Yi Di

763 citations
23 papers · 478 · 1 hit paper · h-index 11

Impact in

Papers in

Yi Di

23 papers receiving 464 citations

Yi Di's Hit Papers

Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis 2024 · 226 citations
2260+1Years since publication50100150200

Peers

Yi Di
Comparison fields: 5 of 61
  • Automotive Engineering 182
  • Renewable Energy, Sustainability and the Environment 95
  • Electrical and Electronic Engineering 220
  • Safety, Risk, Reliability and Quality 31
  • Polymers and Plastics 47
Replace Zhaoqi Wang with:
Zhaoqi Wang China
Jie Lu China
Guodong Chen China
Hao Zhou China
Zhenyu Huang China
Ta‐Wei Lin Taiwan
Donghoun Lee South Korea
Hanxiao Wang China
Wenna Zhang China
Yi Di relative to Zhaoqi Wang China Zhaoqi Wang's profile →
Citations per field
00.5×
Zhaoqi Wang · 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 23 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 →
2024226
2 201924
3 201522
4 202120
5 201820
6 201616
7 201916
8 201915
9 202114
10 201912
11 201612
12 201810
13 201810
14 202010
15 20229
16 20248
17 20218
18 20227
19 20206
20 20174

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 23 papers that have together received 478 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), Advanced Battery Materials and Technologies (3 papers), Quantum Dots Synthesis And Properties (3 papers), Perovskite Materials and Applications (3 papers) and Luminescence and Fluorescent Materials (2 papers). The work is most often cited by research in Automotive Engineering (182 citations), Renewable Energy, Sustainability and the Environment (95 citations), Electrical and Electronic Engineering (220 citations), Safety, Risk, Reliability and Quality (31 citations) and Polymers and Plastics (47 citations). Yi Di has collaborated with scholars based in China and Taiwan. Frequent co-authors include Zhibin Zhao, Zhi Zhai, Fujin Wang, Xuefeng Chen, Jiwen Feng, Bing Chen, Tianshi Qin, Geying Ru, Suping Jia and Shengliang Hu. Their work appears in journals such as Solar Energy, Organic Electronics, Energy storage materials, Advanced Materials Technologies and Ceramics International.

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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