TY - JOUR
T1 - High throughput crystal structure and composition mapping of crystalline nanoprecipitates in alloys by transmission Kikuchi diffraction and analytical electron microscopy
AU - Bhattacharya, Arunodaya
AU - Parish, Chad M.
AU - Henry, Jean
AU - Katoh, Yutai
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/7
Y1 - 2019/7
N2 - Statistically significant crystal structure and composition identification of nanocrystalline features such as nanoparticles/nanoprecipitates in materials chemistry and alloy designing using electron microscopy remains a grand challenge. In this paper, we reveal that differing crystallographic phases of nanoprecipitates in alloys can be mapped with unprecedented statistics using transmission Kikuchi diffraction (TKD), on typical carbon-based electron-transparent samples. Using a case of multiphase, multicomponent nanoprecipitates extracted from an improved version of 9% chromium Eurofer-97 reduced-activation ferritic-martensitic steel we show that TKD successfully identified more than thousand M 23 C 6 , MX, M 7 C 3 and M 2 X (M=Fe, Cr, W, V, Ta; X = C, N) nanoprecipitates in a single scan, something that is currently unachievable using a transmission electron microscope (TEM) without incorporating a precision electron diffraction (PED) system. Precipitates as small as ∼20–25 nm were successfully phase identified by TKD. We verified the TKD phase identification using high-resolution transmission electron microscopy (HRTEM) and convergent beam electron diffraction (CBED) pattern analysis of a few precipitates that were identified by TKD on same sample. TKD study was combined with state-of-art analytical scanning transmission electron microscopy (STEM)-energy dispersive X-ray (EDX) spectroscopy and multivariate statistical analysis (MVSA) which provided the complete crystal structure and distinct chemistries of the precipitates in the steel in a high throughput automated way. This technique should be applicable to characterizing any multiphase crystalline nanoparticles or nanomaterials. The results highlight that combining phase identification by TKD with analytical STEM and modern data analytics may open new pathways in big data material characterization at nanoscale that may be highly beneficial for characterizing existing materials and in designing new materials.
AB - Statistically significant crystal structure and composition identification of nanocrystalline features such as nanoparticles/nanoprecipitates in materials chemistry and alloy designing using electron microscopy remains a grand challenge. In this paper, we reveal that differing crystallographic phases of nanoprecipitates in alloys can be mapped with unprecedented statistics using transmission Kikuchi diffraction (TKD), on typical carbon-based electron-transparent samples. Using a case of multiphase, multicomponent nanoprecipitates extracted from an improved version of 9% chromium Eurofer-97 reduced-activation ferritic-martensitic steel we show that TKD successfully identified more than thousand M 23 C 6 , MX, M 7 C 3 and M 2 X (M=Fe, Cr, W, V, Ta; X = C, N) nanoprecipitates in a single scan, something that is currently unachievable using a transmission electron microscope (TEM) without incorporating a precision electron diffraction (PED) system. Precipitates as small as ∼20–25 nm were successfully phase identified by TKD. We verified the TKD phase identification using high-resolution transmission electron microscopy (HRTEM) and convergent beam electron diffraction (CBED) pattern analysis of a few precipitates that were identified by TKD on same sample. TKD study was combined with state-of-art analytical scanning transmission electron microscopy (STEM)-energy dispersive X-ray (EDX) spectroscopy and multivariate statistical analysis (MVSA) which provided the complete crystal structure and distinct chemistries of the precipitates in the steel in a high throughput automated way. This technique should be applicable to characterizing any multiphase crystalline nanoparticles or nanomaterials. The results highlight that combining phase identification by TKD with analytical STEM and modern data analytics may open new pathways in big data material characterization at nanoscale that may be highly beneficial for characterizing existing materials and in designing new materials.
KW - Analytical electron microscopy
KW - HRTEM
KW - Multi-variate statistical analysis (MVSA)
KW - Nanoprecipitates
KW - Transmission Kikuchi diffraction
UR - http://www.scopus.com/inward/record.url?scp=85063500592&partnerID=8YFLogxK
U2 - 10.1016/j.ultramic.2019.03.015
DO - 10.1016/j.ultramic.2019.03.015
M3 - Article
C2 - 30933741
AN - SCOPUS:85063500592
SN - 0304-3991
VL - 202
SP - 33
EP - 43
JO - Ultramicroscopy
JF - Ultramicroscopy
ER -