Weike Ye
Impact in
- Materials Chemistry top 5%
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Electronic and Structural Properties of Oxides
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- Computational Drug Discovery Methods
Papers in ⓘ
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- Machine Learning in Materials Science 10
- X-ray Diffraction in Crystallography 5
- Electronic and Structural Properties of Oxides 2
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- Fuel Cells and Related Materials 2
- Co-authors
- Shyue Ping Ong (7 shared papers)Chi Chen (6 shared papers)Yunxing Zuo (3 shared papers)Zheng Chen (1 shared paper)Xiangguo Li (2 shared papers)Zhi Deng (1 shared paper)Zhenbin Wang (1 shared paper)Iek‐Heng Chu (1 shared paper)
- Journals
- Chemistry of Materials (2 papers)ACS Applied Materials & Interfaces (2 papers)npj Computational Materials (1 paper)Advanced Energy Materials (1 paper)Scripta Materialia (1 paper)
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
Weike Ye
13 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Materials Chemistry 1.3k
- Computational Theory and Mathematics 349
- Catalysis 83
- Metals and Alloys 29
- Renewable Energy, Sustainability and the Environment 155
Countries citing papers authored by Weike Ye
This map shows the geographic impact of Weike Ye's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Weike Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weike Ye more than expected).
Fields of papers citing papers by Weike Ye
This network shows the impact of papers produced by Weike Ye. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Weike Ye. The network helps show where Weike Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Weike Ye, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals Hit paper breakdown → | 2019 | 876 |
| 2 | A Critical Review of Machine Learning of Energy Materials Hit paper breakdown → | 2020 | 436 |
| 3 | 2021 | 87 | |
| 4 | 2016 | 60 | |
| 5 | 2014 | 34 | |
| 6 | 2016 | 26 | |
| 7 | 2024 | 24 | |
| 8 | 2022 | 20 | |
| 9 | 2018 | 20 | |
| 10 | 2022 | 15 | |
| 11 | 2024 | 7 | |
| 12 | 2023 | 1 | |
| 13 | 2022 | 1 | |
| 14 | 2024 | 0 |
About Weike Ye
Weike Ye is a scholar working on Materials Chemistry, Electrical and Electronic Engineering, Computational Theory and Mathematics, Renewable Energy, Sustainability and the Environment and Biomedical Engineering, having authored 14 papers that have together received 1.6k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (10 papers), X-ray Diffraction in Crystallography (5 papers), Computational Drug Discovery Methods (3 papers), Electronic and Structural Properties of Oxides (2 papers), Advanced Photocatalysis Techniques (2 papers), Fuel Cells and Related Materials (2 papers), Ga2O3 and related materials (1 paper) and Electron and X-Ray Spectroscopy Techniques (1 paper). The work is most often cited by research in Materials Chemistry (1.3k citations), Computational Theory and Mathematics (349 citations), Catalysis (83 citations), Metals and Alloys (29 citations) and Renewable Energy, Sustainability and the Environment (155 citations). Weike Ye has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include Shyue Ping Ong, Chi Chen, Yunxing Zuo, Zheng Chen, Xiangguo Li, Zhi Deng, Zhenbin Wang, Iek‐Heng Chu, Jian Luo and Mingde Qin. Their work appears in journals such as Chemistry of Materials, ACS Applied Materials & Interfaces, npj Computational Materials, Advanced Energy Materials and Scripta Materialia.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.