Results 111 to 120 of about 98,314 (264)

Electrolyte Additive Strategies in Aqueous Zn‐Ion Batteries: Recent Advances and Prospects

Advanced Science, EarlyView.
This article provides a comprehensive overview of the current status and future development directions of AZIBs electrolyte additives in three aspects: stabilizing zinc anodes (uniform deposition, inhibition of dendritic crystals), protecting cathodes (structural stability, inhibition of dissolution), and enhancing electrolyte stability (wider ...
Yuanze Yu, Hongmin Liu, Long Fan, Huakun Liu, Shixue Dou, Guoxiu Wang, Nana Wang, Zhongchao Bai   +7 more
wiley   +1 more source

An explainable Grey Wolf optimized extreme learning machine framework for modulation classification in cloud environment. [PDF]

Sci Rep
Sahu PC, Prasad B, Dash R, Muduli D, DasMahapatra S, Mishra S, Parija S.   +6 more
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Retraction: LGD_Net: Capsule network with extreme learning machine for classification of lung diseases using CT scans. [PDF]

PLoS One
PLOS One Editors.
europepmc   +1 more source

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

Predicting unconfined compressive strength of geopolymer-stabilized clays using a sector fruit fly-based extreme learning machine. [PDF]

Sci Rep
Abdellatief M, Mortagi M.
europepmc   +1 more source

Ethical Precision in Nanoscale Brain Interfacing

Advanced Science, EarlyView.
As brain interfaces approach the nanoscale, precision no longer only measures—it knows, predicts, and potentially reshapes the mind. This work argues that traditional ethics fails under such conditions and proposes a shift toward continuous, operation‐based governance using the recovery–discovery framework to track, constrain, and responsibly steer ...
Guilherme Wood
wiley   +1 more source

A hybrid spiking convolutional neural framework with extreme learning machine for enhanced anomaly detection in network security. [PDF]

Sci Rep
Li W.
europepmc   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Explainable AI-driven diagnosis model for early glaucoma detection using grey-wolf optimized extreme learning machine approach. [PDF]

PLoS Comput Biol
Muduli D, Sharma SK, Dash S, Lemos B, Mallik S.   +4 more
europepmc   +1 more source