Curved glass fiber–reinforced polymer (GFRP) composites are superior to alloy-steel pipes due to their excellent corrosive resistance properties, finding wide applications in the transportation of petrochemicals, chemical storage tanks, and power and water-treatment plants. Among the defects found in GFRP pipes, internal pitting or wall loss is one of the most severe, caused by material deterioration and the friction of small particles in the transfer fluid. This study investigates these in-service discontinuities using a pulsed thermal nondestructive evaluation technique. The paper focuses on the quantification of defect depth using the temperature peak contrast derivative and defect sizing using the full width at half maximum method. Further, the paper investigates the ability of pulsed thermography to estimate pitting or wall-loss defects at various depths and sizes through simulation and experimentation. Thermographic signal reconstruction images are used for quantification of defects at a deeper depth. The results of the present study are then compared with well-established ultrasonic C-scan results.
{"title":"Characterization of Wall-Loss Defects in Curved GFRP Composites Using Pulsed Thermography","authors":"R. Gomathi, M. Ashok, M. Menaka, B. Venkatraman","doi":"10.32548/2022.me-04160","DOIUrl":"https://doi.org/10.32548/2022.me-04160","url":null,"abstract":"Curved glass fiber–reinforced polymer (GFRP) composites are superior to alloy-steel pipes due to their excellent corrosive resistance properties, finding wide applications in the transportation of petrochemicals, chemical storage tanks, and power and water-treatment plants. Among the defects found in GFRP pipes, internal pitting or wall loss is one of the most severe, caused by material deterioration and the friction of small particles in the transfer fluid. This study investigates these in-service discontinuities using a pulsed thermal nondestructive evaluation technique. The paper focuses on the quantification of defect depth using the temperature peak contrast derivative and defect sizing using the full width at half maximum method. Further, the paper investigates the ability of pulsed thermography to estimate pitting or wall-loss defects at various depths and sizes through simulation and experimentation. Thermographic signal reconstruction images are used for quantification of defects at a deeper depth. The results of the present study are then compared with well-established ultrasonic C-scan results.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43429942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
While various common alloys, such as steels, titaniums, and more recently aluminums, have been tested and inspected using X-ray fluorescence spectroscopy (XRF) for decades, uncommon and niche alloys can produce surprising and unusual results. The ability to identify the base metal, major alloying elements, and trace materials in these alloys is critical to XRF testing and inspection procedures. Modern XRF instruments and software can quickly and easily characterize standard and common alloys, such as low-carbon steel, grade 5 titanium, and 6000 series aluminum; detected signals from the metals are generally discrete and strongly pronounced. Less common alloys, such as nickel superalloys and uraniums, present a greater analytical hurdle for rapid on-site testing, grading, and inspection. These exotic materials contain either weaker signals from the alloying elements or nonunique signatures, preventing accurate quantification. Standardization adjustments through software improvements increase the testing accuracy for these uncommon alloys, bringing their results in line with those from more traditional alloys. By modulating the detection energies of interest, the robust calculation can greatly surpass standard, out-of-the-box performance without the need for any inspector input. These improvements can provide greater inspection accuracy on a wider variety of rare and valuable alloys into the future.
{"title":"Improvement of Exotic Material Verification Using XRF","authors":"Joshua H. Litofsky","doi":"10.32548/2022.me-04268","DOIUrl":"https://doi.org/10.32548/2022.me-04268","url":null,"abstract":"While various common alloys, such as steels, titaniums, and more recently aluminums, have been tested and inspected using X-ray fluorescence spectroscopy (XRF) for decades, uncommon and niche alloys can produce surprising and unusual results. The ability to identify the base metal, major alloying elements, and trace materials in these alloys is critical to XRF testing and inspection procedures. Modern XRF instruments and software can quickly and easily characterize standard and common alloys, such as low-carbon steel, grade 5 titanium, and 6000 series aluminum; detected signals from the metals are generally discrete and strongly pronounced. Less common alloys, such as nickel superalloys and uraniums, present a greater analytical hurdle for rapid on-site testing, grading, and inspection. These exotic materials contain either weaker signals from the alloying elements or nonunique signatures, preventing accurate quantification. Standardization adjustments through software improvements increase the testing accuracy for these uncommon alloys, bringing their results in line with those from more traditional alloys. By modulating the detection energies of interest, the robust calculation can greatly surpass standard, out-of-the-box performance without the need for any inspector input. These improvements can provide greater inspection accuracy on a wider variety of rare and valuable alloys into the future.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49132764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chenggeng Li, Zhenhua Chen, Wei-bing Chen, Chao-feng Lu
The impact damage imposed on carbon fiber–reinforced polymer (CFRP) materials used in aircraft fuselage may seriously affect flight safety. An ultrasonic testing method can be used to inspect for damage; however, in some cases of invisible or barely visible impact damage, linear ultrasound may not provide a clear indication of the underlying damage. Accordingly, a nonlinear Lamb wave technique was developed in this study to detect invisible impact damage (IID). First, a nonlinear Lamb wave testing platform was set, as well as damage areas with different impact energies. Second, the anisotropic propagation of Lamb waves was studied to determine the wave mode and the distribution of the transducers, and the linear parameters of the Lamb waves were determined. Last, three types of characteristic parameters of nonlinear Lamb waves were obtained for damage detection. As revealed from the results, the linear ultrasonic parameters of A0 mode Lamb waves can be applied to the detection of macro surface cracks, and the frequency shift, relative nonlinearity coefficient (RNC), and fluctuation coefficient of RNCs are highly sensitive to the detection of IID. Thus, a combination of nonlinear S0 Lamb waves and linear A0 Lamb waves can be used for IID and macro surface crack detection, respectively.
