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Predictive multiphase evolution in Al-containing high-entropy alloys.
Santodonato, L J; Liaw, P K; Unocic, R R; Bei, H; Morris, J R.
Afiliação
  • Santodonato LJ; Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.
  • Liaw PK; Advanced Research Systems, Macungie, PA, 18018, USA.
  • Unocic RR; Department of Materials Science and Engineering, The University of Tennessee, Knoxville, TN, 37996, USA.
  • Bei H; Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.
  • Morris JR; Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.
Nat Commun ; 9(1): 4520, 2018 10 30.
Article em En | MEDLINE | ID: mdl-30375384
ABSTRACT
The ability to predict and understand phases in high-entropy alloys (HEAs) is still being debated, and primarily true predictive capabilities derive from the known thermodynamics of materials. The present work demonstrates that prior work using high-throughput first-principles calculations may be further utilized to provide direct insight into the temperature- and composition-dependent phase evolution in HEAs, particularly Al-containing HEAs with a strengthening multiphase microstructure. Using a simple model with parameters derived from first-principles calculations, we reproduce the major features associated with Al-containing phases, demonstrating a generalizable approach for exploring potential phase evolution where little experimental data exists. Neutron scattering, in situ microscopy, and calorimetry measurements suggest that our high-throughput Monte Carlo technique captures both qualitative and quantitative features for both intermetallic phase formation and microstructure evolution at lower temperatures. This study provides a simple approach to guide HEA development, including ordered multi-phase HEAs, which may prove valuable for structural applications.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article