This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to
battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily …

CRISP-DM is the de-facto standard and an industry-independent process model for applying
data mining projects. Twenty years after its release in 2000, we would like to provide a …

Technologies that accelerate the delivery of reliable battery-based energy storage will not
only contribute to decarbonization such as transportation electrification, smart grid, but also …

Lithium‐ion battery manufacturing chain is extremely complex with many controllable
parameters especially for the drying process. These processes affect the porous structure …

Lithium-ion battery manufacturing is a highly complicated process with strongly coupled
feature interdependencies; a feasible solution that can analyze feature variables within …

Due to the rapid growth in the demand for high-energy density lithium battery in energy
storage systems and inadequate global lithium reserves, the configuration of limited lithium …

With the rise of battery electric vehicles to mass production, many technical improvements
have been realized to drastically increase the electric range, efficiency, and sustainability …

Electro-mobility is considered a key strategy to reduce GHG emissions in the transport sector
and to make individual mobility more sustainable. However, the production of electric …

The supply of defect-free, high-quality products is an important success factor for the long-
term competitiveness of manufacturing companies. Despite the increasing challenges of …

Battery manufacturing plays a direct and pivotal role in determining battery performance,
which, in turn, significantly affects the applications of battery-related energy storage systems …