{"title":"Study on Nonlinear Lamb Wave Test for Invisible Impact Damage on CFRP Laminates","authors":"Chenggeng Li, Zhenhua Chen, Wei-bing Chen, Chao-feng Lu","doi":"10.32548/2022.me-04191","DOIUrl":"https://doi.org/10.32548/2022.me-04191","url":null,"abstract":"The impact damage imposed on carbon fiber–reinforced polymer (CFRP) materials used in aircraft fuselage may seriously affect flight safety. An ultrasonic testing method can be used to inspect for damage; however, in some cases of invisible or barely visible impact damage, linear ultrasound may not provide a clear indication of the underlying damage. Accordingly, a nonlinear Lamb wave technique was developed in this study to detect invisible impact damage (IID). First, a nonlinear Lamb wave testing platform was set, as well as damage areas with different impact energies. Second, the anisotropic propagation of Lamb waves was studied to determine the wave mode and the distribution of the transducers, and the linear parameters of the Lamb waves were determined. Last, three types of characteristic parameters of nonlinear Lamb waves were obtained for damage detection. As revealed from the results, the linear ultrasonic parameters of A0 mode Lamb waves can be applied to the detection of macro surface cracks, and the frequency shift, relative nonlinearity coefficient (RNC), and fluctuation coefficient of RNCs are highly sensitive to the detection of IID. Thus, a combination of nonlinear S0 Lamb waves and linear A0 Lamb waves can be used for IID and macro surface crack detection, respectively.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46375850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yavuz Selim Balcioglu, B. Sezen, M. S. Gok, Sezai Tunca
Intelligent production requires improved data analytics and better technological possibilities to improve system performance and decision making. With the widespread use of the machine learning process, a growing need has arisen for processing extensive production data, equipped with high volumes, high speed, and high diversity. At this point, deep learning provides advanced analysis tools for processing and analyzing extensive production data. The deep convolutional neural network (DCNN) displays state-of-the-art performance on many grounds, including metal manufacturing surface defect detection. However, there is still space for improving the defect detection performance over generic DCNN models. The proposed approach performed better than the associated methods in the particular area of surface crack detection. The defect zones of disjointed results are classified into their unique classes by a DCNN. The experimental outcomes prove that this method meets the durability and efficiency requirements for metallic object defect detection. In time, it can also be extended to other detection methods. At the same time, the study will increase the accuracy quality of the features that can make a difference in the deep learning method for the detection of surface defects.
{"title":"Image Processing with Deep Learning: Surface Defect Detection of Metal Gears through Deep Learning","authors":"Yavuz Selim Balcioglu, B. Sezen, M. S. Gok, Sezai Tunca","doi":"10.32548/2022.me-04230","DOIUrl":"https://doi.org/10.32548/2022.me-04230","url":null,"abstract":"Intelligent production requires improved data analytics and better technological possibilities to improve system performance and decision making. With the widespread use of the machine learning process, a growing need has arisen for processing extensive production data, equipped with high volumes, high speed, and high diversity. At this point, deep learning provides advanced analysis tools for processing and analyzing extensive production data. The deep convolutional neural network (DCNN) displays state-of-the-art performance on many grounds, including metal manufacturing surface defect detection. However, there is still space for improving the defect detection performance over generic DCNN models. The proposed approach performed better than the associated methods in the particular area of surface crack detection. The defect zones of disjointed results are classified into their unique classes by a DCNN. The experimental outcomes prove that this method meets the durability and efficiency requirements for metallic object defect detection. In time, it can also be extended to other detection methods. At the same time, the study will increase the accuracy quality of the features that can make a difference in the deep learning method for the detection of surface defects.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47712180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article is a companion piece for my first article published in the April 2020 issue of Materials Evaluation (https://doi.org/10.32548/2020.me-04136). While that article provided a broad overview of neutron radiography, this article delves deeper into the mechanics of neutron radiation and provides more examples of its applications in the field of nondestructive testing.
