We introduce an unsupervised machine learning (ML) based technique for the identification and characterization of microstructures in three-dimensional (3D) samples obtained from molecular dynamics simulations, particle tracking data, or experiments. Our technique combines topology classification, image processing, and clustering algorithms, and can handle a wide range of microstructure types including grains in polycrystalline materials, voids in porous systems, and structures from self/directed assembly in soft-matter complex solutions. Our technique does not require a priori microstructure description of the target system and is insensitive to disorder such as extended defects in polycrystals arising from line and plane defects. We demonstrate quantitively that our technique provides unbiased microstructural information such as precise quantification of grains and their size distributions in 3D polycrystalline samples, characterizes features such as voids and porosity in 3D polymeric samples and micellar size distribution in 3D complex fluids. To demonstrate the efficacy of our ML approach, we benchmark it against a diverse set of synthetic data samples representing nanocrystalline metals, polymers and complex fluids as well as experimentally published characterization data. Our technique is computationally efficient and provides a way to quickly identify, track, and quantify complex microstructural features that impact the observed material behavior.

/pdf/machine-learning-enabled-autonomous-microstructural-58yy2bofk1.pdf

Machine learning enabled autonomous microstructural characterization in 3D samples

Superplasticity in Ti-6Al-4V: Characterisation, modelling and applications

On the mechanisms of superplasticity in Ti–6Al–4V

Electron backscatter diffraction: Strategies for reliable data acquisition and processing

Fracture toughness is one the most important parameters for design applications and performance assessment of WC–Co cemented carbides (hardmetals). Different from hardness, fracture toughness is co ...

/pdf/fracture-toughness-of-cemented-carbides-testing-method-and-42txyc70wu.pdf

Fracture toughness of cemented carbides: Testing method and microstructural effects

Accurate measurements of grain size are required to underpin development of models to predict properties, particularly of hybrid and multiphase materials. The conventional method for WC grain size determination in WC/Co is to use linear intercept measurements from light microscope or scanning electron microscopic images, usually requiring lengthy manual measurements, and subjective interpretation of grain boundary positions according to the level of etching and change in contrast. The possibilities offered by electron backscattering diffraction (EBSD) for improving the characterisation of both the WC and Co phase size, and contiguity between them, has been investigated. Samples covering a range of grain sizes have been examined by both EBSD and conventional methods to determine mean values and size distributions, with a special emphasis on the measurement of small grains. Diameters determined by both area (to give a circle equivalent diameter) and linear intercept from EBSD data are compared with the SEM image linear intercept method. It is shown that although the EBSD method is automated, great care must be taken in data analysis to identify and handle consistently small size values. If care is taken in the data handling then a good correlation can be shown between the EBSD and optical techniques.

Comparison of EBSD and conventional methods of grain size measurement of hardmetals

In an attempt to improve the material selection, design and reliability of rock bit WC-Co cemented carbides (hardmetals), an extensive and detailed study is conducted with the main goal of characterizing the fracture and fatigue crack growth (FCG) behavior of four hardmetal grades. Work includes basic microstructural and mechanical characterization of the materials, assessment of fracture toughness and FCG kinetics. It is found that rock bit cemented carbides exhibit relatively high fracture toughness values (between 17 and 20 MPa root m) in direct association with their specific microstructural characteristics, i.e. medium/coarse carbide grain size and medium cobalt content. The influence of microstructure on the measured crack growth mechanics under monotonic loading may be accounted by considering the effective operation of ductile ligament bridging and crack deflection as the prominent toughening mechanisms. Regarding FCG behavior, it is observed to exhibit a significant Km influence. Furthermore, relative increments in toughness are maintained, in terms of crack growth threshold, under cyclic loading. As a consequence, fatigue sensitivity for rock bit cemented carbides is found to be lower than that extrapolated from data reported for fine-grained grades. Crack growth resistance under cyclic loading for the hardmetals studied may be understood on the basis that prevalent toughening mechanisms (ductile ligament bridging and crack deflection) show distinct susceptibility to fatigue degradation and are thus critical in determining fatigue sensitivity. (C) 2014 Elsevier Ltd. All rights reserved.

Fracture and fatigue of rock bit cemented carbides: Mechanics and mechanisms of crack growth resistance under monotonic and cyclic loading

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Comparison of EBSD and conventional methods of grain size measurement of hardmetals

Fracture and fatigue of rock bit cemented carbides: Mechanics and mechanisms of crack growth resistance under monotonic and cyclic loading