Lithium-ion batteries (LIBs) are leading the energy storage market. Significant efforts are
being made to widely adopt LIBs due to their inherent performance benefits and reduced …

Abstract Physics-Based Models (PBMs) offer a promising approach to develop advanced
battery management systems that rely on information about the internal states of battery …

Aluminum batteries with imidazolium-based electrolytes present a promising avenue toward
the post-lithium-ion battery era. A critical bottleneck is the development of reversible …

Non‐trivial relationships link individual materials properties to device‐level performance.
Device optimization therefore calls for new automation approaches beyond the laboratory …

High-throughput computing (HTC) is a pivotal asset in many scientific fields, such as biology,
material science and machine learning. Applying HTC to the complex physics-based …

Physicochemical lithium-ion battery models are promising for advanced battery
management systems because they can estimate internal electrochemical states to ensure …

Utilizing a human in the loop Bayesian optimisation paradigm based on Gaussian process
regression, we optimized an Ni electrodeposition method to synthesize nano-structured …

Actual market requirements for storage systems highlight the limits of graphite as an anode
for Li-ion batteries. Lithium metal can represent a suitable alternative to graphite due to its …

Due to their high power density and availability, aluminum batteries consisting of graphite
positive electrode and ionic liquid electrolytes are promising candidates for post‐lithium‐ion …

Predicting degradation of lithium-ion batteries holds significant value for the automotive and
energy storage industries, as it provides invaluable opportunities to enhance performance …