| 1 |
Statistical investigation of structural and transport properties of densely-packed assemblies of overlapping spheres using the resistor network method
Birkholz O, Neumann M, Schmidt V, Kamlah M
Powder Technology, 378, 659, 2021 |
| 2 |
Wall heat transfer coefficient and effective radial conductivity of ceramic foam catalyst supports
Turchetti L, Murmura MA, Monteleone G, Annesini MC
Chemical Engineering Research & Design, 156, 146, 2020 |
| 3 |
Complex dielectric permittivity of metal and polymer modified montmorillonite
Chu Y, Nie SK, Liu SY, Lee C, Bate B
Journal of Hazardous Materials, 374, 382, 2019 |
| 4 |
Modeling the effective conductivity of the solid and the pore phase in granular materials using resistor networks
Birkholz O, Gan YX, Kamlah M
Powder Technology, 351, 54, 2019 |
| 5 |
Stochastic 3D Modeling of Three-Phase Microstructures for Predicting Transport Properties: A Case Study
Neumann M, Abdallah B, Holzer L, Willot F, Schmidt V
Transport in Porous Media, 128(1), 179, 2019 |
| 6 |
The microstructure effect on ion conduction in composite electrolyte
Zheng KQ, Shen SL
International Journal of Energy Research, 42(13), 4229, 2018 |
| 7 |
Big Data for Microstructure-Property Relationships: A Case Study of Predicting Effective Conductivities
Stenzel O, Pecho O, Holzer L, Neumann M, Schmidt V
AIChE Journal, 63(9), 4224, 2017 |
| 8 |
Numerical and experimental evaluation of the relationship between porous electrode structure and effective conductivity of ions and electrons in lithium-ion batteries
Inoue G, Kawase M
Journal of Power Sources, 342, 476, 2017 |
| 9 |
Phase field modeling of microstructure evolution and concomitant effective conductivity change in solid oxide fuel cell electrodes
Lei YK, Cheng TL, Wen YH
Journal of Power Sources, 345, 275, 2017 |
| 10 |
Predicting Effective Conductivities Based on Geometric Microstructure Characteristics
Stenzel O, Pecho O, Holzer L, Neumann M, Schmidt V
AIChE Journal, 62(5), 1834, 2016 |
