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Toward predictive alloy design: a vacancy engineering maturity framework

Aswin Karkadakattil

2026enalloy designvacancy engineeringmaterials sciencecomputational modelling

Abstract

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Atomic vacancies are fundamental point defects that govern diffusion, recovery, precipitation, phase transformations, and defect evolution in metallic materials. Recent advances in non-equilibrium processing, vacancy-sensitive characterization, and computational modelling have created opportunities to treat vacancies as potentially controllable microstructural variables. However, the evidence remains fragmented across processing routes, characterization techniques, modelling scales, and alloy systems, limiting the transition from fundamental vacancy science to deliberate alloy design. This review critically assesses vacancy engineering by integrating vacancy generation, quantitative characterization, transport, vacancy–solute interactions, defect evolution, microstructural response, and engineering property implications within a unified evidence assessment framework. Vacancy generation through rapid solidification, severe plastic deformation, thermomechanical processing, irradiation, and additive manufacturing is examined alongside experimental and computational approaches for resolving vacancy behaviour. A Vacancy Engineering Maturity Framework (VEMF) is proposed across four dimensions: vacancy generation controllability, quantitative characterization, vacancy-mediated transport and property linkage, and readiness for alloy design. To support transparent assessment, the review distinguishes direct, indirect, computational, coupled experimental–computational, and mechanistic evidence and evaluates the extent to which reported vacancy effects can be quantitatively characterized and linked to material response. Quantitative descriptors including vacancy concentration and supersaturation, formation and migration energies, diffusivity, vacancy lifetime, vacancy–solute binding energy, sink density, and diffusion length are identified as key parameters for advancing beyond qualitative descriptions. The analysis shows that the central challenge is not simply generating vacancies, but quantifying, stabilizing, and controlling their concentration, mobility, lifetime, spatial distribution, and interactions with solutes and other defects.

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Cite This Work

@article{53e314d8-7f47-4894-b5ed-e398fbcefb98,
  title={Toward predictive alloy design: a vacancy engineering maturity framework},
  author={Aswin Karkadakattil},
  year={2026},
  language={en}
}
TY  - JOUR
TI  - Toward predictive alloy design: a vacancy engineering maturity framework
AU  - Aswin Karkadakattil
PY  - 2026
LA  - en
ER  -

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