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The as-DPD sample is structurally characterized by a mixed nanostructure consisting of nanosized grains with an average size of 43 nm and bundles of nanoscale twins (with an average twin/matrix lamella thickness of 5 nm), as well as some dislocation structures, which exhibits a high yield strength of about 1470 MPa but a limited tensile ductility.
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The sample was structurally, morphologically, and chemically characterized by X-ray diffraction and field emission scanning electron microscopy analyses.
The sample was structurally characterized by X-ray diffraction (XRD) and neutron powder diffraction (NPD), since neutrons provide a bulk analysis and avoid preferred orientation problems.
The sample was structurally, morphologically, and chemically characterized by means of a Philips X-ray diffractometer (X'pert multi-purpose diffractometer (MPD); CuKa radiation) with a step size of 0.02° and step time of 1 s, and field emission scanning electron microscopy (FESEM) (CamScan MV2300, Czech and England).
As-cast samples are structurally microheterogeneous systems in which the composition and the relative content of different microphases varies with the chain length and the chemical nature of the soft component.
The samples were structurally characterised by X-ray diffraction (XRD), infrared spectroscopy (FTIR- ATR) and solid-state nuclear magnetic resonance (MAS NMR) of 27Al and 13C nuclei.
The samples were structurally characterized by conventional transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM), field emission scanning electron microscopy (FE-SEM), and energy dispersive X-ray (EDX) spectrometer measurements.
Tissues were furthermore degraded from tissues into individual cells while lab-scale pretreated samples were structurally almost intact.
The samples are structurally characterized by atomic force microscopy to evaluate the particle size, the particle densities, and the degree of aggregation.
Social Security is structurally sound.
In other words, this principle for model validation restricts the applicability of a model to reliably predict those test samples that are structurally similar to the training samples used to build that model [4 6].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com