Unraveling Temperature-Induced Vacancy Clustering in Tungsten: From Direct Microscopy to Atomistic Insights via Data-Driven Bayesian Sampling

Unraveling Temperature-Induced Vacancy Clustering in Tungsten: From Direct Microscopy to Atomistic Insights via Data-Driven Bayesian Sampling

The evolution of the microstructure of materials is primarily governed by defect-mediated diffusion. Here, we examine the intriguing role played by vacancies in tungsten, a strategic metal for high-temperature fusion-energy systems. We address the existing apparent contradictions between experimenta...

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Bibliographic Details
Main Authors: Anruo Zhong, Clovis Lapointe, Alexandra M. Goryaeva, Kazuto Arakawa, Manuel Athènes, Mihai-Cosmin Marinica
Format: Article
Language:English
Published: American Physical Society 2025-02-01
Series:PRX Energy
Online Access:http://doi.org/10.1103/PRXEnergy.4.013008
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