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- W3001726563 endingPage "112943" @default.
- W3001726563 startingPage "112943" @default.
- W3001726563 abstract "Annealed metastable β titanium (Ti) alloys comprise body-centred-cubic β and hexagonal-close-packed α phases and possibly, orthorhombic α″ martensite that forms on quenching or deformation. Electron backscattering diffraction is amongst the most popular methods for characterising such multi-phase microstructures. However, the crystallographic similarity between α and α″ martensite renders unambiguous discrimination of these phases via electron backscattering patterns (EBSPs) virtually impossible; thereby limiting the use of EBSD in characterising β-Ti alloys. In this study, we demonstrate that α and α″ martensite are primarily misindexed due to an indiscernible difference between these phases along their [1¯10]α and [010]α″ zone axes. Furthermore, the slight compositional difference between α and α″ is insufficient to discriminate these phases using on-the-fly energy-dispersive X-ray spectroscopy (EDS) spectrum matching. Consequently, a segmentation method was developed that relies on a combination of reindexed EBSPs and grain-median EDS elemental data to unambiguously discriminate β, α and α″ martensite in metastable β Ti alloys. All steps are implemented in an open-source and freely available computer program called phaseSegmenter that makes use of the MTEX toolbox in MATLAB. The program is readily applicable to Ti alloys containing α′, α″ or massively transformed α as well as other phase transforming alloy systems with similar phase discrimination issues." @default.
- W3001726563 created "2020-01-30" @default.
- W3001726563 creator A5033976706 @default.
- W3001726563 creator A5086714408 @default.
- W3001726563 date "2020-04-01" @default.
- W3001726563 modified "2023-10-14" @default.
- W3001726563 title "Discriminating β, α and α″ phases in metastable β titanium alloys via segmentation: A combined electron backscattering diffraction and energy-dispersive X-ray spectroscopy approach" @default.
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- W3001726563 doi "https://doi.org/10.1016/j.ultramic.2020.112943" @default.
- W3001726563 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32062056" @default.
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