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167 results on '"Fang, Lichao"'

1. Comment on 'Comments regarding 'Transonic dislocation propagation in diamond' by Katagiri, et al. (Science 382, 69-72, 2023)' by Hawreliak, et al. (arXiv:2401.04213)

Author

Katagiri, Kento, Pikuz, Tatiana, Fang, Lichao, Albertazzi, Bruno, Egashira, Shunsuke, Inubushi, Yuichi, Kamimura, Genki, Kodama, Ryosuke, Koenig, Michel, Kozioziemski, Bernard, Masaoka, Gooru, Miyanishi, Kohei, Nakamura, Hirotaka, Ota, Masato, Rigon, Gabriel, Sakawa, Youichi, Sano, Takayoshi, Schoofs, Frank, Smith, Zoe J., Sueda, Keiichi, Togashi, Tadashi, Vinci, Tommaso, Wang, Yifan, Yabashi, Makina, Yabuuchi, Toshinori, Dresselhaus-Marais, Leora E., and Ozaki, Norimasa

Subjects
Condensed Matter - Materials Science
Abstract

In their comment (1), Hawreliak et al. claims that our observation of stacking fault formation and transonic dislocation propagation in diamond (2) is not valid as they interpret the observed features as cracks. In this response letter, we describe our rationale for interpreting the observed features as stacking faults. We also address other points raised in their comments, including the clarifications of how the results of Makarov et al. (3) are not in conflict with our study., Comment: Comment on arXiv:2401.04213. 10 pages, 2 figures

Published
2024

2. Dark-Field X-ray Microscopy for 2D and 3D imaging of Microstructural Dynamics at the European X-ray Free Electron Laser

Author

Irvine, Sara J., Katagiri, Kento, Ræder, Trygve M., Boesenberg, Ulrike, Chalise, Darshan, Stanton, Jade I., Pal, Dayeeta, Hallmann, Jörg, Ansaldi, Gabriele, Brauße, Felix, Eggert, Jon H., Fang, Lichao, Folsom, Eric, Haubro, Morten, Holstad, Theodor S., Madsen, Anders, Möller, Johannes, Nielsen, Martin M., Poulsen, Henning F., Pudell, Jan-Etienne, Rodriguez-Fernandez, Angel, Schoofs, Frank, Seiboth, Frank, Wang, Yifan, Jo, Wonhyuk, Youssef, Mohamed, Zozulya, Alexey, Haldrup, Kristoffer, and Dresselhaus-Marais, Leora E.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract

Dark field X-ray microscopy (DXFM) can visualize microstructural distortions in bulk crystals. Using the femtosecond X-ray pulses generated by X-ray free-electron lasers (XFEL), DFXM can achieve sub-{\mu}m spatial resolution and <100 fs time resolution simultaneously. In this paper, we demonstrate ultrafast DFXM measurements at the European XFEL to visualize an optically-driven longitudinal strain wave propagating through a diamond single crystal. We also present two DFXM scanning modalities that are new to the XFEL sources: spatially 3D and 2D axial-strain scans with sub-{\mu}m spatial resolution. With this progress in XFEL-based DFXM, we discuss new opportunities to study multi-timescale spatio-temporal dynamics of microstructures.

Published
2023

3. Transonic Dislocation Propagation in Diamond

Author

Katagiri, Kento, Pikuz, Tatiana, Fang, Lichao, Albertazzi, Bruno, Egashira, Shunsuke, Inubushi, Yuichi, Kamimura, Genki, Kodama, Ryosuke, Koenig, Michel, Kozioziemski, Bernard, Masaoka, Gooru, Miyanishi, Kohei, Nakamura, Hirotaka, Ota, Masato, Rigon, Gabriel, Sakawa, Youichi, Sano, Takayoshi, Schoofs, Frank, Smith, Zoe J., Sueda, Keiichi, Togashi, Tadashi, Vinci, Tommaso, Wang, Yifan, Yabashi, Makina, Yabuuchi, Toshinori, Dresselhaus-Marais, Leora E., and Ozaki, Norimasa

Subjects
Condensed Matter - Materials Science
Abstract

The motion of line defects (dislocations) has been studied for over 60 years but the maximum speed at which they can move is unresolved. Recent models and atomistic simulations predict the existence of a limiting velocity of dislocation motions between the transonic and subsonic ranges at which the self-energy of dislocation diverges, though they do not deny the possibility of the transonic dislocations. We use femtosecond x-ray radiography to track ultrafast dislocation motion in shock-compressed single-crystal diamond. By visualizing stacking faults extending faster than the slowest sound wave speed of diamond, we show the evidence of partial dislocations at their leading edge moving transonically. Understanding the upper limit of dislocation mobility in crystals is essential to accurately model, predict, and control the mechanical properties of materials under extreme conditions.

