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Prior austenite grain boundary recognition in martensite microstructure based on deep learning
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作者 xuan-dong wang Nan Li +1 位作者 Hang Su Hui-min Meng 《Journal of Iron and Steel Research International》 SCIE EI CAS CSCD 2023年第5期1050-1056,共7页
Grain size determination is essential in producing and testing iron and steel materials.Grain size determination of martensitic steels usually requires etching with picric acid to reveal the prior austenite grain boun... Grain size determination is essential in producing and testing iron and steel materials.Grain size determination of martensitic steels usually requires etching with picric acid to reveal the prior austenite grain boundaries.However,picric acid is toxic and explosive and belongs to hazardous chemicals,which makes it difficult for laboratories and testing institutions to obtain.A new experimental method was developed to use Nital etchant instead of picric acid.The deep learning method was used to recognize the prior austenite grain boundaries in the etched martensite microstructure,and the grain size could be determined according to the recognition result.Firstly,the polished martensite specimen was etched twice with Nital etchant and picric acid,respectively,and the same position was observed using an optical microscope.The images of the martensitic structure and its prior austenite grain boundary label were obtained,and a data set was constructed.Secondly,based on this data set,a convolutional neural network model with a semantic segmentation function was trained,and the accuracy rate of the test set was 87.53%.Finally,according to the recognition results of the model,the grain size rating can be automatically determined or provide a reference for experimenters,and the difference between the automatic determination results and the measured results is about 0.5 level. 展开更多
关键词 Prior austenite grain boundary Microstructure etching Image recognition Deep learning
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Ultrasound extraction optimization, structural features, andantioxidant activity of polysaccharides from Tricholoma matsutake 被引量:18
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作者 Yun CHEN Xiu-ju DU +2 位作者 Yang ZHANG Xin-hua LIU xuan-dong wang 《Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)》 SCIE CAS CSCD 2017年第8期674-684,共11页
An ultrasonic-assisted technique was employed to extract crude polysaccharide from Tricholoma matsutake fruiting bodies. Single-factor tests and orthogonal experimental design(L_9(3~3)) were used to obtain the optimal... An ultrasonic-assisted technique was employed to extract crude polysaccharide from Tricholoma matsutake fruiting bodies. Single-factor tests and orthogonal experimental design(L_9(3~3)) were used to obtain the optimal extraction conditions. Results showed that the optimal parameters were as follows: ultrasonic temperature, 40 °C; ultrasonic time, 50 min; water to raw material ratio, 25 ml/g; ultrasonic frequency, 45 k Hz; and ultrasonic power, 100 W. Three novel T. matsutake polysaccharide(TMP) fractions(TMP30, TMP60, and TMP80) were isolated and purified from TMP by stepwise alcohol precipitation. Their preliminary structural features were determined by highperformance anion-exchange chromatography with pulsed-amperometric detection(HPAEC-PAD) and Fourier transform infrared spectrophotometer(FT-IR) analyses. Furthermore, their in vitro antioxidant activity was investigated in terms of a reducing power assay and the scavenging rates of 2,2-diphenyl-1-picrylhydrazyl(DPPH) and hydroxyl radicals. The order of the various fractions based on their antioxidant activity was TMP80>TMP>TMP60>TMP30. These findings suggested that novel polysaccharide fractions from T. matsutake, especially TMP80, could be promising active macromolecules for biomedical use. 展开更多
关键词 TRICHOLOMA matsutake POLYSACCHARIDE Orthogonal test design Ultrasound-assisted extraction Mono-saccharide composition Antioxidant activity
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