dr.ing. A. Banerjee (Aayan)

Engineering & Materials Science

# Cathodes
# Electrodes
# Electrolysis
# Gases
# Oxides
# Regenerative Fuel Cells
# Solid Oxide Fuel Cells (Sofc)
# Thermal Gradients

Faculty of Science and Technology (TNW), Catalytic Processes and Materials (CPM)

We develop integrated multi-scale models to better understand and rationally scale up next generation chemical and electrochemical technologies from innovative lab-scale devices to novel industrial systems. We employ a hierarchical approach to accurately predict the performance, lifetime, and cost of commercial-scale systems directly from material, catalytic and morphological properties measured in the lab using a myriad of techniques including detailed micro-kinetic reaction modelling, structural evolution modelling, continuum transport modelling and machine learning.

Our various research works on high temperature solid oxide cell technology utilizing this integrated multiscale approach are showcased in this Wiley article: https://onlinelibrary.wiley.com/doi/full/10.1002/cite.202100199

Active Projects

Exploring the impact of solid oxide cell size on performance and reliability (NWO KICH1.ED04.20.020)

Solid Oxide Electrolysis is an energy-efficient conversion technology enabling green chemicals and fuels generation. Together with TNO, KIT, Sunfire and Shell, we will address the scale-up of the technology towards multi-MW scale by determining the maximum size for a solid oxide cell that can tolerate electrolysis operation without mechanical failure.

Direct CO₂ methanation inside a proton-conducting solid oxide electrolyser (NWO KICH1.ED04.20.018)

Next-generation proton ceramic electrolysers offer the promise of efficient synthesis of high value chemicals and fuels from relatively abundant and inexpensive raw materials. Together with EIFER and Shell, we will test that promise by attempting to make synthetic methane inside a proton ceramic cell using CO₂, steam, and electricity.

Banerjee, A. (2022). Integrated Multiscale Modeling of Solid Oxide Electrodes, Cells, Stacks, and Systems. Chemie-Ingenieur-Technik, 94(5), 766-773. https://doi.org/10.1002/cite.202100199

Williams, N. J., Seymour, I. D., Leah, R. T. , Banerjee, A., Mukerjee, S., & Skinner, S. J. (2022). Non-equilibrium thermodynamics of mixed ionic-electronic conductive electrodes and their interfaces: a Ni/CGO study. Journal of Materials Chemistry A. https://doi.org/10.1039/D1TA07351F

Wehrle, L., Wang, Y., Boldrin, P., Brandon, N. P., Deutschmann, O. , & Banerjee, A. (2022). Optimizing Solid Oxide Fuel Cell Performance to Re-evaluate Its Role in the Mobility Sector. ACS Environmental Au, 2(1), 42-64. https://doi.org/10.1021/acsenvironau.1c00014

Chowdhury, R., Zhao, Y., Xia, Y., Ouyang, M., Brandon, N. , & Banerjee, A. (2021). Revisiting the promise of Bi-layer graded cathodes for improved Li-ion battery performance. Sustainable Energy & Fuels, 5(20), 5193-5204. https://doi.org/10.1039/D1SE01077H

Wehrle, L., Schmider, D., Dailly, J. , Banerjee, A., & Deutschmann, O. (2021). Model-based optimization of solid oxide electrolysis cells and stacks for powerto- gas applications. In ECS Transactions (1 ed., Vol. 103, pp. 545-554). (ECS Transactions; Vol. 103, No. 1). IOP Publishing Ltd.. https://doi.org/10.1149/10301.0545ecst

Chowdhury, R. , Banerjee, A., Zhao, Y., Liu, X., & Brandon, N. (2021). Simulation of bi-layer cathode materials with experimentally validated parameters to improve ion diffusion and discharge capacity. Sustainable Energy & Fuels, 5(4), 1103-1119. https://doi.org/10.1039/d0se01611j

Wang, Y., Wehrle, L. , Banerjee, A., Shi, Y., & Deutschmann, O. (2021). Analysis of a biogas-fed SOFC CHP system based on multi-scale hierarchical modeling. Renewable energy, 163, 78-87. https://doi.org/10.1016/j.renene.2020.08.091

Wiranarongkorn, K. , Banerjee, A., Deutschmann, O., & Arpornwichanop, A. (2020). Performance analysis and temperature gradient of solid oxide fuel cell stacks operated with bio-oil sorption-enhanced steam reforming. International journal of hydrogen energy, 45(21), 12108-12120. https://doi.org/10.1016/j.ijhydene.2020.02.120

Xing, X., Lin, J., Brandon, N. , Banerjee, A., & Song, Y. (2020). Time-Varying Model Predictive Control of a Reversible-SOC Energy-Storage Plant Based on the Linear Parameter-Varying Method. IEEE Transactions on Sustainable Energy, 11(3), 1589-1600. [8782575]. https://doi.org/10.1109/TSTE.2019.2932103

Wang, Y. , Banerjee, A., & Deutschmann, O. (2019). Dynamic behavior and control strategy study of CO₂/H₂O co-electrolysis in solid oxide electrolysis cells. Journal of power sources, 412, 255-264. https://doi.org/10.1016/j.jpowsour.2018.11.047

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Bachelor

Chemical Science Engineering

Master

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