Advancing flexible thermoelectrics for integrated electronics

XL Shi, L Wang, W Lyu, T Cao, W Chen, B Hu… - Chemical Society …, 2024 - pubs.rsc.org
With the increasing demand for energy and the climate challenges caused by the
consumption of traditional fuels, there is an urgent need to accelerate the adoption of green …

All-temperature area battery application mechanism, performance, and strategies

S Chen, X Wei, G Zhang, X Wang, J Zhu, X Feng, H Dai… - The Innovation, 2023 - cell.com
Further applications of electric vehicles (EVs) and energy storage stations are limited
because of the thermal sensitivity, volatility, and poor durability of lithium-ion batteries (LIBs) …

Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data

J Yao, T Han - Energy, 2023 - Elsevier
Accurate estimation of lithium-ion battery capacity is crucial for ensuring its safety and
reliability. While data-driven modelling is a common approach for capacity estimation …

A comprehensive insight into the thermal runaway issues in the view of lithium-ion battery intrinsic safety performance and venting gas explosion hazards

G Wei, R Huang, G Zhang, B Jiang, J Zhu, Y Guo… - Applied Energy, 2023 - Elsevier
A comprehensive understanding of thermal runaway (TR) features and battery venting gas
(BVG) explosion characteristics is the critical issue of thermal hazard prevention. In this …

Flexible battery state of health and state of charge estimation using partial charging data and deep learning

J Tian, R **ong, W Shen, J Lu, F Sun - Energy Storage Materials, 2022 - Elsevier
Accurately monitoring battery states over battery life plays a central role in building
intelligent battery management systems. This study proposes a flexible method using only …

Semi-supervised estimation of capacity degradation for lithium ion batteries with electrochemical impedance spectroscopy

R **ong, J Tian, W Shen, J Lu, F Sun - Journal of Energy Chemistry, 2023 - Elsevier
Abstract Machine learning-based methods have emerged as a promising solution to
accurate battery capacity estimation for battery management systems. However, they are …

Light‐Assisted Energy Storage Devices: Principles, Performance, and Perspectives

X Dong, X Chen, X Jiang, N Yang - Advanced Energy Materials, 2023 - Wiley Online Library
Various energy storage devices are highly demanded by o ur modern society. The use of
solar energy, an important green energy source, is extremely attractive for future energy …

[HTML][HTML] Battery safety: Machine learning-based prognostics

J Zhao, X Feng, Q Pang, M Fowler, Y Lian… - Progress in Energy and …, 2024 - Elsevier
Lithium-ion batteries play a pivotal role in a wide range of applications, from electronic
devices to large-scale electrified transportation systems and grid-scale energy storage …

Advances in COFs for energy storage devices: harnessing the potential of covalent organic framework materials

M Chafiq, A Chaouiki, YG Ko - Energy Storage Materials, 2023 - Elsevier
Covalent organic frameworks (COFs) have attracted significant attention in the materials
science community on account of their unique properties and versatile applications. These …

An adaptive capacity estimation approach for lithium-ion battery using 10-min relaxation voltage within high state of charge range

B Jiang, Y Zhu, J Zhu, X Wei, H Dai - Energy, 2023 - Elsevier
Capacity estimation is essential for battery health management during the whole lifecycle.
The data-driven technique has shown advanced performance in battery capacity estimation …