[HTML][HTML] Machine learning for advanced energy materials

Y Liu, OC Esan, Z Pan, L An - Energy and AI, 2021 - Elsevier
The screening of advanced materials coupled with the modeling of their quantitative
structural-activity relationships has recently become one of the hot and trending topics in …

Advances in modification methods and the future prospects of high-voltage spinel LiNi 0.5 Mn 1.5 O 4—a review

T Fu, D Lu, Z Yao, Y Li, C Luo, T Yang, S Liu… - Journal of Materials …, 2023 - pubs.rsc.org
In order to reduce the production cost of lithium-ion batteries and the damage to the
environment, cobalt-free cathode materials have become the focus of the lithium-ion battery …

Advances in materials and machine learning techniques for energy storage devices: A comprehensive review

P Thakkar, S Khatri, D Dobariya, D Patel, B Dey… - Journal of Energy …, 2024 - Elsevier
The increasing global need for energy supply in modern society has created a pressing
need to explore new materials for renewable energy technologies. However, conventional …

Machine learning of materials design and state prediction for lithium ion batteries

J Mao, J Miao, Y Lu, Z Tong - Chinese Journal of Chemical Engineering, 2021 - Elsevier
With the widespread use of lithium ion batteries in portable electronics and electric vehicles,
further improvements in the performance of lithium ion battery materials and accurate …

Machine learning in metal-ion battery research: advancing material prediction, characterization, and status evaluation

T Yu, C Wang, H Yang, F Li - Journal of Energy Chemistry, 2023 - Elsevier
Abstract Metal-ion batteries (MIBs), including alkali metal-ion (Li+, Na+, and K+), multi-valent
metal-ion (Zn 2+, Mg 2+, and Al 3+), metal-air, and metal-sulfur batteries, play an …

High-voltage performance of LiNi 0.5 Mn 1.5 O 4-based lithium-ion batteries with 4-methyl-1, 3, 2-dioxathiolane-2, 2-dioxide (MDTD) as an electrolyte additive

J Mu, X Li, R He, L Sun, X Bai, L Zhang… - Journal of Materials …, 2024 - pubs.rsc.org
Spinel-type LiNi0. 5Mn1. 5O4 (LNMO) materials have attracted broad attention as
components of rechargeable lithium-ion batteries (LIBs) due to their high energy density …

Machine learning technique-based data-driven model of exploring effects of electrolyte additives on LiNi0. 6Mn0. 2Co0. 2O2/graphite cell

TN Tran, A Garg, TG Phung, MLP Le… - Journal of Energy …, 2021 - Elsevier
Abstract Recently, state-of-the-art and perspective Li-ion batteries have been focused on
NMC622 cathode for energy densities and power densities enhancement. This work …

Effect of the succinonitrile additive, electrode processing, and N/P ratios in the performance of high‐voltage lithium‐ion batteries using LiNi0.5Mn1.5O4 cathode

HTM Nguyen, QN Nguyen, TTT Truong… - Vietnam Journal of …, 2024 - Wiley Online Library
The progressive improvement in the gravimetric energy density of lithium‐ion batteries
(LIBs) leads to electrolyte design, positive electrode, and full‐cell optimization processes …

[图书][B] Collagen-derived Materials: Synthesis and Applications in Electrochemical Energy Storage and Conversion

F Wang, Y Huang, J Niu - 2022 - books.google.com
b” Collagen-Derived MaterialsComprehensive Resource for Current Ideas and Strategies for
the Synthesis and Characterization of Advanced Collagen-Derived Materials This book …

Data-driven Design of Electrolyte Additives for High-Performance 5 V LiNi0. 5Mn1. 5O4 Cathodes

C Liao, B Wang, H Doan, SB Son, D Abraham, S Trask… - 2024 - researchsquare.com
Abstract LiNi 0.5 Mn 1.5 O 4 (LNMO) is a high-capacity spinel-structured material with an
average lithiation/de-lithiation potential at ca. 4.6–4.7 V, far exceeding the stability limits of …