Evidence map›Paper›PMID 39769659›Full record

ArticleMaterials (Basel, Switzerland)2024

Quantitative Indicators of Microstructure and Texture Heterogeneity in Polycrystalline System.

Jurij J Sidor

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Jurij J SidorEötvös Lorand University (ELTE), Faculty of Informatics, Savaria Institute of Technology, Karolyi Gaspar tér 4, 9700 Szombathely, Hungary.ORCID 0000-0001-7521-6963

Funding

Ministry of Culture and Innovation of Hungary, the National Research, Devel-opment and Innovation Fund TKP2021-NVA-29
6 · The paper itself

Abstract

The microstructural features of polycrystals determine numerous properties, whereas the evolution of crystallographic texture is responsible for the anisotropy of particular properties. Therefore, it is of crucial importance to find proper quantitative indicators, which reflect the nature of microstructure and texture characteristics. This is partially performed by the assessment of the average grain size and texture intensity that provide basic information on the microstructural features evolved; however, often, the basic quantitative indicators are not capable of revealing the complete microstructural state especially when the system is highly heterogeneous. This contribution presents various methods to assess the degree of microstructural heterogeneity, while the crystallographic aspect of microstructure evolution is characterized by several indicators of texture heterogeneity. Numerous synthetic microstructures with normal, lognormal, and bimodal grain size distributions as well as their combinations are analyzed to evaluate the applicability of the methods presented in this study. The quantitative indicators described in the frame of this contribution are likewise tested on experimentally observed microstructures. It is shown that the derived coefficients of microstructure heterogeneity correlate well with the standard deviation in grain size distribution, Gini, and Hoover coefficients, while the quantitative measures of texture heterogeneity are capable of revealing hidden aspects of microstructure evolution.

Indexed as

heterogeneitymicrostructuretexture

Identifiers

PMID39769659
PMCPMC11728279

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.