Recent Publications
Copies available upon request2024
1. Yuya Takakura, Suryateja Ravutla, Jinsu Kim, Keisuke Ikeda, Hiroshi Kajiro, Tomoyuki Yajima, Junpei Fujiki, Fani Boukouvala, Matthew Realff, Yoshiaki Kawajiri, Surrogate model optimization of vacuum pressure swing adsorption using a flexible metal organic framework with hysteretic sigmoidal isotherms, International Journal of Greenhouse Gas Control (in press)2. Zou, T.; Yajima, T.; Kawajiri, Y., A parameter estimation method for chromatographic separation process based on physics-informed neural network. J. Chromatogr. A 2024, 1730, 465077.
3. Yuyama, S.; Machida, H.; Yajima, T.; Kawajiri, Y., Modeling and uncertainty quantification of CO2 absorption process using phase separation solvent. Chem. Eng. Sci. 2024, 298.
4. Sugiyama, H.; Yamamoto, Y.; Suzuki, K.; Yajima, T.; Kawajiri, Y., Parameter estimation for reactive chromatography model by Bayesian inference and parallel sequential Monte Carlo. Chem. Eng. Res. Des. 2024, 203, 378-390.
5. Okumura, T.; Yamaguchi, T.; Nishibe, S.; Numaguchi, R.; Kawajiri, Y., Modeling of moving bed CO2 capture process using amine solid adsorbent and its validation using pilot plant test data. International Journal of Greenhouse Gas Control 2024, 133, 104094.
6. Harada, H.; Sinha, A.; Yajima, T.; Kawajiri, Y., Model-based techno–economic analysis of an integrated synthetic natural gas production system with direct air capture and water electrolysis. Carbon Capture Science & Technology 2024, 10, 100181.
7. El-Shafie, M.; Harada, H.; Yajima, T.; Tsuda, S.; Inazu, K.; Kawajiri, Y., A comprehensive analysis of ammonia synthesis over a commercial iron-based catalyst using differential and integral reactor models. Int. J. Hydrogen Energy 2024, 58, 1009-1019.
8. Suzuki, K.; Yajima, T.; Kawajiri, Y., Process Robustness Evaluation for Various Operating Configurations of Simulated Moving Bed Chromatography. In Comput. Aided Chem. Eng., Elsevier: 2024; Vol. 53, pp 229-234.
9. Harada, H.; Sinha, A.; Yajima, T.; Kawajiri, Y., Model-based techno-economic analysis for integrated synthetic natural gas production system using atmospheric CO2 captured by metal organic framework adsorbent. In Comput. Aided Chem. Eng., Elsevier: 2024; Vol. 53, pp 2023-2028.
2023
1. Yuan, Z.; Yamamoto, Y.; Yajima, T.; Kawajiri, Y., Estimation and statistical analysis of model parameters using sequential Monte Carlo for phenol and p-cresol separation. Journal of Chromatography A 2023, 1688, 463703.2. Sugiura, Y.; Yajima, T.; Kawajiri, Y., Mapping adsorbent properties to optimal process performance of two-bed temperature swing adsorption by superstructure optimization. Chemical Engineering and Processing - Process Intensification 2023, 191.
3. Sugimoto, S.; Takakura, Y.; Kajiro, H.; Fujiki, J.; Dashti, H.; Yajima, T.; Kawajiri, Y., Modeling, parameter estimation, and uncertainty quantification for CO2 adsorption process using flexible metal–organic frameworks by Bayesian Monte Carlo methods. Journal of Advanced Manufacturing and Processing 2023.
4. Kuwabara, Y.; Tokunaga, T.; Moriyama, T.; Koizumi, M.; Mizuno, S.; Hagino, T.; Kusaka, S.; Matsuda, R.; Yajima, T.; Kawajiri, Y., Subambient temperature swing adsorption utilizing cold energy from liquefied natural gas. International Journal of Greenhouse Gas Control 2023, 126.
5. Kim, Y.; Kawajiri, Y.; Rousseau, R. W.; Grover, M. A., Modeling of Nucleation, Growth, and Dissolution of Paracetamol in Ethanol Solution for Unseeded Batch Cooling Crystallization with Temperature-Cycling Strategy. Ind. Eng. Chem. Res. 2023, 62 (6), 2866-2881.
6. Kakiuchi, T.; Yajima, T.; Shigaki, N.; Kawajiri, Y., Modeling and optimal design of multicomponent vacuum pressure swing adsorber for simultaneous separation of carbon dioxide and hydrogen from industrial waste gas. Adsorption 2023, 29, 9-27.
7. Fujiki, J.; Kajiro, H.; Takakura, Y.; Yajima, T.; Kawajiri, Y., Breakthrough analysis for parameter estimation of CO2 adsorption on pelletized flexible metal–organic framework. Chem. Eng. J. 2023, 460, 141781.
2022
1. Tsuboi, T.; Yasuda, S.; Choi, C.; Zhang, W.; Machida, H.; Norinaga, K.; Yajima, T.; Kawajiri, Y., Modeling and estimating kinetic parameters for CO2 methanation from fixed bed reactor experiments. Journal of Advanced Manufacturing and Processing 2022, 5 (1), e10145.2. Takakura, Y.; Sugimoto, S.; Fujiki, J.; Kajiro, H.; Yajima, T.; Kawajiri, Y., Model-Based Analysis of a Highly Efficient CO2 Separation Process Using Flexible Metal–Organic Frameworks with Isotherm Hysteresis. ACS Sustainable Chemistry & Engineering 2022, 10 (45), 14935-14947.
3. Sinha, A.; Thakkar, H.; Rezaei, F.; Kawajiri, Y.; Realff, M. J., Reduced building energy consumption by combined indoor CO2 and H2O composition control. Applied Energy 2022, 322.
4. Shigaki, N.; Mogi, Y.; Kijima, H.; Kakiuchi, T.; Yajima, T.; Kawajiri, Y., Performance evaluation of gas fraction vacuum pressure swing adsorption for CO2 capture and utilization process. International Journal of Greenhouse Gas Control 2022, 120.
5. Kojima, S.; Park, J.; Carter, E. A.; Walton, K. S.; Realff, M. J.; Sholl, D. S.; Yajima, T.; Fujiki, J.; Kawajiri, Y., Discrepancy quantification between experimental and simulated data of CO2 adsorption isotherm using hierarchical Bayesian estimation. Sep. Purif. Technol. 2022, 296.
6. Harada, H.; Suzuki, K.; Sato, K.; Okada, K.; Tsuruta, M.; Yajima, T.; Kawajiri, Y., Process development for advanced simulated moving bed (ASMB) chromatography by parameter refinement using pilot plant experimental data. Sep. Purif. Technol. 2022, 281.
7. Suzuki, K.; Yajima, T.; Kawajiri, Y. In Comprehensive Quantification of Model Prediction Uncertainty for Simulated Moving Bed Chromatography, Computer Aided Chemical Engineering: Proceedings of the 14th International Symposium on Process Systems Engineering – PSE 2021+, Kyoto, Japan, Yamashita, Y.; Kano, M., Eds. Elsevier, B.V.: Kyoto, Japan, 2022; pp 943-948.
8. Kakiuchi, T.; Yajima, T.; Shigaki, N.; Kawajiri, Y., Modeling and Optimal Design of Pressure Swing Adsorber for Carbon Dioxide and Hydrogen Separation from Industrial Waste Gas. In 14th International Symposium on Process Systems Engineering – PSE 2021+, Yamashita, Y.; Kano, M., Eds. Kyoto, Japan, 2022.
