| How theory and simulation can drive fuel cell electrocatalysis MJ Eslamibidgoli, J Huang, T Kadyk, A Malek, M Eikerling Nano Energy 29, 334-361, 2016 | 90 | 2016 |
| Effect of IrO6 Octahedron Distortion on the OER Activity at (100) IrO2 Thin Film G Buvat, MJ Eslamibidgoli, AH Youssef, S Garbarino, A Ruediger, ... ACS Catalysis 10 (1), 806-817, 2019 | 58 | 2019 |
| Cation overcrowding effect on the oxygen evolution reaction J Huang, M Li, MJ Eslamibidgoli, M Eikerling, A Groß Jacs Au 1 (10), 1752-1765, 2021 | 53 | 2021 |
| Atomistic mechanism of Pt extraction at oxidized surfaces: insights from DFT MJ Eslamibidgoli, MH Eikerling Electrocatalysis 7, 345-354, 2016 | 47 | 2016 |
| Electrochemical Formation of Reactive Oxygen Species at Pt (111) A Density Functional Theory Study MJ Eslamibidgoli, MH Eikerling Acs Catalysis 5 (10), 6090-6098, 2015 | 39 | 2015 |
| Surface configuration and wettability of nickel (oxy) hydroxides: a first-principles investigation MJ Eslamibidgoli, A Groß, M Eikerling Physical Chemistry Chemical Physics 19 (34), 22659-22669, 2017 | 35 | 2017 |
| Approaching the self-consistency challenge of electrocatalysis with theory and computation MJ Eslamibidgoli, MH Eikerling Current Opinion in Electrochemistry 9, 189-197, 2018 | 31 | 2018 |
| The Effect of Side-Chain Length on the Solid-State Structure and Optoelectronic Properties of Fluorene-alt-Benzothiadiazole Based Conjugated PolymersA DFT … MJ Eslamibidgoli, JB Lagowski The Journal of Physical Chemistry A 116 (43), 10597-10606, 2012 | 28 | 2012 |
| Deciphering the exceptional performance of NiFe hydroxide for the oxygen evolution reaction in an anion exchange membrane electrolyzer L Wang, VA Saveleva, MJ Eslamibidgoli, D Antipin, C Bouillet, I Biswas, ... ACS Applied Energy Materials 5 (2), 2221-2230, 2022 | 21 | 2022 |
| Deep learning for the automation of particle analysis in catalyst layers for polymer electrolyte fuel cells A Colliard-Granero, M Batool, J Jankovic, J Jitsev, MH Eikerling, K Malek, ... Nanoscale 14 (1), 10-18, 2022 | 21 | 2022 |
| OER Performances of Cationic Substituted (100)-Oriented IrO2 Thin Films: A Joint Experimental and Theoretical Study G Buvat, MJ Eslamibidgoli, S Garbarino, M Eikerling, D Guay ACS applied energy materials 3 (6), 5229-5237, 2020 | 19 | 2020 |
| Phosphorene degradation: visualization and quantification of nanoscale phase evolution by scanning transmission X-ray microscopy W Li, Z Wang, F Zhao, M Li, X Gao, Y Zhao, J Wang, J Zhou, Y Hu, Q Xiao, ... Chemistry of Materials 32 (3), 1272-1280, 2020 | 19 | 2020 |
| Mechanical and chemical stability of monolayer black phosphorous studied by density functional theory simulations MJ Eslamibidgoli, MH Eikerling The Journal of Physical Chemistry C 122 (39), 22366-22373, 2018 | 17 | 2018 |
| Low-spin state of Fe in Fe-doped NiOOH electrocatalysts ZD He, R Tesch, MJ Eslamibidgoli, MH Eikerling, PM Kowalski Nature Communications 14 (1), 3498, 2023 | 16 | 2023 |
| Local impact of Pt nanodeposits on ionomer decomposition in polymer electrolyte membranes S Helmly, MJ Eslamibidgoli, KA Friedrich, MH Eikerling Electrocatalysis 8, 501-508, 2017 | 15 | 2017 |
| Virtual materials intelligence for design and discovery of advanced electrocatalysts A Malek, MJ Eslamibidgoli, M Mokhtari, Q Wang, MH Eikerling, K Malek ChemPhysChem 20 (22), 2946-2955, 2019 | 13 | 2019 |
| Modeling the local potential at Pt nanoparticles in polymer electrolyte membranes MJ Eslamibidgoli, PÉA Melchy, MH Eikerling Physical Chemistry Chemical Physics 17 (15), 9802-9811, 2015 | 12 | 2015 |
| Convolutional neural networks for high throughput screening of catalyst layer inks for polymer electrolyte fuel cells MJ Eslamibidgoli, FP Tipp, J Jitsev, J Jankovic, MH Eikerling, K Malek RSC advances 11 (51), 32126-32134, 2021 | 11 | 2021 |
| Understanding the Improved Activity of Dendritic Sn1Pb3 Alloy for the CO2 Electrochemical Reduction: A Computational–Experimental Investigation M Fan, MJ Eslamibidgoli, X Zhu, S Garbarino, AC Tavares, M Eikerling, ... ACS catalysis 10 (18), 10726-10734, 2020 | 11 | 2020 |
| Recurrent neural network-based model for accelerated trajectory analysis in aimd simulations MJ Eslamibidgoli, M Mokhtari, MH Eikerling arXiv preprint arXiv:1909.10124, 2019 | 11 | 2019 |
Michael EikerlingRWTH Aachen University and Forschungszentrum Juelich在 fz-juelich.de 的电子邮件经过验证
