Jongkoo Lim

591 total citations
24 papers, 447 citations indexed

About

Jongkoo Lim is a scholar working on Control and Systems Engineering, Electrical and Electronic Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Jongkoo Lim has authored 24 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Control and Systems Engineering, 7 papers in Electrical and Electronic Engineering and 7 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Jongkoo Lim's work include Fuel Cells and Related Materials (7 papers), Fault Detection and Control Systems (7 papers) and Electrocatalysts for Energy Conversion (6 papers). Jongkoo Lim is often cited by papers focused on Fuel Cells and Related Materials (7 papers), Fault Detection and Control Systems (7 papers) and Electrocatalysts for Energy Conversion (6 papers). Jongkoo Lim collaborates with scholars based in South Korea, United States and China. Jongkoo Lim's co-authors include Junghwan Kim, Hyungtae Cho, Hyundo Park, Yung‐Eun Sung, Myung Su Lim, Ji Eun Park, Sungjun Kim, Il Moon, Yong‐Hun Cho and Chi‐Yeong Ahn and has published in prestigious journals such as Journal of Power Sources, Chemical Engineering Journal and Electrochimica Acta.

In The Last Decade

Jongkoo Lim

22 papers receiving 433 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jongkoo Lim South Korea 12 217 182 103 68 53 24 447
Md Momtazur Rahman Australia 14 206 0.9× 189 1.0× 50 0.5× 22 0.3× 62 1.2× 22 613
Nizar F.O. Al-Muhsen Iraq 7 191 0.9× 212 1.2× 55 0.5× 42 0.6× 40 0.8× 23 489
M. Jayachandran India 10 298 1.4× 62 0.3× 95 0.9× 38 0.6× 198 3.7× 24 549
Keval Chandrakant Nikam India 11 101 0.5× 154 0.8× 28 0.3× 91 1.3× 33 0.6× 17 434
Nima Khalilpoor Iran 14 102 0.5× 123 0.7× 39 0.4× 76 1.1× 21 0.4× 34 453
Bekkay Hajji Morocco 15 340 1.6× 348 1.9× 36 0.3× 29 0.4× 65 1.2× 47 614
Kurt Kornbluth United States 10 196 0.9× 83 0.5× 32 0.3× 31 0.5× 100 1.9× 20 406
Mubashir Ali Siddiqui Pakistan 12 156 0.7× 128 0.7× 34 0.3× 30 0.4× 51 1.0× 38 419
Kevin N. Nwaigwe Botswana 10 145 0.7× 204 1.1× 18 0.2× 140 2.1× 83 1.6× 30 507
Sadegh Afzal Iran 8 163 0.8× 214 1.2× 44 0.4× 40 0.6× 26 0.5× 12 557

Countries citing papers authored by Jongkoo Lim

Since Specialization
Citations

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

Fields of papers citing papers by Jongkoo Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jongkoo Lim

