Jin Bai

9.8k citations
250 papers · 6.9k · h-index 48

Impact in

Papers in

Jin Bai

234 papers receiving 6.8k citations

Peers

Jin Bai
Comparison fields: 5 of 110
  • Fuel Technology 285
  • Geochemistry and Petrology 1.8k
  • Biomedical Engineering 3.5k
  • Mechanical Engineering 2.9k
  • Renewable Energy, Sustainability and the Environment 1.1k
Replace Guangsuo Yu with:
Guangsuo Yu China
Arash Tahmasebi Australia
Sheng Su China
Song Hu China
Yijun Cao China
N.A. Rowson United Kingdom
Weiren Bao China
Zongqing Bai China
Houzhang Tan China
Yonghui Bai China
Jin Bai relative to Guangsuo Yu China Guangsuo Yu's profile →
Citations per field
00.5×4.9×
Guangsuo Yu · 1×
Citations per year

Countries citing papers authored by Jin Bai

Since Specialization
Citations

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

Fields of papers citing papers by Jin Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jin Bai, 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 Jin Bai Line = papers co-authored together Jin Bai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 250 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014178
2 2021139
3 2012130
4 2016129
5 2012121
6 2007117
7 2017100
8 201299
9 201697
10 201892
11 201691
12 201788
13 201887
14 202186
15 201485
16 201883
17 201370
18 201969
19 201869
20 201867

About Jin Bai

Jin Bai is a scholar working on Biomedical Engineering, Mechanical Engineering, Geochemistry and Petrology, Materials Chemistry and Ocean Engineering, having authored 250 papers that have together received 6.9k indexed citations. Recurring topics across this work include Thermochemical Biomass Conversion Processes (112 papers), Coal and Its By-products (75 papers), Iron and Steelmaking Processes (69 papers), Metallurgical Processes and Thermodynamics (54 papers), Coal Properties and Utilization (45 papers), Recycling and utilization of industrial and municipal waste in materials production (30 papers), Coal Combustion and Slurry Processing (26 papers) and Thermal and Kinetic Analysis (20 papers). The work is most often cited by research in Fuel Technology (285 citations), Geochemistry and Petrology (1.8k citations), Biomedical Engineering (3.5k citations), Mechanical Engineering (2.9k citations) and Renewable Energy, Sustainability and the Environment (1.1k citations). Jin Bai has collaborated with scholars based in China, Germany and Australia. Frequent co-authors include Zongqing Bai, Lingxue Kong, Wen Li, Zhenxing Guo, Wen Li, Huaizhu Li, Jingchong Yan, Chong He, Shaozheng Hu and Stefan Guhl. Their work appears in journals such as Fuel, Fuel Processing Technology, Energy & Fuels, Journal of the Energy Institute and RSC Advances.

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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