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Ryan M Trottier1, Samantha L Millican1, Charles B Musgrave1,2,3,4

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This study introduces a modified single iteration synchronous-transit (MSIST) method to quickly estimate diffusion barriers in materials. MSIST significantly reduces computational cost while providing reliable bounds for transition state energies.

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Solid-State Physics

Background:

  • Accurate prediction of material properties relies on understanding solid-state diffusion kinetics.
  • Traditional methods for calculating diffusion barriers, like nudged elastic band (NEB), are computationally expensive.
  • Accelerating materials screening requires more efficient computational approaches for diffusion analysis.

Purpose of the Study:

  • To develop and validate a computationally efficient method for estimating solid-state diffusion barriers.
  • To identify reliable upper and lower bounds for transition state (TS) energies.
  • To enable high-throughput screening of materials for diffusion-controlled properties.

Main Methods:

  • Proposed a modified single iteration synchronous-transit (MSIST) approach to identify TS energy bounds.
  • Reduced computational demand by ∼70% compared to full NEB calculations, requiring only 30% of force evaluations.
  • Validated MSIST by comparing its results with explicit NEB calculations across 53 cases.

Main Results:

  • MSIST successfully bracketed NEB-calculated TS energies in all 53 comparative cases.
  • Demonstrated MSIST's efficacy in analyzing Na+ diffusion in battery electrodes and oxygen vacancy diffusion in fuel cell components.
  • Achieved average diffusion barrier ranges of 0.08 eV for Na+ diffusion and 0.33 eV in high-throughput screening of 97 materials.

Conclusions:

  • MSIST offers a significant computational speedup for estimating diffusion barriers, enabling broader materials analysis.
  • The method provides explicit error bounds, facilitating reliable data modeling and physical insight development.
  • MSIST accelerates the discovery of materials with desirable diffusion properties for applications like batteries and fuel cells.