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Crystals
Special Issues
Nondestructive Characterization and Evaluation of Crystalline Materials
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Nondestructive Characterization and Evaluation of Crystalline Materials

A special issue of Crystals (ISSN 2073-4352). This special issue belongs to the section "Inorganic Crystalline Materials".

Deadline for manuscript submissions: 10 October 2024 | Viewed by 1701

Special Issue Editors

Dr. Xiongbing Li

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Guest Editor
School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Interests: ultrasonic nondestructive evaluation; ultrasonic characterization of random media; ultrasonic phased array testing; ultrasound Imaging; nonlinear ultrasonic techniques; ultrasonic measurement model; signals analysis processing
Special Issues, Collections and Topics in MDPI journals
Dr. Anmin Yin

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Ningbo University, Ningbo, China
Interests: ultrasonic/laser ultrasonic nondestructive testing technology; microstructure and mechanical properties of metal materials; metal material processing technology and failure analysis
Dr. Yongfeng Song

E-Mail
Guest Editor
School of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou, China
Interests: ultrasonic scattering in polycrystals and oligocrystals; subwavelength flaw detection in strongly scattering material; multiscale microstructure characterization; ultrasonic numerical simulation and experimental measurement.
Dr. Jie Zhang

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Bristol, Bristol, China
Interests: ultrasonic NDE of layers, interface and imaging using arrays

Special Issue Information

Dear Colleagues,

The crystal structure and crystal orientation of materials are important characteristic parameters that reflect the microstructure of materials, and directly affect the mechanical and physical properties of materials. At present, the traditional measurement methods of crystal properties include metallography, SEM, EBSD, mechanical properties testing and so on. Although these methods have high accuracy, they cause irreversible damage to the material, and have complex processes, cumbersome operations, expensive equipment, and large space footprint, which cannot meet the needs for rapid and non-destructive testing of the material manufacturing industry. Therefore, it is of paramount importance to explore a non-destructive testing method with good adaptability and rapid acquisition of crystal properties of materials. Furthermore, since polycrystalline, oligocrystalline, monocrystalline, and quasicrystalline materials generally belong to random media, with random orientation or orientation distribution, stray grains, dislocations, and residual stresses, these bring continuous challenges for their non-destructive evaluation.

This Special Issue aims to address this pressing need by inviting researchers and practitioners to share their manuscripts that address new techniques and methods related to the non-destructive characterization of random media composed of crystals, ultimately contributing to improvements in material manufacturing processes and the development of high-performance materials. Potential areas of interest for submissions may include, but are not limited to, the development of novel non-destructive testing techniques, advancements in crystallographic analysis methods, innovations in imaging technologies, and the application of machine learning and artificial intelligence in non-destructive testing. Contributions that demonstrate the practicality, efficiency, and effectiveness of the proposed methods in real-world scenarios will be highly valued.

Dr. Xiongbing Li
Dr. Anmin Yin
Dr. Yongfeng Song
Dr. Jie Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Crystals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • nondestructive evaluation
  • random media characterization
  • ultrasonic/laser ultrasonics
  • signal processing approaches
  • inverse analysis
  • fundamental acousto-optic
  • wave propagation and scattering
  • simulation and theory
  • industrial applications

Published Papers (2 papers)

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Research

13 pages, 8438 KiB  
Article
The Microstructure Characterization of a Titanium Alloy Based on a Laser Ultrasonic Random Forest Regression
by Jinfeng Wu, Shuxian Yuan, Xiaogang Wang, Huaidong Chen, Fei Huang, Chang Yu, Yeqing He and Anmin Yin
Crystals 2024, 14(7), 607; https://doi.org/10.3390/cryst14070607 - 30 Jun 2024
Viewed by 373
Abstract
The traditional microstructure detecting methods such as metallography and electron backscatter diffraction are destructive to the sample and time-consuming and they cannot meet the needs of rapid online inspection. In this paper, a random forest regression microstructure characterization method based on a laser [...] Read more.
The traditional microstructure detecting methods such as metallography and electron backscatter diffraction are destructive to the sample and time-consuming and they cannot meet the needs of rapid online inspection. In this paper, a random forest regression microstructure characterization method based on a laser ultrasound technique is investigated for evaluating the microstructure of a titanium alloy (Ti-6Al-4V). Based on the high correlation between the longitudinal wave velocity of ultrasonic waves, the average grain size of the primary α phase, and the volume fraction of the transformed β matrix of the titanium alloy, and with the longitudinal wave velocity as the input feature and the average grain size of the primary α phase and the volume fraction of the transformed β matrix as the output features, prediction models for the average grain size of the primary α phase and the volume fraction of the transformed β matrix were developed based on a random forest regression. The results show that the mean values of the mean relative errors of the predicted mean grain size of the native α phase and the volume fraction of the transformed β matrix for the six samples in the two prediction models were 11.55% and 10.19%, respectively, and the RMSE and MAE obtained from both prediction models were relatively small, which indicates that the two established random forest regression models have a high prediction accuracy. Full article
(This article belongs to the Special Issue Nondestructive Characterization and Evaluation of Crystalline Materials)
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19 pages, 7927 KiB  
Article
Analysis and Mechanism Study of Residual Stress during the Spontaneous Crystallisation Process of Molten Titanium-Containing Blast Furnace Slag
by Daizheng Wang, Bingji Yan, Ziyu Dang, Peng Li, Hongwei Guo and Ziyu Song
Crystals 2024, 14(1), 70; https://doi.org/10.3390/cryst14010070 - 10 Jan 2024
Viewed by 922
Abstract
Molten titanium-containing blast furnace slag can be used to obtain cast stone materials by controlling a reasonable heat treatment system. The material acquired during this process showcases residual stress, which additionally impacts the macroscopic characteristics of the material. This article simulates the process [...] Read more.
Molten titanium-containing blast furnace slag can be used to obtain cast stone materials by controlling a reasonable heat treatment system. The material acquired during this process showcases residual stress, which additionally impacts the macroscopic characteristics of the material. This article simulates the process of manufacturing microcrystalline cast stones based on the self-crystallisation ability of titanium-containing products. This research employs X-ray diffraction to precisely and conveniently assess the residual stress of microcrystalline cast stones and investigates how viscosity and the thermal expansion coefficient influence the residual stress level. The study provides a theoretical foundation for explaining titanium-containing blast furnace slag and combines characterisation methods such as XRD (X-ray diffraction), SEM (Scanning electron microscope), DTA (Differential thermal analysis), and theoretical calculations such as Factpage and Fullprop to study the effect of the TiO2 content on the microstructure of self-crystallised mechanical characteristics of microcrystalline cast stones through residual stress. The results of the experiment indicate that as the TiO2 content in the system increases, the glass phase is reduced, the crystallinity improves, and the main crystal phase changes from a feldspar phase to a diopside phase. Furthermore, its viscosity, thermal expansion coefficient, and residual stress decrease while its corresponding compressive strength and bending strength increase. Full article
(This article belongs to the Special Issue Nondestructive Characterization and Evaluation of Crystalline Materials)
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