A5101474913- Hydrogen embrittlement and corrosion behaviors in metals
- Additive Manufacturing Materials and Processes
- Machine Learning in Materials Science
- Robotic Path Planning Algorithms
- Non-Destructive Testing Techniques
- Microstructure and Mechanical Properties of Steels
- Carbon Dioxide Capture Technologies
- Metal Alloys Wear and Properties
- Covalent Organic Framework Applications
- High-Temperature Coating Behaviors
- Medical Image Segmentation Techniques
- Welding Techniques and Residual Stresses
- Robotics and Sensor-Based Localization
- Radiomics and Machine Learning in Medical Imaging
- High Entropy Alloys Studies
- Robotic Locomotion and Control
- Metal-Organic Frameworks: Synthesis and Applications
- AI in cancer detection
Chengdu University
2023-2024
University of Washington Applied Physics Laboratory
2022
Southwest Jiaotong University
2020
Nanjing University
2012
Based upon the (3,6)-connected metal-organic framework {Cu(L1)·2H(2)O·1.5DMF}(∞) (L1 = 5-(pyridin-4-yl)isophthalic acid) (SYSU, for Sun Yat-Sen University), iso-reticular {Cu(L2)·DMF}(∞) (L2 5-(pyridin-3-yl)isophthalic (NJU-Bai7; NJU-Bai Nanjing University Bai group) and {Cu(L3)·DMF·H(2)O}(∞) (L3 5-(pyrimidin-5-yl)isophthalic (NJU-Bai8) were designed by shifting coordination sites of ligands to fine-tune pore size polarizing inner surface with uncoordinated nitrogen atoms, respectively,...
High entropy alloys (HEAs) have excellent properties because they can form simple solid solution (SS) phases, including body-centered cubic (BCC) phase, face-centered (FCC) or FCC + BCC so phase prediction is the first step in alloy design. In current research, machine learning (ML) approach had been widely used to guide discovery and design of materials. The HEAs structure based on a hot topic. this work, five ML algorithms were utilized predict for SS amorphous (AM) phases 399 collected...
The space environment of path planning for service robots is complex. In this environment, the traditional Rapid-exploring Random Tree * (RRT*) algorithm guarantees completeness and asymptotic optimality global search probability, but it has high memory occupancy, slow convergence speed, large sampling long time-consuming. Therefore, a fast extended random tree star trajectory proposed in paper. R-RRT* improves above problems through three novel strategies: connected domain sampling,...
Medical image analysis is an interdisciplinary field of comprehensive medical imaging and analyzing, whose goal to recognize disease diagnosis lesion area through the related computer vision technology. Benefiting from continuous development convolutional neural networks, based on deep learning has become a research hot spot. In this paper, in-depth literature results progress in recent years, we mainly analyze domestic foreign status Imaging various application fields such as detection,...