Dr Masoud Khajenoor | Chemical Engineering | Engineering Development Award

Dr, Masoud Khajenoori, University of Kashan, Iran

Dr. Masoud Khajenoori is an Assistant Professor in the Department of Chemical Engineering at the Faculty of Engineering. With extensive experience in heterogeneous catalysis, gas separation technologies, and simulation of molecular dynamics, he has established himself as a dedicated researcher in the field. His scientific interests include dry reforming of methane over nano-catalysts, modeling of gas centrifuge systems, and investigation of mass transfer in human airways. Dr. Khajenoori has co-authored multiple peer-reviewed journal articles, collaborating with researchers across fields such as nanotechnology, chemical engineering, and nuclear science. His work addresses both fundamental and applied aspects of energy-efficient gas separation and reaction mechanisms. Through his research, Dr. Khajenoori aims to contribute to sustainable energy solutions and advanced separation systems. He actively mentors students and participates in collaborative research projects, enhancing interdisciplinary academic activities and bridging theoretical research with industrial application.

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🔹 Education 

Dr. Masoud Khajenoori holds a Ph.D. in Chemical Engineering, specializing in molecular simulation and heterogeneous catalysis. His academic training provided a solid foundation in the principles of reaction engineering, mass transfer, and nanomaterials. He pursued both his undergraduate and graduate studies in top-ranked institutions, where he focused on advanced simulation techniques including Direct Simulation Monte Carlo (DSMC) and computational modeling of gas-solid systems. His doctoral research emphasized the development and application of nano-catalysts for dry reforming reactions, with a specific interest in CeO₂-promoted Ni/MgO catalysts. Throughout his academic journey, Dr. Khajenoori was recognized for his analytical skills, academic excellence, and interdisciplinary approach to solving complex engineering problems. His strong background in physics, thermodynamics, and numerical methods enables him to carry out pioneering research in gas centrifugation and nanoparticle behavior under various flow conditions. He continues to apply this expertise in both teaching and research activities.

🔹 Employment

Dr. Masoud Khajenoori is currently employed as an Assistant Professor in the Department of Chemical Engineering, Faculty of Engineering. He holds a full-time, on-contract position, where he actively teaches undergraduate and graduate courses in reaction engineering, process simulation, and heat and mass transfer. As a faculty member, he has contributed significantly to curriculum development and academic planning, ensuring alignment with global research and industry trends. Beyond teaching, Dr. Khajenoori leads several research projects focusing on gas centrifuge modeling, nano-catalysis, and chemical process optimization. He plays a vital role in mentoring students, supervising thesis projects, and fostering interdisciplinary collaborations with national and international partners. He frequently engages in publishing high-impact journal articles and contributes to peer reviews for scientific journals. His employment reflects a commitment to advancing both academic excellence and technological innovation in chemical engineering.

🔹 Research Focus

Dr. Masoud Khajenoori’s research centers on gas separation technologies, catalytic processes, and computational modeling. His primary focus lies in the dry reforming of methane using nano-engineered catalysts such as CeO₂-promoted Ni/MgO, addressing both energy efficiency and CO₂ utilization. He has developed comprehensive models for gas centrifuge systems using DSMC (Direct Simulation Monte Carlo) and Sickafus analytical methods, enabling precise simulations of multi-component gas separation. Another area of his research involves the prediction and modeling of physical properties like thermal conductivity and viscosity in rare gases and radioactive compounds. Additionally, he has worked on simulations of nanoparticle deposition in human airways, bridging chemical engineering and biomedical applications. His recent projects extend into molecular pump optimization using metaheuristic algorithms, reflecting a strong commitment to computational chemical engineering. Dr. Khajenoori’s work provides novel insights into improving separation power, catalyst performance, and sustainable gas processing technologies.

🔹 Publication Top Notes

1. Dry reforming over CeO₂-promoted Ni/MgO nano-catalyst: effect of Ni loading and CH₄/CO₂ molar ratio

• Authors: M. Khajenoori, M. Rezaei, F. Meshkani

• Journal: Journal of Industrial and Engineering Chemistry, Vol. 21, Pages 717–722, 2015

• Citations: 116

• Summary:
  This study investigates the catalytic performance of CeO₂-promoted Ni/MgO nano-catalysts in the dry reforming of methane (DRM). The researchers evaluated how varying nickel loadings and CH₄/CO₂ ratios affect conversion efficiency and catalyst stability. Results showed that an optimal Ni content improves dispersion, reduces sintering, and enhances resistance to carbon deposition. CeO₂ acts as a structural promoter, increasing oxygen storage and supporting CO₂ activation. This research contributes to the development of sustainable reforming processes using greenhouse gases as feedstocks.

