Data for: "Subgrain structure and dislocations in WC-Co hard metals revealed by electron channelling contrast imaging"



This dataset contains the experimental data used to generate the figures in the journal article, “Subgrain structure and dislocations in WC-Co hard metals revealed by electron channelling contrast imaging”.

The electron channelling contrast imaging data was recorded using a Zeiss Auriga FIB SEM using the Zeiss supplied quadrant diode backscattered electron detector which is inserted beneath the pole piece. The sample was tilted by around 20° away from the horizontal to increase the intensity of the backscattered signal, as the number of backscattered electrons increases as you increase the tilt of the sample. A series of images of single WC grains with the sample at different tilts or for different rotations were then acquired. In the case of the tilt series, ECCI images were acquired for tilts between 17° and 22° with the sample tilt changed by 0.2° between image acquisitions. For the rotation series, the sample was tilted at 20° and rotated 10° between image acquisitions, with the sample rotated by 180 for each grain. ECCI is a SEM based diffraction technique which can be used to detect small orientation changes or changes in lattice constant in a material. ECCI micrographs may be produced when a sample is placed so that a plane or planes are at, or close to, the Bragg angle with respect to the incident electron beam. Any deviation in crystallographic orientation or in lattice constant due to local strain will produce a variation in contrast in the resultant ECCI micrograph. Extremely small changes in orientation and strain are detectable, revealing subgrains and extended defects such as dislocations and stacking faults. We can also investigate the contrast exhibited by a defect for different diffraction conditions, ultimately identifying the nature of the defect.

EBSD data in this study was collected in a Zeiss Auriga FIB SEM outfitted with an Oxford NordlysNano system. EBSD maps were acquired at 20 or 30 kV accelerating voltage with a 10 nA beam and the sample tilted at 70° from the horizontal. In EBSD the sample is tilted at around 70 to the normal of the incident electron beam. The impinging electrons are scattered inelastically through high angles forming a diverging source of electrons which can be diffracted. The resultant electron backscatter diffraction pattern (EBSP) consists of a large number of overlapping bands, known as Kikuchi bands, which are closely related to a 2-D projection of the crystal structure. Acquiring EBSPs over a grid of points on a sample allows mapping of the sample’s microstructure.

Abstract of the paper:

In this study, electron channelling contrast imaging (ECCI) and electron backscatter diffraction (EBSD) have been used to examine the substructure and dislocations in tungsten carbide (WC) grains in tungsten carbide-cobalt (WC-Co) hardmetals. These complimentary scanning electron microscopy (SEM) diffraction techniques provide quantifiable information of the substructure without the difficulty of transmission electron microscopy (TEM) sample preparation and examination. Subgrain structures in WC grains have rarely been reported previously because of the sample preparation difficulty, but this study has found they can occur frequently and may provide information on grain growth during sintering. ECCI has also shown for the first time complex dislocation networks across large grains, indicating accumulation of stress in as-sintered materials. To identify the defects revealed by ECCI more precisely, WC grains with surface normals [0001],[11 ̅00] and [112 ̅0], were identified using inverse pole figure orientation maps generated from EBSD data. ECC images from these grains reveal defects intersecting the surface and subgrains bound by dislocations. The combination of ECCI and EBSD allows for new insights into dislocation networks in a WC-Co hardmetal sample over a large, in this case 75 μm × 75 μm, field of view.
Date made available18 Dec 2019
PublisherUniversity of Strathclyde
Date of data production2016 -

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