Thomas Igou

669 total citations
26 papers, 481 citations indexed

About

Thomas Igou is a scholar working on Renewable Energy, Sustainability and the Environment, Environmental Chemistry and Water Science and Technology. According to data from OpenAlex, Thomas Igou has authored 26 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Renewable Energy, Sustainability and the Environment, 8 papers in Environmental Chemistry and 6 papers in Water Science and Technology. Recurrent topics in Thomas Igou's work include Algal biology and biofuel production (11 papers), Aquatic Ecosystems and Phytoplankton Dynamics (6 papers) and Innovations in Aquaponics and Hydroponics Systems (3 papers). Thomas Igou is often cited by papers focused on Algal biology and biofuel production (11 papers), Aquatic Ecosystems and Phytoplankton Dynamics (6 papers) and Innovations in Aquaponics and Hydroponics Systems (3 papers). Thomas Igou collaborates with scholars based in United States, China and South Korea. Thomas Igou's co-authors include Yongsheng Chen, Steven W. Van Ginkel, Shifa Zhong, Elliot Reid, Haiping Gao, Guanghui Lan, Terry W. Snell, Yangying Zhao, Lan Gan and Wenlong Zhang and has published in prestigious journals such as Environmental Science & Technology, Applied Energy and International Journal of Molecular Sciences.

In The Last Decade

Thomas Igou

22 papers receiving 468 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas Igou United States 13 166 134 103 87 67 26 481
M. Pachés Spain 14 251 1.5× 92 0.7× 77 0.7× 120 1.4× 26 0.4× 35 645
Jean‐Sébastien Deschênes Canada 15 400 2.4× 94 0.7× 103 1.0× 147 1.7× 22 0.3× 49 734
Madhumanti Mondal India 14 701 4.2× 93 0.7× 65 0.6× 285 3.3× 52 0.8× 17 933
José F. Casanueva Spain 11 111 0.7× 140 1.0× 30 0.3× 31 0.4× 45 0.7× 12 506
S. K. Patidar India 9 385 2.3× 126 0.9× 85 0.8× 149 1.7× 24 0.4× 15 580
Lakshmanan Uma India 17 475 2.9× 35 0.3× 96 0.9× 285 3.3× 66 1.0× 31 872
Zongbo Yang China 15 593 3.6× 36 0.3× 146 1.4× 132 1.5× 115 1.7× 21 752
Zhongyu Guo China 13 110 0.7× 154 1.1× 36 0.3× 60 0.7× 62 0.9× 33 576
Asemgul K. Sadvakasova Kazakhstan 16 403 2.4× 33 0.2× 55 0.5× 133 1.5× 81 1.2× 53 700

Countries citing papers authored by Thomas Igou

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Igou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Igou

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Igou. A scholar is included among the top collaborators of Thomas Igou 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 Thomas Igou. Thomas Igou 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.
2.
Reid, Elliot, Qingquan Ma, Lan Gan, et al.. (2025). Improving the Hydrophobicity of Powder Activated Carbon to Enhance the Adsorption Kinetics of Per- and Polyfluoroalkyl Substances. ACS ES&T Water. 5(5). 2322–2332. 1 indexed citations
3.
4.
Cheng, Lin, et al.. (2025). Machine Learning-Assisted Expert Control in Wastewater Aeration Treatment Process Application. ACS ES&T Engineering. 5(11). 3140–3152.
5.
Igou, Thomas, et al.. (2025). Per- and polyfluoroalkyl substances (PFAS) in resource recovery: Transforming challenges into opportunities for sustainable nutrients and biosolids management. Process Safety and Environmental Protection. 203. 107980–107980. 1 indexed citations
6.
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Zhong, Shifa, et al.. (2024). Screening Environmentally Benign Ionic Liquids for CO2 Absorption Using Representation Uncertainty-Based Machine Learning. Environmental Science & Technology Letters. 11(11). 1193–1199. 3 indexed citations
8.
Reid, Elliot, Thomas Igou, Yangying Zhao, et al.. (2023). The Minus Approach Can Redefine the Standard of Practice of Drinking Water Treatment. Environmental Science & Technology. 57(18). 7150–7161. 32 indexed citations
9.
Zhong, Shifa, et al.. (2023). Development of gradient boosting-assisted machine learning data-driven model for free chlorine residual prediction. Frontiers of Environmental Science & Engineering. 18(2). 10 indexed citations
10.
Igou, Thomas, Shifa Zhong, Elliot Reid, & Yongsheng Chen. (2023). Real-Time Sensor Data Profile-Based Deep Learning Method Applied to Open Raceway Pond Microalgal Productivity Prediction. Environmental Science & Technology. 57(46). 17981–17989. 15 indexed citations
11.
Zhong, Shifa, et al.. (2022). Enlarging Applicability Domain of Quantitative Structure–Activity Relationship Models through Uncertainty-Based Active Learning. ACS ES&T Engineering. 2(7). 1211–1220. 19 indexed citations
12.
Zhang, Bopeng, et al.. (2020). Backwash sequence optimization of a pilot-scale ultrafiltration membrane system using data-driven modeling for parameter forecasting. Journal of Membrane Science. 612. 118464–118464. 35 indexed citations
13.
Ginkel, Steven W. Van, et al.. (2018). Environmental influence on rotenone performance as an algal crop protective agent to prevent pond crashes for biofuel production. Algal Research. 33. 277–283. 9 indexed citations
14.
Sun, Yingqiang, et al.. (2018). Effect of water content on [Bmim][HSO4] assisted in-situ transesterification of wet Nannochloropsis oceanica. Applied Energy. 226. 461–468. 30 indexed citations
15.
Ginkel, Steven W. Van, et al.. (2016). The Selective Use of Hypochlorite to Prevent Pond Crashes for Algae‐Biofuel Production. Water Environment Research. 88(1). 70–78. 31 indexed citations
16.
Ginkel, Steven W. Van, et al.. (2016). The prevention of saltwater algal pond contamination using the electron transport chain disruptor, rotenone. Algal Research. 18. 209–212. 14 indexed citations
17.
Ginkel, Steven Van, Thomas Igou, Hao Fu, et al.. (2015). Use of Copper to Selectively Inhibit Brachionus calyciflorus (Predator) Growth in Chlorella kessleri (Prey) Mass Cultures for Algae Biodiesel Production. International Journal of Molecular Sciences. 16(9). 20674–20684. 25 indexed citations
18.
Ginkel, Steven W. Van, et al.. (2015). Taking advantage of rotifer sensitivity to rotenone to prevent pond crashes for algal-biofuel production. Algal Research. 10. 100–103. 34 indexed citations
19.
Xu, Chunyan, et al.. (2015). The Use of the Schizonticidal Agent Quinine Sulfate to Prevent Pond Crashes for Algal-Biofuel Production. International Journal of Molecular Sciences. 16(11). 27450–27456. 14 indexed citations
20.
Igou, Thomas, et al.. (2014). Effect of Centrifugation on Water Recycling and Algal Growth to Enable Algae Biodiesel Production. Water Environment Research. 86(12). 2325–2329. 2 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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