Weike Ye

2.3k total citations · 2 hit papers
14 papers, 1.6k citations indexed

About

Weike Ye is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Weike Ye has authored 14 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Materials Chemistry, 4 papers in Electrical and Electronic Engineering and 3 papers in Computational Theory and Mathematics. Recurrent topics in Weike Ye's work include Machine Learning in Materials Science (10 papers), X-ray Diffraction in Crystallography (5 papers) and Computational Drug Discovery Methods (3 papers). Weike Ye is often cited by papers focused on Machine Learning in Materials Science (10 papers), X-ray Diffraction in Crystallography (5 papers) and Computational Drug Discovery Methods (3 papers). Weike Ye collaborates with scholars based in United States, Switzerland and China. Weike Ye's co-authors include Shyue Ping Ong, Chi Chen, Yunxing Zuo, Zheng Chen, Xiangguo Li, Zhi Deng, Iek‐Heng Chu, Zhenbin Wang, Jian Luo and Mingde Qin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Chemistry of Materials and Advanced Energy Materials.

In The Last Decade

Weike Ye

13 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

2019 876 citations Chi Chen, Weike Ye et al. Chemistry of Materials profile →
A Critical Review of Machine Learning of Energy Materials

2020 436 citations Chi Chen, Yunxing Zuo et al. Advanced Energy Materials profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Weike Ye United States	10	1.3k	461	349	155	148	14	1.6k
Katherine C. Elbert United States	10	1.2k 0.9×	609 1.3×	199 0.6×	303 2.0×	233 1.6×	16	1.9k
Malia B. Wenny United States	7	1.0k 0.8×	305 0.7×	202 0.6×	133 0.9×	228 1.5×	13	1.6k
Paul Raccuglia United States	2	872 0.7×	245 0.5×	198 0.6×	88 0.6×	183 1.2×	2	1.3k
Tanjin He United States	19	1.1k 0.8×	315 0.7×	178 0.5×	94 0.6×	232 1.6×	27	1.7k
Kevin Maik Jablonka Switzerland	18	1.1k 0.9×	213 0.5×	195 0.6×	178 1.1×	186 1.3×	27	1.6k
Philip Adler United Kingdom	5	888 0.7×	253 0.5×	200 0.6×	89 0.6×	185 1.3×	9	1.3k
Felipe Oviedo United States	14	894 0.7×	526 1.1×	184 0.5×	92 0.6×	121 0.8×	35	1.4k
Zekun Ren Singapore	17	1.1k 0.8×	757 1.6×	164 0.5×	129 0.8×	280 1.9×	47	1.7k
Venkatesh Botu United States	12	1.1k 0.9×	367 0.8×	284 0.8×	259 1.7×	167 1.1×	15	1.5k
Vladimir V. Gusev United Kingdom	6	636 0.5×	203 0.4×	182 0.5×	132 0.9×	279 1.9×	25	1.1k

Countries citing papers authored by Weike Ye

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Weike Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Weike Ye. A scholar is included among the top collaborators of Weike Ye based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Weike Ye. Weike Ye is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

Yang, Zhenze, et al.. (2024). De novo design of polymer electrolytes using GPT-based and diffusion-based generative models. npj Computational Materials. 10(1). 24 indexed citations

Khajeh, Arash, X. L. Lei, Weike Ye, et al.. (2024). A materials discovery framework based on conditional generative models applied to the design of polymer electrolytes. Digital Discovery. 4(1). 11–20. 7 indexed citations

Mueller, Tim, Joseph H. Montoya, Weike Ye, et al.. (2024). An electrochemical series for materials. Proceedings of the National Academy of Sciences. 121(38). e2320134121–e2320134121.

Kamat, Gaurav A., Aniket S. Mule, Melissa E. Kreider, et al.. (2023). Mechanisms of Stabilization and Degradation of Transition Metal Oxygen Electroreduction Catalysts with in-Situ Electrochemical Flow Cell ICP-MS. ECS Meeting Abstracts. MA2023-02(55). 2682–2682. 1 indexed citations

Ye, Weike, X. L. Lei, Muratahan Aykol, & Joseph H. Montoya. (2022). Novel inorganic crystal structures predicted using autonomous simulation agents. Scientific Data. 9(1). 302–302. 15 indexed citations

Ye, Weike, Hui Zheng, Chi Chen, & Shyue Ping Ong. (2022). A Universal Machine Learning Model for Elemental Grain Boundary Energies. Scripta Materialia. 218. 114803–114803. 20 indexed citations

Ye, Weike, Hui Zheng, Chi Chen, & Shyue Ping Ong. (2022). A Universal Machine Learning Model for Elemental Grain Boundary Energies. SSRN Electronic Journal. 1 indexed citations

Zuo, Yunxing, Mingde Qin, Chi Chen, et al.. (2021). Accelerating materials discovery with Bayesian optimization and graph deep learning. Materials Today. 51. 126–135. 87 indexed citations

Chen, Chi, Yunxing Zuo, Weike Ye, et al.. (2020). A Critical Review of Machine Learning of Energy Materials. Advanced Energy Materials. 10(8). 436 indexed citations breakdown →

10.

Chen, Chi, Weike Ye, Yunxing Zuo, Zheng Chen, & Shyue Ping Ong. (2019). Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals. Chemistry of Materials. 31(9). 3564–3572. 876 indexed citations breakdown →

11.

Ye, Weike, Chi Chen, Shyam Dwaraknath, et al.. (2018). Harnessing the Materials Project for machine-learning and accelerated discovery. MRS Bulletin. 43(9). 664–669. 20 indexed citations

12.

Agarwal, Vipul, Diwei Ho, Faizah Md Yasin, et al.. (2016). Functional Reactive Polymer Electrospun Matrix. ACS Applied Materials & Interfaces. 8(7). 4934–4939. 26 indexed citations

13.

Wang, Zhenbin, Weike Ye, Iek‐Heng Chu, & Shyue Ping Ong. (2016). Elucidating Structure–Composition–Property Relationships of the β-SiAlON:Eu²⁺ Phosphor. Chemistry of Materials. 28(23). 8622–8630. 60 indexed citations

14.

Hu, Shanwen, Bi-Yi Xu, Weike Ye, et al.. (2014). Versatile Microfluidic Droplets Array for Bioanalysis. ACS Applied Materials & Interfaces. 7(1). 935–940. 34 indexed citations

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.

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