2. Simulation of Gas Centrifuge Separation Process for Binary and Ternary Isotope Mixtures Using Direct Simulation Monte Carlo (DSMC) Method

• Authors: M. Khajenoori, A. R. Alaei

• Journal: Progress in Nuclear Energy, Vol. 85, Pages 506–516, 2015

• Citations: 41

• Summary:
  This paper presents a DSMC-based simulation for analyzing gas centrifuge separation efficiency in binary and ternary isotope mixtures, particularly uranium enrichment. The study compares simulation results with analytical models and experimental benchmarks, showing excellent agreement and improved understanding of separation mechanisms at molecular levels. The findings support the optimization of gas centrifuge designs in nuclear fuel cycles.

3. Thermal Conductivity and Viscosity Prediction of Rare Gases and Radioactive Gas Mixtures Using Artificial Neural Networks

• Authors: M. Khajenoori, H. Khorsand, M. Rezaei

• Journal: Applied Thermal Engineering, Vol. 60, Issues 1–2, Pages 129–136, 2013

• Citations: 36

• Summary:
  This research applies artificial neural network (ANN) models to predict the thermal conductivity and viscosity of rare gases and radioactive gas mixtures, often used in nuclear and space applications. The ANN model achieved high accuracy compared to traditional equations, offering a fast and reliable predictive tool for complex gas behavior under varied temperature and pressure conditions.

4. Study of Nanoparticles’ Deposition in Human Airways Using a Two-phase Eulerian–Lagrangian Model

• Authors: M. Khajenoori, A. Ebrahimnia-Bajestan, M. B. Shafii

• Journal: Journal of Aerosol Science, Vol. 103, Pages 32–43, 2016

• Citations: 29

• Summary:
  This interdisciplinary study models how inhaled nanoparticles deposit in the respiratory tract using a two-phase flow simulation approach. The research is significant in evaluating health risks of nano-sized particles from environmental and industrial exposure. Findings highlight the impact of particle size, breathing rate, and flow dynamics on deposition efficiency in various airway regions.

5. CFD Simulation and Optimization of Molecular Drag Pump Using Genetic Algorithm and Response Surface Method

• Authors: M. Khajenoori, M. Aminyavari, M. T. Ahmadi

• Journal: Vacuum, Vol. 119, Pages 173–182, 2015

• Citations: 22

• Summary:
  The paper combines computational fluid dynamics (CFD), genetic algorithms (GA), and response surface methodology (RSM) to optimize the performance of molecular drag pumps (MDPs). By adjusting geometrical parameters, the team significantly enhanced throughput and compression ratios. The integrated approach serves as a blueprint for designing high-performance vacuum systems used in electronics and semiconductors.

6. Experimental and Theoretical Study on CeO₂-modified Ni Catalysts Supported on Mesoporous MgO for CO₂ Reforming of Methane

• Authors: M. Khajenoori, F. Meshkani, A. A. Mirzaei

• Journal: International Journal of Hydrogen Energy, Vol. 38, Issue 4, Pages 1905–1916, 2013

• Citations: 61

• Summary:
  This article investigates the effect of CeO₂ addition on Ni/MgO catalysts prepared via sol–gel and co-precipitation methods for CO₂ reforming of methane. The CeO₂-modified catalysts displayed superior catalytic stability, higher activity, and resistance to carbon formation. Experimental results were validated using kinetic modeling and characterization techniques like XRD and BET analysis.

Conclusion

Dr. Masoud Khajenoori demonstrates strong potential and current achievements in engineering research and development. His work on process modeling, clean energy, and advanced simulations contributes meaningfully to engineering knowledge and innovation. While he would benefit from increased industry collaboration and wider dissemination of his work, his solid research foundation, technical sophistication, and contribution to education make him a strong contender for the Research for Engineering Development Award.