Yi Di

902 citations
24 papers · 577 · 1 hit paper · h-index 11

Impact in

Papers in

Yi Di

23 papers receiving 564 citations

Yi Di's Hit Papers

Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis 2024 · 317 citations
3170+1Years since publication100200300

Peers

Yi Di
Comparison fields: 5 of 60
  • Automotive Engineering 248
  • Renewable Energy, Sustainability and the Environment 99
  • Electrical and Electronic Engineering 238
  • Safety, Risk, Reliability and Quality 33
  • Polymers and Plastics 48
Replace Jie Lu with:
Jie Lu China
Zhaoqi Wang China
Hao Zhou China
Zhenyu Huang China
Guodong Chen China
Donghoun Lee South Korea
Hanxiao Wang China
Guiyu Zhang China
Ta‐Wei Lin Taiwan
Yi Di relative to Jie Lu China Jie Lu's profile →
Citations per field
00.5×11×
Jie Lu · 1×
Citations per year

Countries citing papers authored by Yi Di

Since Specialization
Citations

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

Fields of papers citing papers by Yi Di

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yi Di, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yi Di Line = papers co-authored together Yi Di links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis
Hit paper breakdown →
2024317
2 201924
3 201523
4 201821
5 202120
6 201916
7 201616
8 201916
9 202115
10 201612
11 201912
12 202010
13 201810
14 202210
15 201810
16 20248
17 20218
18 20227
19 20206
20 20245

About Yi Di

Yi Di is a scholar working on Renewable Energy, Sustainability and the Environment, Electrical and Electronic Engineering, Materials Chemistry, Polymers and Plastics and Molecular Biology, having authored 24 papers that have together received 577 indexed citations. Recurring topics across this work include TiO2 Photocatalysis and Solar Cells (10 papers), Advanced Photocatalysis Techniques (9 papers), Advancements in Battery Materials (4 papers), Conducting polymers and applications (3 papers), Quantum Dots Synthesis And Properties (3 papers), Advanced Battery Materials and Technologies (3 papers), Perovskite Materials and Applications (3 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Automotive Engineering (248 citations), Renewable Energy, Sustainability and the Environment (99 citations), Electrical and Electronic Engineering (238 citations), Safety, Risk, Reliability and Quality (33 citations) and Polymers and Plastics (48 citations). Yi Di has collaborated with scholars based in China, Japan and Taiwan. Frequent co-authors include Fujin Wang, Xuefeng Chen, Zhibin Zhao, Zhi Zhai, Jiwen Feng, Bing Chen, Tianshi Qin, Geying Ru, Shengliang Hu and Suping Jia. Their work appears in journals such as Organic Electronics, Solar Energy, Physical Chemistry Chemical Physics, Polymers and Energy storage 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.

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