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20212023
most citedClassification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers

3 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

physics.chem-ph2023

Unveiling the impact of crosslinking redox-active polymers on their electrochemical behavior by 3D imaging and statistical microstructure analysis

Marten Ademmer, Po-Hua Su, Lukas Dodell +8

Polymer-based batteries offer potentially higher power densities and a smaller ecological footprint compared to state-of-the-art lithium-ion batteries comprising inorganic active m…

cond-mat.mtrl-sci2022★ 2 cited

Quantitative comparison of different approaches for reconstructing the carbon-binder domain from tomographic image data of cathodes in lithium-ion batteries and its influence on electrochemical properties

Benedikt Prifling, Matthias Neumann, Simon Hein +10

It is well known that the spatial distribution of the carbon-binder domain (CBD) offers a large potential to further optimize lithium-ion batteries. However, it is challenging to r…

cond-mat.mtrl-sci2022★ 3 cited

Classification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers

Markus Osenberg, André Hilger, Matthias Neumann +6

FIB/SEM tomography represents an indispensable tool for the characterization of three-dimensional nanostructures in battery research and many other fields. However, contrast and 3D…

cond-mat.dis-nn2021

Asymptotic properties of one-layer artificial neural networks with sparse connectivity

Christian Hirsch, Matthias Neumann, Volker Schmidt

A law of large numbers for the empirical distribution of parameters of a one-layer artificial neural networks with sparse connectivity is derived for a simultaneously increasing nu…