A5101967058- Computational Drug Discovery Methods
- Machine Learning in Materials Science
- Machine Learning in Bioinformatics
- Advanced Photocatalysis Techniques
- Perovskite Materials and Applications
- TiO2 Photocatalysis and Solar Cells
- Quantum Dots Synthesis And Properties
- Spectroscopy and Chemometric Analyses
- X-ray Diffraction in Crystallography
- Gas Sensing Nanomaterials and Sensors
- Conducting polymers and applications
- Catalytic Processes in Materials Science
- Semiconductor materials and devices
- Protein Structure and Dynamics
- GaN-based semiconductor devices and materials
- Genomics and Phylogenetic Studies
- ZnO doping and properties
- Layered Double Hydroxides Synthesis and Applications
- RNA and protein synthesis mechanisms
- Bioinformatics and Genomic Networks
- Advanced Chemical Sensor Technologies
- Analytical Chemistry and Chromatography
- Metal and Thin Film Mechanics
- Metal-Organic Frameworks: Synthesis and Applications
- Metabolomics and Mass Spectrometry Studies
Shanghai University
2015-2024
Zhejiang Lab
2022-2024
National University of Defense Technology
2023
Second Affiliated Hospital of Guangzhou Medical University
2022
Guangzhou Medical University
2022
Guangdong Province Women and Children Hospital
2022
Guangdong University of Technology
2019-2020
Shanghai Institute of Hematology
2019
Shanghai Jiao Tong University
2008-2019
Commercial Aircraft Corporation of China (China)
2017
Abstract The development of materials is one the driving forces to accelerate modern scientific progress and technological innovation. Machine learning (ML) technology rapidly developed in many fields opening blueprints for discovery rational design materials. In this review, we retrospected latest applications ML assisting perovskites discovery. First, tendency perovskite publications recent years was organized analyzed. Second, workflow introduced. Then various properties inorganic...
Abstract This review discussed the dilemma of small data faced by materials machine learning. First, we analyzed limitations brought data. Then, workflow learning has been introduced. Next, methods dealing with were introduced, including extraction from publications, database construction, high-throughput computations and experiments source level; modeling algorithms for imbalanced algorithm active transfer strategy level. Finally, future directions in science proposed.
Abstract Under the guidance of material genome initiative (MGI), use data‐driven methods to discover new materials has become an innovation science. The polymer have been one most important parts in science for excellent physical and chemical properties as well corresponding complex structures. Machine learning, core methods, taken place design discovery. In this review, authors introduced applications machine learning discovery materials. development tendency published papers about...
Background With the huge amount of uncharacterized protein sequences generated in post-genomic age, it is highly desirable to develop effective computational methods for quickly and accurately predicting their functions. The information thus obtained would be very useful both basic research drug development a timely manner. Methodology/Principal Findings Although many efforts have been made this regard, most them were based on either sequence similarity or protein-protein interaction (PPI)...
Dye-sensitized solar cells (DSSCs) are the most promising low-cost photovoltaic devices. Whereas, absorption bands of organic sensitizers, vital component in DSSCs, limited to a relatively narrow visible range. To obtain efficient sensitizer, series D–A−π–A metal-free dyes have been designed based on one best sensitizers WS-9 by modifying auxiliary acceptor and characterized theoretically. The results illustrate that introduction heterocycle is revealed very band gap (HOMO–LUMO), leading an...
Carbon-based TiO₂ composites have many advantages as photocatalysts. However, they suffer from low light efficiency due to the contrast of with carbon. We synthesized a novel type anatase-type TiO₂-C hybrid aerogel by one-pot sol-gel method, which shows photocatalytic activity for methylene degradation up 4.23 times that P25, commercial photocatalyst Degussa Inc. The aerogels are prepared TiCl₄ and resorcinol-furfural, tunable macropore size 167 996 nm. They formed submicrometer particles...
Recent developments in data mining-aided materials discovery and optimization are reviewed this paper, an introduction to the mining (MDM) process is provided using case studies. Both qualitative quantitative methods machine learning can be adopted MDM accomplish different tasks discovery, design, optimization. State-of-the-art techniques demonstrated by reviewing controllable synthesis of dendritic Co3O4 superstructures, design layered double hydroxide, battery thermoelectric design. The...
Monodisperse manganese oxide flowerlike nanostructures have been prepared facilely at low temperature and ambient atmosphere. The effect of the reaction time on microstructure morphology is observed systemically by transmission electron microscopy (TEM) high-resolution (HRTEM). Meanwhile, possible formation mechanism has proposed discussed. It also found that great influences these unique nanostructures. results nitrogen adsorption−desorption experiments electrochemical measurements show...
Hierarchical cantaloupe-like and hollow microspherical AlOOH superstructures were successfully synthesized on a large scale via one-step hydrothermal route. The as-obtained characterized by several techniques, such as X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning (SEM), nitrogen adsorption/desorption measurement. superstructures, consisting of closely packed nanorods in an ordered fashion, have average horizontal axis ca. 2.5 µm longitudinal 1.5 µm....
Well-defined porous Co3O4 nanodendrites have been synthesized by a simple one-pot hydrothermal method combined with subsequent calcination. Importantly, after thermal treatment, the dendritic morphology could be completely preserved. The as-obtained superstructures are characterized several techniques, such as powder X-ray diffraction, Fourier transform infrared spectroscopy, photoemission elemental analysis, transmission electron microscopy, high-resolution TEM and magnetometry. On...
// Qiang Su 1 , Wencong Lu 2 Dongshu Du 1, 3 Fuxue Chen Bing Niu 4 and Kuo-Chen Chou 4, 5, 6 College of Life Science, Shanghai University, 200444, China Department Chemistry, Sciences, Heze Shandong 274500, Gordon Science Institute, Boston, MA 02478, USA 5 Center for Informational Biology, University Electronic Technology China, Chengdu 610054, Excellence in Genomic Medicine Research, King Abdulaziz Jeddah 21589, Saudi Arabia Correspondence to: Niu, email: bniu@gordonlifescience.org...
Predicting the formability of perovskite structure for hybrid organic–inorganic perovskites (HOIPs) is a prominent challenge in search required materials from huge space. Here, we propose an interpretable strategy combining machine learning with shapley additive explanations (SHAP) approach to accelerate discovery potential HOIPs. According prediction best classification model, top-198 nontoxic candidates probability (Pf) >0.99 are screened 18560 virtual samples. The SHAP analysis reveals...