Published
2023

6. Data driven analysis of thermal simulations, microstructure and mechanical properties of Inconel 718 thin walls deposited by metal additive manufacturing

Author

Fang, Lichao, Cheng, Lin, Glerum, Jennifer A., Bennett, Jennifer, Cao, Jian, and Wagner, Gregory J.

Subjects
Physics - Applied Physics
Abstract

The extreme and repeated temperature variation during additive manufacturing of metal parts has a large effect on the resulting material microstructure and properties. The ability to accurately predict this temperature field in detail, and relate it quantitatively to structure and properties, is a key step in predicting part performance and optimizing process design. In this work, a finite element simulation of the Directed Energy Deposition (DED) process is used to predict the space- and time-dependent temperature field during the multi-layer build process for Inconel 718 walls. The thermal model is validated using the dynamic infrared (IR) images captured in situ during the DED builds, showing good agreement with experimental measurements. The relationship between predicted cooling rate, microstructural features, and mechanical properties is examined, and cooling rate alone is found to be insufficient in giving quantitative property predictions. Because machine learning offers an efficient way to identify important features from series data, we apply a 1D convolutional neural network (CNN) data-driven framework to automatically extract the dominant predictive features from simulated temperature history. The relationship between the CNN-extracted features and the mechanical properties is studied. To interpret how CNN performs in intermediate layers, we visualize the extracted features produced on each convolutional layer by a trained CNN. Our results show that the results predicted by the CNN agree well with experimental measurements and give insights into physical mechanisms of microstructure evolution and mechanical properties.

Published
2021

14. Preparation and effectiveness evaluation of DNA methylation photoelectrochemical sensor based on 3-D rigid DNA bridge nanoprobes

Author

ZHU Chuiyu, HUANG Hui, LI Yan, FANG Lichao, and WANG Lina

Subjects
dna methylation, bridge dna nanoprobes, photoelectrochemistry, biosensing techniques, Medicine (General), R5-920
Abstract

Objective To construct a photoelectrochemical (PEC) sensor based on a 3-dimensional (3-D) rigid DNA bridge nanoprobe for the analysis of DNA methylation sites. Methods Titanium dioxide (TiO2) suspension was dropped onto the surface of ITO electrode to form a thin film; gold nanoparticles (AuNPs) were deposited on the TiO2 nanofilm by potentiometric stripping, and then the 3-D rigid DNA bridge probe was fixed to the electrode surface by Au-S binding. Furthermore, the 5-methylcytosine antibody and cadmium telluride quantum dots (Ab-CdTe QDs) conjugate were prepared. In the presence of the target sequence, the 5-methylcytosine specifically bound to the antibody, and made Ab-CdTe QDs connect to the electrode surface, and then a co-sensitized structure with AuNPs/TiO2 was formed to enhance the photoelectric signal. The PEC signal response of the sensor was measured in phosphate buffer (PBS) containing L-ascorbic acid (AA). Results 3-D rigid DNA bridge nanoprobes were successfully prepared. The optimal concentration of TiO2 suspension was 4 mg/mL, and that of 5-methylcytosine antibody was 10 μg/ml. Under the optimal experimental conditions, 5 electrodes prepared under the same condition were tested parallelly, and the relative standard deviation (RSD) was only 1.8%. After 4 weeks, the photocurrent of the sensor still maintained 92.5% of the initial value. Meanwhile, the sensor presented good selectivity to the target sequence, and the photoelectric response value exhibited a linear relationship with the number of DNA methylation sites. The regression equation was ΔI=-0.004 7+4.011 4×N, and the coefficient of determination R2 was 0.999 7. Conclusion The developed photoelectrochemical sensor involves excellent stability and specificity, and can be used for quantitative detection of multi-site DNA methylation.

Published
2022
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15. Method of Wheel Out-of-Roundness Detection Based on POVMD and Multinuclear LS-SVM

Author

Fang, Lichao, Li, Shibo, Dai, Wang, Zhang, Yong, Xing, Zongyi, Han, Yulin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Baoming, editor, Liu, Zhigang, editor, Diao, Lijun, editor, and An, Min, editor

Published
2020
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16. Research on Monitoring Technology of Pantograph Sliding Plate Abrasion Based on Sub-pixel Edge Extraction

Author

Dai, Wang, Su, Zhaoyi, Fang, Lichao, Li, Shibo, Zhang, Yong, Xing, Zongyi, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Baoming, editor, Liu, Zhigang, editor, Diao, Lijun, editor, and An, Min, editor

Published
2020
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17. Research on Train Energy-Saving Optimization Based on Parallel Immune Particle Swarm Optimization

Author

Li, Shibo, Dai, Wang, Fang, Lichao, Zhang, Yong, Xing, Zongyi, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Baoming, editor, Liu, Zhigang, editor, Diao, Lijun, editor, and An, Min, editor

Published
2020
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24. Photoelectrochemical sensor based on AuNPs@WO3@TpPa-1-COF for quantification of DNA methylation levels.