{"title":"Mechanics of Neutron Radiation and Applications in the Field","authors":"Willow Ascenzo","doi":"10.32548/2022.me-04265","DOIUrl":"https://doi.org/10.32548/2022.me-04265","url":null,"abstract":"This article is a companion piece for my first article published in the April 2020 issue of Materials Evaluation (https://doi.org/10.32548/2020.me-04136). While that article provided a broad overview of neutron radiography, this article delves deeper into the mechanics of neutron radiation and provides more examples of its applications in the field of nondestructive testing.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42459914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In 1931, a professional photographer named Giuseppe Enri pointed his camera at a piece of cloth called the Shroud of Turin. How was this image formed? When was it made? Who made it? Is this an image of a real person? Could this be an image of the man known as Jesus Christ? Could this be the authentic burial cloth of Jesus? These are just a few of the questions that arise. This article provides an overview of the Shroud, including its images, history, materials, and previous testing. It also includes the author’s hypothesis to explain the main mysteries of the Shroud, including image formation, carbon dating, and features of the blood on the Shroud. The purpose of this article is to encourage the development of a program for future testing of the Shroud. There are rumors the Shroud may go on exhibition in Turin, Italy, in 2025. To help obtain authorization for further scientific testing possibly following the exhibition in 2025, a comprehensive testing program should be developed for the Shroud to take advantage of advances in technology since the last extensive testing in 1978.
{"title":"The Mysteries of the Shroud of Turin","authors":"R. Rucker","doi":"10.32548/2022.me-02022","DOIUrl":"https://doi.org/10.32548/2022.me-02022","url":null,"abstract":"In 1931, a professional photographer named Giuseppe Enri pointed his camera at a piece of cloth called the Shroud of Turin. How was this image formed? When was it made? Who made it? Is this an image of a real person? Could this be an image of the man known as Jesus Christ? Could this be the authentic burial cloth of Jesus? These are just a few of the questions that arise. This article provides an overview of the Shroud, including its images, history, materials, and previous testing. It also includes the author’s hypothesis to explain the main mysteries of the Shroud, including image formation, carbon dating, and features of the blood on the Shroud. The purpose of this article is to encourage the development of a program for future testing of the Shroud. There are rumors the Shroud may go on exhibition in Turin, Italy, in 2025. To help obtain authorization for further scientific testing possibly following the exhibition in 2025, a comprehensive testing program should be developed for the Shroud to take advantage of advances in technology since the last extensive testing in 1978.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47487682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Informatization is defined as the process by which information technologies, such as the World Wide Web and other communication technologies, have transformed economic and social relations to such an extent that cultural and economic barriers are minimized. What does this mean for nondestructive testing and evaluation (NDT/E)? In short: informatization in NDT and NDE has happened and will continue to happen, independent of whether individuals or companies like it or not. However, we can shape it—together.
{"title":"NDE Outlook: Informatization of NDT and NDE","authors":"Johannes Ludwig Vrana","doi":"10.32548/2022.me-800122","DOIUrl":"https://doi.org/10.32548/2022.me-800122","url":null,"abstract":"Informatization is defined as the process\u0000by which information technologies,\u0000such as the World Wide Web and other\u0000communication technologies, have\u0000transformed economic and social relations\u0000to such an extent that cultural and\u0000economic barriers are minimized.\u0000What does this mean for nondestructive\u0000testing and evaluation (NDT/E)? In\u0000short: informatization in NDT and NDE\u0000has happened and will continue to\u0000happen, independent of whether individuals\u0000or companies like it or\u0000not. However, we can shape\u0000it—together.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49464629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.32548/10.32548/2022.me-04232
Yan Wang, Lijun Chen, Nairan Wang, Jie Gu
In order to improve the accuracy of damage source identification in concrete based on acoustic emission testing (AE) and neural networks, and locating and repairing the damage in a practical roller compacted concrete (RCC) dam, a multilevel AE processing platform based on wavelet energy spectrum analysis, principal component analysis (PCA), and a neural network is proposed. Two data sets of 15 basic AE parameters and 23 AE parameters added on the basis of the 15 basic AE parameters were selected as the input vectors of a basic parameter neural network and a wavelet neural network, respectively. Taking the measured tensile data of an RCC prism sample as an example, the results show that compared with the basic parameter neural network, the wavelet neural network achieves a higher accuracy and faster damage source identification, with an average recognition rate of 8.2% and training speed of about 33%.
