Research projects
Adsorption processes
Adsorptive separation is a crucial technique utilized in many fields such as CO2 recovery, pharmaceuticals, food, etc. Our research group applies process systems engineering techniques to adsorption processes for modeling, design, and optimization. Our group owns experimental setups, where we obtain experimental data ourselves to streamline development of adsorption processes.Recent topics include:
- Optimal design of adsorption and chromatographic separation processes
- Modeling, design and economic evaluation of CO2 separation processes
- Design and optimization of direct air capture (DAC) processes
- Simulated moving bed chromatography
- Bayesian estimation for adsorption equilibria and processes
Data utilization and uncertainty quantification
Recent data science techniques are changing our approaches to chemical process development. In our research group, we analyze experimental and operational data to establish highly predictable and reliable models. We also tackle process optimization utilizing such models.Recent topics include:
- Design of processes with uncertainties
- Advanced simulation by statistical methods
- Design making for processes with uncertainty
- Optimization approaches and its application
External Links
>>>Optimization program for simulate moving bed chromatography, Pyomo DAE Kensuke Suzuki, Doctoral Student
Reference: Suzuki et al. Journal of Advanced Manufacturing and Processing, e10103, 2021 https://doi.org/10.1002/amp2.10103
>>>Uncertainty quantification for chromatographic process model parameters by Bayesian inference using sequential monte carlo method
Yota Yamamoto, M.S. March 2021
Reference: Yamamoto et al. Chemical Engineering Research and Design, 175, 223-237, 2021 https://doi.org/10.1016/j.cherd.2021.09.003
Simulated moving bed chromatography system
Simulated moving bed chromatography system
Adsorption breakthrough experimetal unit (Dr. Junpei Fujiki)
