Yannick Ureel

470 total citations · 1 hit paper
18 papers, 309 citations indexed

About

Yannick Ureel is a scholar working on Materials Chemistry, Biomedical Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Yannick Ureel has authored 18 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Materials Chemistry, 6 papers in Biomedical Engineering and 5 papers in Computational Theory and Mathematics. Recurrent topics in Yannick Ureel's work include Thermochemical Biomass Conversion Processes (6 papers), Machine Learning in Materials Science (5 papers) and Computational Drug Discovery Methods (5 papers). Yannick Ureel is often cited by papers focused on Thermochemical Biomass Conversion Processes (6 papers), Machine Learning in Materials Science (5 papers) and Computational Drug Discovery Methods (5 papers). Yannick Ureel collaborates with scholars based in Belgium, Netherlands and United States. Yannick Ureel's co-authors include Kevin M. Van Geem, Florence H. Vermeire, Robin John Varghese, Mehrdad Seifali Abbas‐Abadi, Georgios D. Stefanidis, Andreas Eschenbacher, Jogchum Oenema, Maarten R. Dobbelaere, Maarten K. Sabbe and Christian V. Stevens and has published in prestigious journals such as SHILAP Revista de lepidopterología, Analytical Chemistry and Chemical Engineering Journal.

In The Last Decade

Yannick Ureel

17 papers receiving 302 citations

Hit Papers

Challenges and opportunities of light olefin production v... 2023 2026 2024 2025 2023 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yannick Ureel Belgium 7 105 103 72 68 65 18 309
Elena Hájeková Slovakia 12 127 1.2× 172 1.7× 96 1.3× 75 1.1× 56 0.9× 21 349
Jaromír Lederer Czechia 10 78 0.7× 168 1.6× 40 0.6× 93 1.4× 43 0.7× 24 355
Yuehong Zhao China 13 64 0.6× 98 1.0× 36 0.5× 58 0.9× 126 1.9× 33 364
Zezhou Chen China 12 83 0.8× 271 2.6× 66 0.9× 137 2.0× 50 0.8× 27 437
Dipesh Patel United Kingdom 12 38 0.4× 159 1.5× 24 0.3× 115 1.7× 235 3.6× 15 517
Alp Er Ş. Konukman Türkiye 12 28 0.3× 48 0.5× 28 0.4× 71 1.0× 93 1.4× 25 384
Xin Dai China 11 47 0.4× 135 1.3× 20 0.3× 98 1.4× 63 1.0× 31 423
Shuhua Yang China 10 36 0.3× 234 2.3× 33 0.5× 97 1.4× 78 1.2× 22 339
P. E. Gloor Canada 10 32 0.3× 79 0.8× 35 0.5× 78 1.1× 82 1.3× 10 526
Xiaohong Gao China 12 27 0.3× 52 0.5× 32 0.4× 17 0.3× 188 2.9× 27 512

Countries citing papers authored by Yannick Ureel

Since Specialization
Citations

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

Fields of papers citing papers by Yannick Ureel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yannick Ureel

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

All Works

18 of 18 papers shown
1.
Ureel, Yannick, et al.. (2025). Microkinetic Modeling of Plastic Waste Catalytic Cracking with Phosphorus-Modified Mesoporous HZSM-5: An Iso-Octane Model Compound Study. Industrial & Engineering Chemistry Research. 64(34). 16563–16573.
2.
Ureel, Yannick, et al.. (2025). Genesys-Cat: automatic microkinetic model generation for heterogeneous catalysis with improved Bayesian optimization. Catalysis Science & Technology. 15(3). 750–764. 4 indexed citations
3.
Ureel, Yannick, et al.. (2025). Organochloride Speciation in Plastic Pyrolysis Oil by GC × GC Coupled to High-Resolution TOF-MS Using Scripting Expressions. Analytical Chemistry. 97(20). 10680–10690. 3 indexed citations
4.
Ureel, Yannick, et al.. (2025). Detailed analysis of olefins and diolefins in hydrotreated plastic waste pyrolysis oils by GC-VUV. Waste Management. 202. 114828–114828. 2 indexed citations
5.
Ureel, Yannick, Martha L. Chacón‐Patiño, Marvin Kusenberg, et al.. (2024). Compositional Analysis of Oxygenates and Hydrocarbons in Waste and Virgin Polyolefin Pyrolysis Oils by Ultrahigh-Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Energy & Fuels. 39(2). 1283–1295. 4 indexed citations
7.
Ureel, Yannick, et al.. (2024). Electrification pathways for sustainable syngas production: A comparative analysis for low-temperature Fischer-Tropsch technology. International Journal of Hydrogen Energy. 81. 974–985. 5 indexed citations
8.
Ureel, Yannick, et al.. (2024). Coke Formation in Steam Cracking Reactors: Deciphering the Impact of Aromatic Compounds and Temperature on Fouling Dynamics. Industrial & Engineering Chemistry Research. 63(21). 9391–9403. 5 indexed citations
9.
Ureel, Yannick, Konstantinos Alexopoulos, Kevin M. Van Geem, & Maarten K. Sabbe. (2024). Predicting the effect of framework and hydrocarbon structure on the zeolite-catalyzed beta-scission. Catalysis Science & Technology. 14(24). 7020–7036. 5 indexed citations
10.
Ureel, Yannick, Martha L. Chacón‐Patiño, Marvin Kusenberg, et al.. (2024). Characterization of PP and PE Waste Pyrolysis Oils by Ultrahigh-Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Energy & Fuels. 38(12). 11148–11160. 10 indexed citations
11.
12.
Ureel, Yannick, Maarten R. Dobbelaere, István Lengyel, et al.. (2024). Machine learning applications for thermochemical and kinetic property prediction. Reviews in Chemical Engineering. 41(4). 419–449. 6 indexed citations
13.
Ureel, Yannick, Florence H. Vermeire, Maarten K. Sabbe, & Kevin M. Van Geem. (2023). Beyond group additivity: Transfer learning for molecular thermochemistry prediction. Chemical Engineering Journal. 472. 144874–144874. 12 indexed citations
14.
Ureel, Yannick, Maarten R. Dobbelaere, Yi Ouyang, et al.. (2023). Active Machine Learning for Chemical Engineers: A Bright Future Lies Ahead!. Engineering. 27. 23–30. 20 indexed citations
15.
Abbas‐Abadi, Mehrdad Seifali, Yannick Ureel, Andreas Eschenbacher, et al.. (2023). Challenges and opportunities of light olefin production via thermal and catalytic pyrolysis of end-of-life polyolefins: Towards full recyclability. Progress in Energy and Combustion Science. 96. 101046–101046. 133 indexed citations breakdown →
16.
Dobbelaere, Maarten R., et al.. (2022). Machine Learning for Physicochemical Property Prediction of Complex Hydrocarbon Mixtures. Industrial & Engineering Chemistry Research. 61(24). 8581–8594. 34 indexed citations
17.
Ureel, Yannick, Florence H. Vermeire, Maarten K. Sabbe, & Kevin M. Van Geem. (2022). Ab Initio Group Additive Values for Thermodynamic Carbenium Ion Property Prediction. Industrial & Engineering Chemistry Research. 62(1). 223–237. 6 indexed citations
18.
Ureel, Yannick, et al.. (2022). Active learning-based exploration of the catalytic pyrolysis of plastic waste. Fuel. 328. 125340–125340. 24 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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