Author

Liu, Huamin, Li, Chenghong, Wang, Lina, Fang, Lichao, Huang, Hui, Deng, Jun, Hu, Yue, Li, Mimi, Ran, Xiaoping, Li, Lulu, and Zheng, Junsong

Subjects
DNA methylation, AMPLIFICATION reactions, GOLD nanoparticles, TUNGSTEN trioxide, ELECTRON donors, LINEAR equations
Abstract

A "signal-off" photoelectrochemical (PEC) sensing platform has been designed for the ultrasensitive detection of DNA methylation levels and multiple methylated sites. The platform employs tungsten trioxide and TpPa-1-COF loaded by gold nanoparticle (AuNPs@WO3@TpPa-1-COF) composite material as the photoactive component and p-type reduced graphene (rGO) as an efficient quencher. The PEC signal of AuNPs@WO3@TpPa-1-COF composite is effectively quenched in the presence of p-type rGO, because p-type rGO can compete with AuNPs@WO3@TpPa-1-COF to deplete light energy and electron donors. In addition, a hybrid strand reaction (HCR) amplification strategy fixes more target DNA and then combines with rGO-modified anti-5-methylcytosine antibody to facilitate ultrasensitive DNA methylation detection. Under optimal conditions, DNA methylation can be measured within a linear concentration range of 10–14 to 10–8 M, with an exceptionally low detection limit of 0.19 fM (S/N = 3). At the same time, the platform can conduct quantitative determination of multi-site methylation, with the linear equation △I = 44.19LogA + 61.43, and the maximum number of methylation sites is 5. The sensor demonstrates high sensitivity, excellent selectivity, and satisfactory stability. Furthermore, the proposed signal-off PEC strategy was successfully employed to detect DNA methylation in spiked human serum samples, with recoveries ranging from 93.17 to 107.28% and relative standard deviation (RSD) ranging from 1.15 to 5.49%. [ABSTRACT FROM AUTHOR]

Published
2024
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25. Transonic dislocation propagation in diamond

Author

Katagiri, Kento, primary, Pikuz, Tatiana, additional, Fang, Lichao, additional, Albertazzi, Bruno, additional, Egashira, Shunsuke, additional, Inubushi, Yuichi, additional, Kamimura, Genki, additional, Kodama, Ryosuke, additional, Koenig, Michel, additional, Kozioziemski, Bernard, additional, Masaoka, Gooru, additional, Miyanishi, Kohei, additional, Nakamura, Hirotaka, additional, Ota, Masato, additional, Rigon, Gabriel, additional, Sakawa, Youichi, additional, Sano, Takayoshi, additional, Schoofs, Frank, additional, Smith, Zoe J., additional, Sueda, Keiichi, additional, Togashi, Tadashi, additional, Vinci, Tommaso, additional, Wang, Yifan, additional, Yabashi, Makina, additional, Yabuuchi, Toshinori, additional, Dresselhaus-Marais, Leora E., additional, and Ozaki, Norimasa, additional

Published
2023
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32. An Improved MAHAKIL Oversampling Method for Imbalanced Dataset Classification

Author

Zuo Tingting, Fang Lichao, Jun Li, Zongyi Xing, and Yong Zhang

Subjects
MAHAKIL algorithm, General Computer Science, Crossover, 02 engineering and technology, K-means cluster, 020204 information systems, Genetic algorithm, 0202 electrical engineering, electronic engineering, information engineering, Oversampling, General Materials Science, Cluster analysis, Mahalanobis distance, business.industry, General Engineering, Pattern recognition, Classification, Data set, Euclidean distance, Statistical classification, ComputingMethodologies_PATTERNRECOGNITION, oversampling, imbalanced dataset, 020201 artificial intelligence & image processing, Artificial intelligence, lcsh:Electrical engineering. Electronics. Nuclear engineering, business, lcsh:TK1-9971
Abstract

In the process of imbalanced dataset classification, traditional oversampling technologies do not take into the account of the distribution characteristics of data sets, which easily results in low classification accuracy of positive samples. In order to improve the recognition rate of positive samples, the algorithm combining the K-means clustering with the MAHAKIL oversampling is proposed in this article. Firstly, the K-means clustering algorithm is used to divide the positive samples into K clusters. The samples in each cluster are then divided into two initial populations according to the magnitude of the Mahalanobis distance. Finally, the crossover operator of the genetic algorithm is used to continuously synthesize new data samples to balance the data set. The experimental results show that when K-means MAHAKIL oversampling algorithm is combined with different classification algorithms, it can achieve better classification performance, which verifies the effectiveness of the algorithm.

