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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Bahreini, M., Désilets, M., Pahija, E., Legrand, U., Guo, J., & Fink, A. G. (2024). Investigation of CO<sub>2</sub> Reduction to Formate in an Industrial-Scale Electrochemical Cell through Transient Numerical Modeling. Industrial & Engineering Chemistry Research. External link
Ma, Z., Legrand, U., Pahija, E., Tavares, J. R., & Boffito, D. C. (2021). From CO₂ to formic acid fuel cells. Industrial & Engineering Chemistry Research, 60(2), 803-815. Available
Pahija, E., Hwangbo, S., Saulnier-Bellemare, T., & Patience, G. S. (2024). Experimental methods in chemical engineering: Monte Carlo. Canadian Journal of Chemical Engineering, 25374 (14 pages). Available
Pahija, E., Panaritis, C., Gusarov, S., Shadbahr, J., Bensebaa, F., Patience, G. S., & Boffito, D. C. (2022). Experimental and Computational Synergistic Design of Cu and Fe Catalysts for the Reverse Water–Gas Shift: A Review. ACS Catalysis, 12(12), 6887-6905. External link
Pahija, E., Panaritis, C., Rutherford, B., Couillard, M., Patarachao, B., Shadbahr, J., Bensebaa, F., Patience, G. S., & Boffito, D. C. (2022). FeOₓ nanoparticle doping on Cu/Al₂O₃ catalysts for the reverse water gas shift. Journal of CO2 Utilization, 64, 102155 (9 pages). External link
Pahija, E., Lee, P. Y., Hui, C.-W., & Sin, G. (2022). Modelling of harvesting techniques for the evaluation of the density of microalgae. Applied Biochemistry and Biotechnology, 194(12), 5992-6006. External link
Pahija, E., Golshan, S., Blais, B., & Boffito, D. C. (2022). Perspectives on the Process Intensification of CO2 Capture and Utilization. Chemical Engineering and Processing - Process Intensification, 176, 8 pages. External link
Rutherford, B., Panaritis, C., Pahija, E., Couillard, M., Patarachao, B., Shadbahr, J., Bensebaa, F., Patience, G. S., & Boffito, D. C. (2023). Ni nanoparticles on Co3O4 catalyze the reverse watergas shift with 95 % CO selectivity at 300 C. Fuel, 348, 11 pages. External link
Shadbahr, J., Peeples, C. A., Pahija, E., Panaritis, C., Boffito, D. C., Patience, G. S., & Bensebaa, F. (2025). Sustainability assessment of catalyst design on CO2-derived fuel production. Renewable and Sustainable Energy Reviews, 208, 115011. External link
Sharifian, M., Hudon, N., Sarpy, G., Pahija, E., & Patience, G. S. (2024). Experimental modeling to design a heat exchanger control strategy for a Fischer–Tropsch fluidized bed. Applied Thermal Engineering, 246, 122911 (15 pages). External link
