Modeling and Simulation

Monjur, M. . S., Demirel, S. . E., Li, J. ., & Hasan, M. . M. F. (2021). SPICE_MARS: A Process Synthesis Framework for Membrane-Assisted Reactive Separations. Industrial & Engineering Chemistry Research, 60, 7635-7655. https://doi.org/10.1021/ACS.IECR.1C00021 (Original work published 2025)

Manoharan, S. ., Lee, K. ., Freiberg, L. ., Coblyn, M. ., Jovanovic, G. ., & Paul, B. . K. (2019). Comparing the economics of metal additive manufacturing processes for micro-scale plate reactors in the chemical process industry. Procedia Manufacturing, 34, 603-612. Pennsylvania: Elsevier B.V. https://doi.org/10.1016/j.promfg.2019.06.168

Li, J. ., Demirel, S. . E., & Hasan, M. . M. F. (2018). Process synthesis using block superstructure with automated flowsheet generation and optimization. AIChE Journal, 64, 3082-3100. https://doi.org/10.1002/aic.16219 (Original work published 2025)

Shade, D. ., Marszalek, B. ., & Walton, K. . S. (2021). Structural similarity, synthesis, and adsorption properties of aluminum-based metal-organic frameworks. Adsorption, 27, 227-236. https://doi.org/10.1007/s10450-020-00282-9 (Original work published 2025)

Tula, A. . K., Eden, M. . R., & Gani, R. . (2019). Component based development of computer-aided tools for different applications. Computer Aided Chemical Engineering, 46, 91–96. https://doi.org/10.1016/B978-0-12-818634-3.50016-3 (Original work published 2025)

Tian, Y. ., Mannan, S. ., & Pistikopoulos, E. . N. (2018). Towards a systematic framework for the synthesis of operable process intensification systems. Computer Aided Chemical Engineering, 44, 2383-2388. https://doi.org/10.1016/B978-0-444-64241-7.50392-X (Original work published 2025)

Bingel, L. . W., Chen, A. ., Agrawal, M. ., & Sholl, D. . S. (2020). Experimentally Verified Alcohol Adsorption Isotherms in Nanoporous Materials from Literature Meta-Analysis. Journal of Chemical and Engineering Data, 65, 4970-4979. https://doi.org/10.1021/acs.jced.0c00598 (Original work published 2025)

Mohammadi, S. ., & Cremaschi, S. . (2019). Efficiency of Uncertainty Propagation Methods for Estimating Output Moments. Computer Aided Chemical Engineering, 47, 487-492. https://doi.org/10.1016/b978-0-12-818597-1.50078-3

Tian, Y. ., Sam Mannan, M. ., Kravanja, Z. ., & Pistikopoulos, E. . N. (2018). Towards the synthesis of modular process intensification systems with safety and operability considerations - application to heat exchanger network. 28 European Symposium on Computer Aided Process Engineering, 43, 705-710. https://doi.org/10.1016/B978-0-444-64235-6.50125-X (Original work published 2025)

Feng, J. ., Lansford, J. . L., Katsoulakis, M. . A., & Vlachos, D. . G. (2020). Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences. Science Advances, 6, 3204-3218. https://doi.org/10.1126/sciadv.abc3204 (Original work published 2025)