{"title":"Concrete Damage Identification based on Acoustic Emission and Wavelet Neural Network","authors":"Yan Wang, Lijun Chen, Nairan Wang, Jie Gu","doi":"10.32548/10.32548/2022.me-04232","DOIUrl":"https://doi.org/10.32548/10.32548/2022.me-04232","url":null,"abstract":"In order to improve the accuracy of damage source identification in concrete based on acoustic emission testing (AE) and neural networks, and locating and repairing the damage in a practical roller compacted concrete (RCC) dam, a multilevel AE processing platform based on wavelet energy spectrum analysis, principal component analysis (PCA), and a neural network is proposed. Two data sets of 15 basic AE parameters and 23 AE parameters added on the basis of the 15 basic AE parameters were selected as the input vectors of a basic parameter neural network and a wavelet neural network, respectively. Taking the measured tensile data of an RCC prism sample as an example, the results show that compared with the basic parameter neural network, the wavelet neural network achieves a higher accuracy and faster damage source identification, with an average recognition rate of 8.2% and training speed of about 33%.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47131900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates delamination damage mechanisms during the double cantilever beam standard test using the strain energy release rate. The acoustic emission parameter is used to replace the original calculation method of measuring crack length to predict delamination. For this purpose, 24-layer glass/epoxy multidirectional specimens with different layups, and interface orientations of 0°, 30°, 45°, and 60°, were fabricated based on ASTM D5528 (2013). Acoustic emission testing (AE) is used to detect the damage mechanism of composite multidirectional laminates (combined with microscopic real-time observation), and it is verified that the strain energy release rate can be used as a criterion for predicting delamination damage in composite materials. By comparing the AE results with the delamination expansion images observed by microvisualization in real time, it is found that the acoustic emission parameters can predict the damage of laminates earlier. Based on the data inversion of the acoustic emission parameters of the strain energy release rate, it is found that the strain energy release rate of the specimens with different fiber interface orientations is consistent with the original calculated results.
{"title":"Predicting the Delamination Mechanisms of Multidirectional Laminates Using the Energy Release Rate Obtained from AE Monitoring","authors":"Ying-gang Liu, Jiang Peng, Wei Li, Chang-yuan Yang, Ping Sun, Xiaowei Yan","doi":"10.32548/10.32548/2022.me-04254","DOIUrl":"https://doi.org/10.32548/10.32548/2022.me-04254","url":null,"abstract":"This study investigates delamination damage mechanisms during the double cantilever beam standard test using the strain energy release rate. The acoustic emission parameter is used to replace the original calculation method of measuring crack length to predict delamination. For this purpose, 24-layer glass/epoxy multidirectional specimens with different layups, and interface orientations of 0°, 30°, 45°, and 60°, were fabricated based on ASTM D5528 (2013). Acoustic emission testing (AE) is used to detect the damage mechanism of composite multidirectional laminates (combined with microscopic real-time observation), and it is verified that the strain energy release rate can be used as a criterion for predicting delamination damage in composite materials. By comparing the AE results with the delamination expansion images observed by microvisualization in real time, it is found that the acoustic emission parameters can predict the damage of laminates earlier. Based on the data inversion of the acoustic emission parameters of the strain energy release rate, it is found that the strain energy release rate of the specimens with different fiber interface orientations is consistent with the original calculated results.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46534416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.32548/10.32548/2022.me-800122_2
Albert Wenzig
When radiographing an austenitic stainless steel weld with an appreciable weld deposit size, selecting a low radiographic kilovoltage (keV) can contribute to producing a radiographic indication that is not an imperfection. The contributors to this mottled condition are both radiographical and metallurgical. Electrons from low keV can diffract or absorb when penetrating through the dendritic grain structure of a weld. The increase in keV, or using gamma ray–equivalent isotopes, produces a marked change in electron output and penetration in material.
{"title":"Assessing Mottled Indications when Digitally Radiographing Austenitic Stainless Steel Welds","authors":"Albert Wenzig","doi":"10.32548/10.32548/2022.me-800122_2","DOIUrl":"https://doi.org/10.32548/10.32548/2022.me-800122_2","url":null,"abstract":"When radiographing an austenitic stainless steel weld with an appreciable weld deposit size, selecting a low radiographic kilovoltage (keV) can contribute to producing a radiographic indication that is not an imperfection. The contributors to this mottled condition are both radiographical and metallurgical. Electrons from low keV can diffract or absorb when penetrating through the dendritic grain structure of a weld. The increase in keV, or using gamma ray–equivalent isotopes, produces a marked change in electron output and penetration in material.","PeriodicalId":49876,"journal":{"name":"Materials Evaluation","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48186178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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