Data‐Driven Battery Characterization and Prognosis: Recent Progress, Challenges, and Prospects
Battery characterization and prognosis are essential for analyzing underlying
electrochemical mechanisms and ensuring safe operation, especially with the assistance of …
electrochemical mechanisms and ensuring safe operation, especially with the assistance of …
Direct observation of chemomechanical stress-induced phase transformation in high-Ni layered cathodes for lithium-ion batteries
Understanding chemomechanical degradations of layered oxide cathodes is critical to
developing next-generation cathodes for lithium-ion batteries. So far, although the …
developing next-generation cathodes for lithium-ion batteries. So far, although the …
Leveraging advanced X-ray imaging for sustainable battery design
With the growing demand for sustainable battery technologies, state-of-the-art
characterization techniques become more and more critical for optimizing battery materials …
characterization techniques become more and more critical for optimizing battery materials …
Effective transport network driven by tortuosity gradient enables high-electrochem-active solid-state batteries
QS Liu, HW An, XF Wang, FP Kong… - National Science …, 2023 - academic.oup.com
Simultaneously achieving high electrochemical activity and high loading for solid-state
batteries has been hindered by slow ion transport within solid electrodes, in particular with …
batteries has been hindered by slow ion transport within solid electrodes, in particular with …
A general-purpose tool for modeling multifunctional thin porous media (POREnet): From pore network to effective property tensors
PA García-Salaberri, IV Zenyuk - Heliyon, 2024 - cell.com
POREnet, a novel approach to model effective properties of thin porous media, TPM, is
presented. The methodology allows the extraction of local effective property tensors by …
presented. The methodology allows the extraction of local effective property tensors by …
Fracture mechanisms of NCM polycrystalline particles in lithium-ion batteries: A review
K Mao, Y Yao, Y Chen, W Li, X Shen, J Song… - Journal of Energy …, 2024 - Elsevier
The development of high-energy LiNi x Co y Mn z O 2 (NCM) cathode materials for lithium-
ion batteries (LIBs) is central to many emerging technologies in the fields of power and …
ion batteries (LIBs) is central to many emerging technologies in the fields of power and …
Towards full-stack deep learning-empowered data processing pipeline for synchrotron tomography experiments
Z Zhang, C Li, W Wang, Z Dong, G Liu, Y Dong… - The Innovation, 2023 - Elsevier
Synchrotron tomography experiments are transitioning into multi-functional, cross-scale and
dynamic characterizations, enabled by new generation synchrotron light sources and fast …
dynamic characterizations, enabled by new generation synchrotron light sources and fast …
Statistical analysis of metastable pitting behavior of 2024 aluminum alloy based on deep learning
Z Xu, B Cai, L Yan, X Pang, K Gao - Corrosion Science, 2024 - Elsevier
In this study, a processing flow model for recognizing, statistically analyzing, and assessing
pitting images in 2024 aluminum alloy was established based on deep learning object …
pitting images in 2024 aluminum alloy was established based on deep learning object …
Bridging multimodal data and battery science with machine learning
Y Ning, F Yang, Y Zhang, Z Qiang, G Yin, J Wang… - Matter, 2024 - cell.com
Multimodal data hold paramount significance in the realm of battery science research.
Traditional manual tools for data analysis have proven inadequate in meeting the demands …
Traditional manual tools for data analysis have proven inadequate in meeting the demands …