Leveraging machine learning in porous media
The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML),
has had a significant impact on engineering and the fundamental sciences, resulting in …
has had a significant impact on engineering and the fundamental sciences, resulting in …
Perspectives on strategies and techniques for building robust thick electrodes for lithium-ion batteries
Z Wang, C Dai, K Chen, Y Wang, Q Liu, Y Liu… - Journal of Power …, 2022 - Elsevier
Thick electrode is a valid and practical strategy for achieving lithium-ion batteries with high
energy density. However, before widespread practical application, the electron-ion transfer …
energy density. However, before widespread practical application, the electron-ion transfer …
Ultrasonic guided wave measurement and modeling analysis of the state of charge for lithium-ion battery
G Jie, Z Liangheng, L Yan, S Fan, W Bin… - Journal of Energy …, 2023 - Elsevier
This work presents the analytical acoustic model to investigate the interaction mechanism
between the state of charge (SOC) of lithium-ion battery and the propagation characteristics …
between the state of charge (SOC) of lithium-ion battery and the propagation characteristics …
[HTML][HTML] Current trends on the use of deep learning methods for image analysis in energy applications
Deep learning methods for image analysis are attracting increasing interest for application in
a wide range of different research fields. Here we aim to systematically analyze and discuss …
a wide range of different research fields. Here we aim to systematically analyze and discuss …
Electrochemical modeling, Li plating onsets and performance analysis of thick graphite electrodes considering the solid electrolyte interface formed from the first cycle
D Liu, Y He, Y Chen, J Cao, F Zhu - Electrochimica Acta, 2023 - Elsevier
Based on a crack dominated solid electrolyte interface (SEI) resistance, an electrochemical
model considering the SEI formed from the first cycle is established to investigate the …
model considering the SEI formed from the first cycle is established to investigate the …
Mechanistically Understanding the Correlation Between Dynamic Interface Variation and Stability of Surface Coating on the NMC811 Materials
S Lyu, J Yu, XH Guo, X Bu, L Sun, N Li… - Advanced Energy …, 2024 - Wiley Online Library
Abstract LiNi0. 8Co0. 1‐Mn0. 1O2 (NMC811) is widely used in high energy density lithium‐
ion batteries, while dynamic variation of liquid‐solid interface induced by oxygen …
ion batteries, while dynamic variation of liquid‐solid interface induced by oxygen …
Exploring particle-current collector contact damage in Li-ion battery using DEM-FEM scheme
Calendering is an essential step in the manufacturing process of lithium-ion batteries.
However, the intrusion of active particles into metal foil can damage the current collector …
However, the intrusion of active particles into metal foil can damage the current collector …
Stochastic reconstruction and performance prediction of cathode microstructures based on deep learning
X Yang, C He, L Yang, WL Song, HS Chen - Journal of Power Sources, 2024 - Elsevier
The effective properties of lithium-ion battery (LIB) cathode are determined by both the
volume fractions of constituents and the morphological features of microstructure. However …
volume fractions of constituents and the morphological features of microstructure. However …
Exploration of the Influences of Electrode Materials and Solutions on the Performances of a Reverse Electrodialysis Cell with a Deduced Equation
W Cai, F Wang, GQ Yang, J Qian - The Journal of Physical …, 2024 - ACS Publications
Currently, people have to handle the crises of an energy source shortage and environment
pollution. Salinity gradient energy (SGE) is clean and renewable, and its amount in junctions …
pollution. Salinity gradient energy (SGE) is clean and renewable, and its amount in junctions …
Leveraging machine learning in porous media
B Ebrahimpour - Journal of Materials Chemistry A, 2024 - researchportal.port.ac.uk
The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML),
has had a significant impact on engineering and the fundamental sciences, resulting in …
has had a significant impact on engineering and the fundamental sciences, resulting in …