Results 111 to 120 of about 7,387,106 (257)

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source

A Review of Lithium‐Ion Battery Empirical and Semi‐Empirical Aging Models for Off‐Grid Renewable Energy Systems Application

Engineering Reports
Aging of lithium‐ion (Li‐ion) batteries in off‐grid renewable energy systems (RESs) can be monitored and controlled using battery management systems (BMSs) which utilize battery aging models. Empirical and semi‐empirical models (EMs) of battery aging are
Isaac Gwayi, Sarah Paul Ayeng'o, Cuthbert Z. M. Kimambo   +2 more
doaj   +1 more source

Battery-aware dynamic voltage scaling in multiprocessor embedded system

, 2005
— In a battery powered system, a primary design consideration is the battery lifetime. Profile of current drawn from a battery determines its lifetime. Recently in [4] dynamic voltage scaling has been applied to alter the battery load current profile in ...
Yuan Cai, Irith Pomeranz, Bashir M Al-hashimi, Cai, Yuan, Reddy, Sudhakar, Sudhakar M. Reddy, Pomeranz, Irith, Al-Hashimi, Bashir M.   +7 more
core  

Spatially Regulated Silicon Clusters in Trimodal Composite Anodes for High‐Energy Lithium‐Ion Batteries

Advanced Functional Materials, EarlyView.
A trimodal anode architecture spatially regulates silicon clusters within confined interstitial environments formed by graphite and contorted hexabenzocoronene. This confinement suppresses silicon aggregation and localized stress while enabling efficient Li‐ion transport, achieving high‐capacity, stable lithium‐ion batteries.
Jeongmi Joo, Minsung Kang, Seung Hak Oh, Jee Ho Ha, Hyunji Cha, Jimin Han, Ji‐Su Lim, Dae Hyeon Kwon, Won‐Jin Kwak, Sang Kyu Kwak, Seokhoon Ahn, Seok Ju Kang   +11 more
wiley   +1 more source

Optimizing EV Battery Management: Advanced Hybrid Reinforcement Learning Models for Efficient Charging and Discharging

Energies
This paper investigates the application of hybrid reinforcement learning (RL) models to optimize lithium-ion batteries’ charging and discharging processes in electric vehicles (EVs).
Sercan Yalçın, Münür Sacit Herdem
doaj   +1 more source

Optimizing NiMo Electrocatalyst Coatings for Hydrogen Evolution in Alkaline Electrolysis With The Machine Learning‐Guided Autonomous Platform CatBot

Advanced Functional Materials, EarlyView.
This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio, Jonas Elsborg, Elif Coşkun, Andreas Burger, Pradipkumar Manubhai Leuaa, Thu Pham Anh Phan, Jin Hyun Chang, Christodoulos Chatzichristodoulou   +7 more
wiley   +1 more source

Effects of LLZO Microstructure Porosity, LLZO/Li‐Metal Interfacial Polarization Resistance, and Applied Areal Current Density on Li‐Metal Dendrite Formation in LLZO Bilayer Symmetric Cells

Advanced Functional Materials, EarlyView.
The effects of solid‐state electrolyte architecture and electrolyte/electrode interfacial polarization resistance on Critical Current Density and the risks for “interfacial” and “internal” Li‐metal dendrite formation were investigated in simulations of FIB‐reconstructed porous‐dense Li7La3Zr2O12 (LLZO) “bilayers”, providing insight for full cells ...
Tanner R. Hamann, Jon O'Neill, Eric D. Wachsman   +2 more
wiley   +1 more source

Enhanced identification of battery models for real-time battery management

, 2011
Renewable energy generation, vehicle electrification, and smart grids rely critically on energy storage devices for enhancement of operations, reliability, and efficiency.
Caisheng Wang, Sitterly, Mark W., G. George Yin, Mark Sitterly, Le Yi Wang, Wang, Caisheng, Wang, Le Yi (R17515), Yin, George   +7 more
core   +1 more source

Al3+/Ta5+ Co‐Doping Promotes Homogeneous Li+ Transport Enabling High Performance Ni‐Rich Layered Oxide Cathodes

Advanced Functional Materials, EarlyView.
Al3+/Ta5+ co‐doping refines the primary particles of LiNiO2, reduces Li/Ni antisite disorder, and expands the c‐axis lattice parameter, thereby enabling faster and more homogeneous Li+ transport. Such rapid and homogeneous Li+ transport suppresses high‐voltage phase transitions and microcrack formation, ultimately improving the rate capability and long‐
Yanhao Ren, Zezhou Lin, Zhaowen Bai, Wei Wang, Yangqian Zhang, Jihao Zhang, Qingyu Kong, Yisen Xu, Jiaqi Wu, Fengting Ye, Haitao Huang, Yang Ren   +11 more
wiley   +1 more source

PHM overview on battery models approaches [PDF]

, 2017
The Battery Management Systems (BMS) brought a new impetus to the battery energy management which lead to an increase in battery life. But the BMS fails when the State of Charge (SoC), State of Health (SoH), State of Life (SoL) or Remaining Useful Life
Nunes, Eusébio P., Esteves, Manuel A. M.   +1 more
core   +2 more sources