Zhengwei Peng

1.3k citations
40 papers · 954 indexed · h-index 15
Topics
Computational Drug Discovery Methods (15 papers)Chemical Synthesis and Analysis (9 papers)Machine Learning in Materials Science (5 papers)

In The Last Decade

Zhengwei Peng

36 papers receiving 913 citations

Peers

Zhengwei Peng
Comparison fields: 5 of 97
  • Molecular Biology 325
  • Materials Chemistry 308
  • Computational Theory and Mathematics 294
  • Organic Chemistry 231
  • Biomedical Engineering 153
Replace Jonah Z. Vilseck with:
Jonah Z. Vilseck United States
Ilie Fishtik United States
Olga Klimchuk France
Yunsie Chung United States
Rubén Laplaza Switzerland
Marcel Stahn Germany
Rajni M. Bhardwaj United Kingdom
Valentín Vassilev-Galindo Luxembourg
Daniel W. Trahan United States
Vivekanand V. Gobre India
Zhengwei Peng relative to Jonah Z. Vilseck United States Jonah Z. Vilseck's profile →
Citations per field
00.5×1.5×
Jonah Z. Vilseck · 1×
Citations per year

Countries citing papers authored by Zhengwei Peng

Since Specialization
Citations

This map shows the geographic impact of Zhengwei Peng'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 Zhengwei Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhengwei Peng more than expected).

Fields of papers citing papers by Zhengwei Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhengwei Peng. 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 Zhengwei Peng. The network helps show where Zhengwei Peng may publish in the future.

Co-authorship network of co-authors of Zhengwei Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Zhengwei Peng. A scholar is included among the top collaborators of Zhengwei Peng 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 Zhengwei Peng. Zhengwei Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 2
4 0
5 3
6 15
7 8
8 6
9 8
10 145
11 121
12 6
13 7
14 4
15 3
16 28
17 3
18 10
19 10
20 19

About Zhengwei Peng

Zhengwei Peng is a scholar working on Computational Theory and Mathematics, Metals and Alloys and Ceramics and Composites, having authored 40 papers that have together received 954 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (15 papers), Chemical Synthesis and Analysis (9 papers) and Machine Learning in Materials Science (5 papers). The work is most often cited by research in Computational Theory and Mathematics (294 citations), Filtration and Separation (20 citations) and Organic Chemistry (231 citations). Zhengwei Peng has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Carl S. Ewig, A. T. Hagler, Ming‐Jing Hwang, Marvin Waldman, Yu‐hong Lam, Edward C. Sherer, Spencer D. Dreher, Ian W. Davies, Atsuo Kuki and Qiyue Hu. Their work appears in journals such as Science, Angewandte Chemie International Edition and Journal of Medicinal Chemistry.

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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