Abbas Azarpour
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor of Chemical Engineering
Also affiliated: Memorial University of Newfoundland (2018–2023); Shiraz University (2003–2005); Universiti Teknologi Petronas (2015–2017); University of Technology Malaysia (2011–2015)
Research Areas
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Biography and Research Information
OverviewAI-generated summary
Abbas Azarpour's research focuses on energy systems and chemical processes, with a particular emphasis on carbon capture technologies and renewable energy sources. He has conducted a state-of-the-art review on CO2 capture using potassium carbonate solutions and investigated the simultaneous removal of CO2 and H2S using MDEA solutions. His work also extends to the modeling of industrial fixed-bed catalytic reactors and catalytic trickle-bed reactors, examining their performance and development.
Azarpour has also explored the potential of renewable energy in North America, reviewing its progress, challenges, and drawbacks. His research interests include microalgal biomass and biodiesel production through co-cultivation strategies, and the optimization of supercritical carbon dioxide extraction for substances like Passiflora seed oil. His scholarship metrics include an h-index of 14, with 29 total publications and 1,150 total citations.
Metrics
- h-index: 15
- Publications: 32
- Citations: 1,251
Positions
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Assistant Professor of Chemical Engineering publications 2024–2025Southern Arkansas University Institution web page
Selected Publications
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MOF-Based CO2 Adsorption Predictions: Role of Membership and Kernel Functions in Machine Learning Models (2025)
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Predictive Modeling of CO<sub>2</sub> Adsorption in Metal–Organic Frameworks Using Hybrid Machine Learning Approaches (2025)
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Deterministic Models for Performance Analysis of Lignocellulosic Biomass Torrefaction (2025)
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Thermoeconomic Analysis of an Innovative Integrated System for Cogeneration of Liquid Hydrogen and Biomethane by a Cryogenic-Based Biogas Upgrading Cycle and Polymer Electrolyte Membrane Electrolysis (2024)
Collaboration Network
Top Collaborators
- Thermoeconomic Analysis of an Innovative Integrated System for Cogeneration of Liquid Hydrogen and Biomethane by a Cryogenic-Based Biogas Upgrading Cycle and Polymer Electrolyte Membrane Electrolysis
- Deterministic Models for Performance Analysis of Lignocellulosic Biomass Torrefaction
- Predictive Modeling of CO<sub>2</sub> Adsorption in Metal–Organic Frameworks Using Hybrid Machine Learning Approaches
- Thermoeconomic Analysis of an Innovative Integrated System for Cogeneration of Liquid Hydrogen and Biomethane by a Cryogenic-Based Biogas Upgrading Cycle and Polymer Electrolyte Membrane Electrolysis
- Deterministic Models for Performance Analysis of Lignocellulosic Biomass Torrefaction
- Predictive Modeling of CO<sub>2</sub> Adsorption in Metal–Organic Frameworks Using Hybrid Machine Learning Approaches
- Thermoeconomic Analysis of an Innovative Integrated System for Cogeneration of Liquid Hydrogen and Biomethane by a Cryogenic-Based Biogas Upgrading Cycle and Polymer Electrolyte Membrane Electrolysis
- Thermoeconomic Analysis of an Innovative Integrated System for Cogeneration of Liquid Hydrogen and Biomethane by a Cryogenic-Based Biogas Upgrading Cycle and Polymer Electrolyte Membrane Electrolysis
- Predictive Modeling of CO<sub>2</sub> Adsorption in Metal–Organic Frameworks Using Hybrid Machine Learning Approaches
- MOF-Based CO2 Adsorption Predictions: Role of Membership and Kernel Functions in Machine Learning Models
- MOF-Based CO2 Adsorption Predictions: Role of Membership and Kernel Functions in Machine Learning Models
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