Published
2021

34. Photoelectrochemical Biosensor Based on 3d Bridged DNA Nanoprobe and Dual-Signal Amplification for Ultra-Sensitive Detection of DNA 5-Methylcytosine

Author

zheng, junsong, primary, Zhu, Chuiyu, additional, Tian, Xiao, additional, Li, Qiuyan, additional, Wang, Lina, additional, Liu, Huamin, additional, Li, Chenghong, additional, Zahid, Kashif Rafiq, additional, Wu, Chunmei, additional, Huang, Hui, additional, Fang, Lichao, additional, Huang, Qiyuan, additional, Liu, Feixue, additional, Deng, Jun, additional, Liang, Wenbin, additional, and Zeng, Tao, additional

Published
2022
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35. Ultrasensitive Photoelectrochemical Biosensor for DNA 5-Methylcytosine Analysis Based on Co-Sensitization Strategy Combined with Bridged DNA Nanoprobe

Author

Zhu, Chuiyu, primary, Tian, Xiao, additional, Li, Qiuyan, additional, Dai, Zichang, additional, Wang, Lina, additional, Liu, Huamin, additional, Li, Chenghong, additional, Zahid, Kashif Rafiq, additional, Wu, Chunmei, additional, Huang, Hui, additional, Fang, Lichao, additional, Huang, Qiyuan, additional, Liu, Feixue, additional, Deng, Jun, additional, Li, Yan, additional, Zeng, Tao, additional, and zheng, junsong, additional

Published
2022
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39. Method of Wheel Out-of-Roundness Detection Based on POVMD and Multinuclear LS-SVM

Author

Han Yulin, Dai Wang, Fang Lichao, Li Shibo, Zongyi Xing, and Yong Zhang

Subjects
Computer science, Directed acyclic graph, Collision, GeneralLiterature_MISCELLANEOUS, Roundness (object), Vibration, Support vector machine, symbols.namesake, ComputingMethodologies_PATTERNRECOGNITION, Safe operation, Gaussian function, symbols, Train, Algorithm, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

With the continuous increase of the running mileage and speed of the train, more and more wheels become out-of-roundness due to the collision and friction between the wheels and track. It has great significance to detect wheel polygon in order to ensure the safe operation of trains. The wheel out-of-roundness detection method based on POVMD and multinuclear LS-SVM is investigated by using POVMD algorithm to decompose the vibration signal, and then PSO to get optimal parameters which takes VMD algorithm into consideration. Such a method extracts some features from IMF components. Finally, Gaussian kernel function and directed acyclic graph classification method are chosen to build multinuclear classifier to detect wheel out-of-roundness. The experiment results show that the proposed method is effective to analyze wheel out-of-roundness.

Published
2020

40. Research on Monitoring Technology of Pantograph Sliding Plate Abrasion Based on Sub-pixel Edge Extraction

Author

Li Shibo, Fang Lichao, Zhaoyi Su, Dai Wang, Zongyi Xing, and Yong Zhang

Subjects
Slide plate, Computer science, Abrasion (mechanical), Slider, Process (computing), Mechanical engineering, Pantograph, Residual, Fault (power engineering), Camera resectioning
Abstract

Aiming at the fault of the urban rail train caused by the excessive abrasion of the pantograph slide plate, a pantograph sliding plate abrasion monitoring algorithm based on sub-pixel edge extraction is designed in this paper. This paper mainly analyzes the process of the pantograph slide’s wear monitoring algorithm. The experimental results show that the method proposed in this paper can effectively detect the abrasion curve of the pantograph slider and get the minimum residual abrasion value.

Published
2020

41. Research on Train Energy-Saving Optimization Based on Parallel Immune Particle Swarm Optimization

Author

Yong Zhang, Li Shibo, Fang Lichao, Dai Wang, and Zongyi Xing

Subjects
Energy conservation, 050210 logistics & transportation, Mathematical optimization, Optimization problem, Urban rail transit, Computer science, 0502 economics and business, 05 social sciences, Line (geometry), Particle swarm optimization, Point (geometry), Interval (mathematics), Energy (signal processing)
Abstract

Aiming at the optimization problem of subway train energy conservation, this paper proposes a train energy-saving optimization method based on parallel immune particle swarm optimization. The parallel immune particle swarm optimization algorithm is used to optimize the train energy saving in two stages: firstly, the running time of each interval is fixed, the algorithm is used to search for the optimal working condition switching point, and then, the train running time is optimized under the premise of constant running time. Finally, using the real data of Beijing Yizhuang line to simulate, verify the feasibility of the model and algorithm.

Published
2020

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