Results 131 to 140 of about 629,061 (300)

A Novel Fusion Method for State-of-Charge Estimation of Lithium-Ion Batteries Based on Improved Genetic Algorithm BP and Adaptive Extended Kalman Filter. [PDF]

Sensors (Basel), 2023
Cao L, Shao C, Zhang Z, Cao S.
europepmc   +1 more source

NanoMOF‐Based Multilevel Anti‐Counterfeiting by a Combination of Visible and Invisible Photoluminescence and Conductivity

Advanced Functional Materials, EarlyView.
This study presents novel anti‐counterfeiting tags with multilevel security features that utilize additional disguise features. They combine luminescent nanosized Ln‐MOFs with conductive polymers to multifunctional mixed‐matrix membranes and powder composites. The materials exhibit visible/NIR emission and matrix‐based conductivity even as black bodies.
Moritz Maxeiner, Ruben Maile, Murat Cuvalli, Andreas Wolf, Ayisha Komal, Robert Oestreich, Christoph Janiak, Karl Mandel, Alexander Knebel, Klaus Müller‐Buschbaum   +9 more
wiley   +1 more source

State of Charge Estimation of Battery Based on Neural Networks and Adaptive Strategies with Correntropy. [PDF]

Sensors (Basel), 2022
Navega Vieira R, Mauricio Villanueva JM, Sales Flores TK, Tavares de Macêdo EC.   +3 more
europepmc   +1 more source

Cell modelling for state-of-charge and state-of-health estimation

, 2023
La precisión en la modelización de las baterías es fundamental para gestionar eficazmente la energía, prolongar su vida útil y garantizar su seguridad operativa. En el campo de la tecnología de celdas de batería de iones de litio (Li-ion), la estimación precisa del estado de carga (SOC) y el estado de salud (SOH) es esencial para lograr un rendimiento ...
openaire   +1 more source

MnI‐Functionalized Covalent Organic Framework as Efficient Electrocatalyst for CO2 Reduction in a Catholyte‐Free Zero‐Gap Electrolyzer

Advanced Functional Materials, EarlyView.
This work demonstrates the successful integration of a phenanthroline‐based 2D COF with MnI catalytic sites into a catholyte‐free membrane‐electrode‐assembly cell for CO2 electroreduction. The crystalline COF actively suppresses Mn⁰–Mn⁰ dimerization, achieving a turnover frequency of 617 h⁻¹ at 2.8 V (full‐cell potential), and enabling stable operation.
Laura Spies, Marcos Eduardo G. Carmo, Gonçalves J. Marrenjo, Stephan Reuther, Patrick Ganswindt, Antonio Otavio T. Patrocinio, Thomas Bein, Osmando F. Lopes, Jenny Schneider   +8 more
wiley   +1 more source

A Dual-Input Neural Network for Online State-of-Charge Estimation of the Lithium-Ion Battery throughout Its Lifetime. [PDF]

Materials (Basel), 2022
Qian C, Xu B, Xia Q, Ren Y, Yang D, Wang Z.   +5 more
europepmc   +1 more source

Rational Fine‐Tuning of MOF Pore Metrics: Enhanced SO2 Capture and Sensing with Optimal Multi‐Site Interactions

Advanced Functional Materials, EarlyView.
A pore tuning strategy to amplify the multi‐site MOF‐SO2 interactions is proposed to achieve an enhanced trace SO2 capture and chemiresistive sensing in highly stable isostructural DMOFs by annelating benzene rings. This work provides a facile strategy to achieve tailor‐made stable MOF materials for specific multifunctional applications.
Shanghua Xing, Abdulrahman Mohabbat, István Boldog, Jens Möllmer, Marcus Lange, Yulyan Haiduk, Tobias Heinen, Vladimir Pankov, Oliver Weingart, Christoph Janiak   +9 more
wiley   +1 more source

Joint State of Charge and State of Health Estimation Using Bidirectional LSTM and Bayesian Hyperparameter Optimization

IEEE Access
In this study, a novel Machine learning-based method for the joint State of Charge and State of Health estimation of Lithium Batteries that tackle real-world applications and with Bayesian Hyperparameter optimization is proposed.
Panagiotis Eleftheriadis, Spyridon Giazitzis, Julia Kowal, Sonia Leva, Emanuele Ogliari   +4 more
doaj   +1 more source

State of Charge Estimation of Lithium-Ion Batteries Using Stacked Encoder-Decoder Bi-Directional LSTM for EV and HEV Applications. [PDF]

Micromachines (Basel), 2022
Terala PK, Ogundana AS, Foo SY, Amarasinghe MY, Zang H.   +4 more
europepmc   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source