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Michael Hermann Eikerling (1969-)

Name	Michael Hermann Eikerling
Time	1969- (Date of birth and death)
Place	Deutschland
Variant	Michael H. Eikerling Michael Eikerling
Related	Forschungszentrum Jülich
Further information	Diss. Fakultät für Physik, Technische Universität München
Record type	Person
GND-Identifier	121477045
Record ID	121477045
Involved in show all Advancing vanadium redox flow battery analysis: a deep learning approach for high-throughput 3D visualization and bubble quantification Structure and conductivity of ionomer in PEM fuel cell catalyst layers: a model-based analysis Stay Hydrated! Impact of Solvation Phenomena on the CO 2 Reduction Reaction at Pb (100) and Ag (100) surfaces A Data-Driven Framework for the Accelerated Discovery of CO2 Reduction Electrocatalysts Convolutional neural networks for high throughput screening of catalyst layer inks for polymer electrolyte fuel cells Electrochemical CO2 Reduction at Silver from a Local Perspective Virtual Materials Intelligence for Design and Discovery of Advanced Electrocatalysts Chemisorbed Oxygen at Pt(111): a DFT Study of Structural and Electronic Surface Properties Molecular Modeling of Hydronium Ion and Water Distribution in Water-Filled Pt Nanochannels with Corrugated Walls Microstructure of Catalyst Layers in PEM Fuel Cells Redefined: A Computational Approach Theoretische Modellierung der elektrophysikalischen Eigenschaften, der Struktur und Funktion von Niedertemperatur-Ionenaustauschmembranen Theoretische Modellierung der elektrophysikalischen Eigenschaften, der Struktur und Funktion von Niedertemperatur-Ionenaustauschmembranen

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Michael Hermann Eikerling (1969-)

Advancing vanadium redox flow battery analysis: a deep learning approach for high-throughput 3D visualization and bubble quantification

Structure and conductivity of ionomer in PEM fuel cell catalyst layers: a model-based analysis

Stay Hydrated! Impact of Solvation Phenomena on the CO 2 Reduction Reaction at Pb (100) and Ag (100) surfaces

A Data-Driven Framework for the Accelerated Discovery of CO2 Reduction Electrocatalysts

Convolutional neural networks for high throughput screening of catalyst layer inks for polymer electrolyte fuel cells

Electrochemical CO2 Reduction at Silver from a Local Perspective

Virtual Materials Intelligence for Design and Discovery of Advanced Electrocatalysts

Chemisorbed Oxygen at Pt(111): a DFT Study of Structural and Electronic Surface Properties

Molecular Modeling of Hydronium Ion and Water Distribution in Water-Filled Pt Nanochannels with Corrugated Walls

Microstructure of Catalyst Layers in PEM Fuel Cells Redefined: A Computational Approach

Theoretische Modellierung der elektrophysikalischen Eigenschaften, der Struktur und Funktion von Niedertemperatur-Ionenaustauschmembranen

Theoretische Modellierung der elektrophysikalischen Eigenschaften, der Struktur und Funktion von Niedertemperatur-Ionenaustauschmembranen