Weike Ye
Impact in
- Materials Chemistry top 5%
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Electronic and Structural Properties of Oxides
-
- Computational Drug Discovery Methods
Papers in
-
- Machine Learning in Materials Science 11
- X-ray Diffraction in Crystallography 6
- Electronic and Structural Properties of Oxides 2
-
- Computational Drug Discovery Methods 4
- Co-authors
- Shyue Ping Ong (8 shared papers)Chi Chen (7 shared papers)Yunxing Zuo (3 shared papers)Zheng Chen (1 shared paper)Xiangguo Li (2 shared papers)Zhi Deng (1 shared paper)Zhenbin Wang (2 shared papers)Iek‐Heng Chu (2 shared papers)
- Journals
- ACS Applied Materials & Interfaces (2 papers)Chemistry of Materials (2 papers)Materials Today (1 paper)Advanced Energy Materials (1 paper)npj Computational Materials (1 paper)
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
Weike Ye
14 papers receiving 1.9k citations
Weike Ye's Hit Papers
Peers
Comparison fields: 5 of 94
- Materials Chemistry 1.6k
- Computational Theory and Mathematics 399
- Catalysis 108
- Metals and Alloys 36
- Renewable Energy, Sustainability and the Environment 183
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 | 959 |
| 2 | A Critical Review of Machine Learning of Energy Materials Hit paper breakdown → | 2020 | 465 |
| 3 | Deep neural networks for accurate predictions of crystal stability. | 2018 | 203 |
| 4 | 2021 | 93 | |
| 5 | 2016 | 61 | |
| 6 | 2014 | 34 | |
| 7 | 2024 | 29 | |
| 8 | 2016 | 27 | |
| 9 | 2022 | 21 | |
| 10 | 2018 | 20 | |
| 11 | 2022 | 16 | |
| 12 | 2024 | 10 | |
| 13 | 2023 | 1 | |
| 14 | 2022 | 1 | |
| 15 | 2024 | 0 |
About Weike Ye
Weike Ye is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment and Biomedical Engineering, having authored 15 papers that have together received 1.9k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (11 papers), X-ray Diffraction in Crystallography (6 papers), Computational Drug Discovery Methods (4 papers), Electronic and Structural Properties of Oxides (2 papers), Advanced Photocatalysis Techniques (2 papers), Fuel Cells and Related Materials (2 papers), Electrospun Nanofibers in Biomedical Applications (1 paper) and Electrowetting and Microfluidic Technologies (1 paper). The work is most often cited by research in Materials Chemistry (1.6k citations), Computational Theory and Mathematics (399 citations), Catalysis (108 citations), Metals and Alloys (36 citations) and Renewable Energy, Sustainability and the Environment (183 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, Mingde Qin and Jian Luo. Their work appears in journals such as ACS Applied Materials & Interfaces, Chemistry of Materials, Materials Today, Advanced Energy Materials and npj Computational Materials.
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.