to the identification of materials that are catalytically active but not inherently stable under operating conditions.

Purpose of the Study:

  • To introduce a novel multiobjective Bayesian optimization (BO) framework for the design of high entropy alloys (HEAs).
  • To simultaneously optimize HEA candidates for catalytic activity, cost-effectiveness, and entropic stabilization.
  • To explore uncharted HEA design spaces for improved electrocatalytic performance, specifically for the oxygen reduction reaction.

Main Methods:

  • Development of a multiobjective Bayesian optimization (BO) framework tailored for high entropy alloys (HEAs).
  • Integration of catalytic activity, cost, and entropic stabilization as simultaneous optimization objectives.
  • Implementation of diversity-guided batch selection to enhance data efficiency in the screening process.

Main Results:

  • The multiobjective BO framework successfully identified numerous promising HEA candidates for the oxygen reduction reaction.
  • The identified materials effectively balance catalytic activity, cost-effectiveness, and entropic stabilization.
  • The approach enabled exploration of complex HEA design spaces involving up to 10 elements.

Conclusions:

  • The proposed multiobjective BO framework offers a more holistic approach to designing high entropy alloys for electrocatalysis.
  • This method overcomes the limitations of single-objective optimization, leading to more practical and stable HEA catalyst candidates.
  • The findings pave the way for discovering advanced HEAs with tailored properties for various electrochemical applications.