This figure shows the co-authorship network connecting the top 25 collaborators of Jongkoo Lim. A scholar is included among the top collaborators of Jongkoo Lim 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 Jongkoo Lim. Jongkoo Lim 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
1.
Kim, Minseong, Jongkoo Lim, Seokwon Yeom, et al.. (2024). Novel inverse predictive system integrated with industrial lubricant information. Engineering Applications of Artificial Intelligence. 142. 109853–109853.
2.
Park, Hyundo, et al.. (2024). Novel natural gradient boosting-based probabilistic prediction of physical properties for polypropylene-based composite data. Engineering Applications of Artificial Intelligence. 135. 108864–108864. 3 indexed citations
3.
Bhadriraju, Bhavana, et al.. (2024). Machine Learning-Based Adaptive Regression to Identify Nonlinear Dynamics of Biochemical Systems: A Case Study on Bio 2,3-Butanediol Distillation Process. ACS Sustainable Chemistry & Engineering. 12(29). 10869–10879. 1 indexed citations
4.
Park, Hyundo, et al.. (2023). Machine learning-based heat deflection temperature prediction and effect analysis in polypropylene composites using catboost and shapley additive explanations. Engineering Applications of Artificial Intelligence. 126. 106873–106873. 43 indexed citations
5.
Lim, Jongkoo, et al.. (2023). A novel graph-based missing values imputation method for industrial lubricant data. Computers in Industry. 150. 103937–103937. 11 indexed citations
6.
Hong, Seokyoung, Yurim Kim, Hyungtae Cho, et al.. (2023). Dual attention-based multi-step ahead prediction enhancement for monitoring systems in industrial processes. Applied Soft Computing. 147. 110763–110763. 6 indexed citations
7.
Hong, Seokyoung, Hyungtae Cho, Jongkoo Lim, et al.. (2022). Time-series clustering approach for training data selection of a data-driven predictive model: Application to an industrial bio 2,3-butanediol distillation process. Computers & Chemical Engineering. 161. 107758–107758. 12 indexed citations
8.
Hong, Seokyoung, Hyungtae Cho, Jongkoo Lim, et al.. (2022). Correction to: A dynamic soft sensor based on hybrid neural networks to improve early off-spec detection. Engineering With Computers. 39(5). 3155–3155. 1 indexed citations
9.
Park, Hyundo, et al.. (2021). Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters. International Journal of Intelligent Systems. 37(6). 3625–3653. 33 indexed citations
10.
11.
Lim, Jongkoo, et al.. (2019). Dynamic Modeling of Acetone–Butanol–Ethanol Fermentation with ex Situ Butanol Recovery using Glucose/Xylose Mixtures. Industrial & Engineering Chemistry Research. 59(6). 2581–2592. 3 indexed citations
12.
Park, Ji Eun, Jongkoo Lim, Myung Su Lim, et al.. (2019). Gas diffusion layer/flow-field unified membrane-electrode assembly in fuel cell using graphene foam. Electrochimica Acta. 323. 134808–134808. 65 indexed citations
13.
Jeong, Hae Jin, Joon‐Yung Cha, Jung Hoon Choi, et al.. (2018). One-Pot Transformation of Technical Lignins into Humic-Like Plant Stimulants through Fenton-Based Advanced Oxidation: Accelerating Natural Fungus-Driven Humification. ACS Omega. 3(7). 7441–7453. 44 indexed citations
14.
Lee, C. Justin, et al.. (2018). Investigation into the Performance and Safety of Alternative Refrigerants to Ammonia for Integrated OTEC Application. Offshore Technology Conference Asia. 2 indexed citations
15.
Park, Ji Eun, Jongkoo Lim, Sungjun Kim, et al.. (2018). Enhancement of mass transport in fuel cells using three-dimensional graphene foam as flow field. Electrochimica Acta. 265. 488–496. 73 indexed citations
16.
Ahn, Chi‐Yeong, Myung Su Lim, Wonchan Hwang, et al.. (2017). Effect of Porous Metal Flow Field in Polymer Electrolyte Membrane Fuel Cell under Pressurized Condition. Fuel Cells. 17(5). 652–661. 20 indexed citations
17.
Han, In‐Su, et al.. (2012). Effect of serpentine flow-field designs on performance of PEMFC stacks for micro-CHP systems. Renewable Energy. 54. 180–188. 11 indexed citations
18.
Lim, Jongkoo, et al.. (2007). 직접 메탄올 연료전지 유로 설계를 위한 3차원 모델 개발. Korean Journal of Chemical Engineering. 45(1). 93–102. 1 indexed citations
19.
Lim, Jongkoo, et al.. (2006). Gas management in flow field design using 3D direct methanol fuel cell model under high stoichiometric feed. Korean Journal of Chemical Engineering. 23(5). 753–760. 9 indexed citations
20.
Lim, Jongkoo, et al.. (2006). Three-dimensional, two-phase, CFD model for the design of a direct methanol fuel cell. Journal of Power Sources. 162(2). 992–1002. 33 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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