The use of image analysis for sintering investigations: The example of CeO2 doped with TiO2

Coster, Michel; Arnould, Xavier; Chermant, Jean‐Louis; Chermant, Liliane; Chartier, Thierry

doi:10.1016/j.jeurceramsoc.2004.09.003

Cited by 28 publications

(16 citation statements)

References 29 publications

(29 reference statements)

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“…Several works [11][12][13][14] have reported methods to extract microstructural information from polished surfaces of ceramic materials obtained through quantitative microscopy. This approach has many advantages when compared to other methods, such as reducing the data acquisition time, improving the accuracy and reproducibility, and a perfect linking to new concepts of digital microscopy.…”

Section: Introductionmentioning

confidence: 99%

Quantification of microstructural features in gadolinia-doped ceria containing co-additives by digital image analysis

Horovistiz¹,

Muccillo²

2011

Journal of the European Ceramic Society

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Section: Introductionmentioning

confidence: 99%

Quantification of microstructural features in gadolinia-doped ceria containing co-additives by digital image analysis

Horovistiz¹,

Muccillo²

2011

Journal of the European Ceramic Society

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“…Chermant et al [5] have been working with characterization of sintering through morphological analysis since the beginning of the 1980's [5,6,7]. Starting with metallurgical powders of convex particles in 1981, Chermant et al have developed image analysis methods based on the stereology principles as developed by strong names such as DeHoff et al [8], Serra [9].…”

Section: Introductionmentioning

confidence: 99%

“…More recent publications go into more advanced theory, such as relating the results to grain growth theory, performing simulations and investigation of sample homogeneity [7]. Focus lies on the sintering analysis and not full automation, and "images still need additional treatment" [7] which can be suspected to mean manual intervention in the preceding steps.…”

Section: Introductionmentioning

confidence: 99%

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Automated measurement of sintering degree in optical microscopy through image analysis of particle joins

Nellros

Thurley

Jönsson

et al. 2015

Pattern Recognition

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In general terms, sintering describes the bonding of particles into a more coherent structure, where joins form between packed particles, usually as a result of heating. Characterization of sintering is an important topic in the fields of metallurgy, steel, iron ore pellets, ceramics, and snow for understanding material properties and material strength. Characterization using image analysis has been applied in a number of these fields but is either semi-automatic, requiring human interaction in the analysis, or based on statistical sampling and stereology to characterize the sample. This paper presents a novel fully automatic image analysis algorithm to analyze and determine the degree of sintering based on analysis of the particle joins and structure. Quantitative image analysis of the sintering degree is demonstrated for samples of iron ore pellets but could be readily applied to other packed particle materials. Microscope images of polished cross-sections of iron ore pellets have been imaged in their entirety and automated analysis of hundreds of images has been performed. Joins between particles have been identified based on morphological image processing and features have been calculated based on the geometric properties and curvature of these joins. The features have been analyzed and determined to hold discriminative power based on a statistical evaluation using the Welch t-test and display properties consistent with sintering theory and results from traditional pellet diameter measurements on the heated samples.

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“…Sintering CeO 2 has already been investigated by Arnould (Arnould et al, 2001;Arnould, 2002;Arnould et al, 2002;Coster et al 2005), using segmented images, as described in these references.…”

Section: Introductionmentioning

confidence: 99%

A Microstructural Model by Space Tessellation for a Sintered Ceramic: Cerine

Coster¹,

Arnould²,

Chermant³

et al. 2011

Image Anal Stereol

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This paper deals with the use of probabilistic models such as Voronoi tessellation and the Johnson-Mehl model to simulate microstructures of monophased materials. Sintered cerine was chosen to test the various models. The values of morphological parameters measured, both on such models and real microstructures are in very good agreement. An extension for porous materials is also presented. This work shows that the probabilistic models are very well suited for the simulation and description of ceramic and granular microstructures.

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The use of image analysis for sintering investigations: The example of CeO2 doped with TiO2

Cited by 28 publications

References 29 publications

Quantification of microstructural features in gadolinia-doped ceria containing co-additives by digital image analysis

Quantification of microstructural features in gadolinia-doped ceria containing co-additives by digital image analysis

Automated measurement of sintering degree in optical microscopy through image analysis of particle joins

A Microstructural Model by Space Tessellation for a Sintered Ceramic: Cerine

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