Results 161 to 170 of about 1,559,457 (305)

Leaching & electrochemical purification of mixed industrial LFP- & NMC type lithium-ion battery waste. [PDF]

RSC Adv
van de Ven JJMM, Anghel MA, Teeuwisse PJ, Yang Y, Abrahami ST.   +4 more
europepmc   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

Silicon based lithium-ion battery anodes: A chronicle perspective review

, 2017
Si has been regarded as one of the most promising next generation lithium-ion battery (LIB) anodes due to its exceptional capacity and proper working voltage.
Zhu, Jin, Zuo, Xiuxia, Cheng, Ya-Jun, Mueller-Buschbaum, Peter   +3 more
core  

Inorganic Photoluminescent Microparticles as Identifiers for the Sorting of Lithium-Ion Battery Cathodes. [PDF]

ChemSusChem
Ziegler S, Strohhöfer C, Gao G, Flegler A, Giffin GA.   +4 more
europepmc   +1 more source

Enhancing All‐Solid‐State Batteries Performance Through Thickness Control and Surface Passivation of Thermally Evaporated Lithium Metal Anodes

Advanced Science, EarlyView.
This study demonstrates that thermally evaporated lithium anodes combined with LiF passivation provide a high‐performance thin anode design for next‐generation ASSBs. This approach increases the critical current density from 1.6 to 2.6 mA cm−2, enabling full cells to achieve over 500 and 300 cycles at 1.5 and 3 mA cm−2, respectively, outperforming even
Jinsong Zhang, Linfeng Xu, Robin N. Wullich, Thomas J. Schmidt, Mario El Kazzi   +4 more
wiley   +1 more source

Understanding Ionic Transport in LiFeO₂ Polymorphs: Pathways to Enhancing Lithium-Ion Battery Performance. [PDF]

Materials (Basel)
Da Fonseca JR, Caja-Muñoz B, Dávila ME, Martínez-Pastor JP, Sánchez-Royo JF, Asensio MC.   +5 more
europepmc   +1 more source

Physics‐Guided Descriptors Enable Data‐Efficient Prediction of Battery Coulombic Efficiency

Advanced Science, EarlyView.
This work integrates multiscale simulations with data‐driven approaches to predict Coulombic efficiency (CE). Multiscale simulations of battery systems are performed to extract Physics‐Guided descriptors and construct a dataset. Machine learning models trained on this dataset are then subjected to interpretable analysis to identify the most influential
Qintao Sun, Xuewei Gu, Yulin Jie, Hao Yang, Shuhong Jiao, Chao Tang, Yangping Sheng, Yuhao Lu, Ruiguo Cao, Tao Cheng   +9 more
wiley   +1 more source

Thermal annealing-mediated fine-tuning of SnO₂ nanoparticles for advanced lithium-ion battery anodes. [PDF]

RSC Adv
Nguyen PV, Tran TG, Nguyen TL, Dinh DA, Kieu Ngan TT, Kim IT, Kien PT, Nguyen NT, Nguyen DQ, Van Tran M, Pham LT, Thao Nguyen BT.   +11 more
europepmc   +1 more source

A Bifunctional Organosilane Additive for Dynamic pH Regulation and Interfacial Protection in Aqueous Zinc‐Ion Batteries

Advanced Science, EarlyView.
A novel multifunctional additive for aqueous zinc‐ion battery electrolytes can simultaneously dynamically adjust the pH in microzones, regulate the solvation structure of Zn2+, protect the interface, and form a stable solid‐state SEI film. This approach enables a dendrite‐free zinc anode and demonstrates excellent cycling stability and cycle life ...
Lina Pan, Haiyang Wu, Peng Huang, Boyu Yuan, Chao Lai, Yaqian Lan   +5 more
wiley   +1 more source

An Analytical Model for Predicting the Remaining Battery

, 2008
Predicting the residual energy of the battery source that powers a portable electronic device is quite important in designing and employing an effective dynamic power management policy in the device. This paper presents a closed-form analytical model for
Capacity Of Lithium-Ion
core