Results 141 to 150 of about 342,941 (283)

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Artificial Intelligence Predictions in Huge Chemical Spaces: Chiroptical Properties of [6]‐helicene Family

Advanced Science, EarlyView.
This study shows that a local, data‐driven AI model can accurately predict diverse optical and chiroptical properties of [6]helicenes using information from close structural neighbours. Combined with genetic algorithms, it enables inverse design for tailored properties, establishing practical structure–property rules for efficient molecular discovery ...
Rafael G. Uceda, Sandra Míguez‐Lago, Carlos M. Cruz, Boris Pérez‐Cañedo, Alfonso Gijón, Luis Álvarez de Cienfuegos, Antonio J. Mota, Delia Miguel, Juan M. Cuerva   +8 more
wiley   +1 more source

Flexible IMU Sensor Array For 3D Colonoscope Shape Reconstruction and AI‐Based Loop Detection

Advanced Science, EarlyView.
We propose a sensing platform for 3D visualization of the colonoscope combined with artificial intelligence (AI)‐based loop detection. The system consists of an array of 15 inertial measurement units (IMUs) mounted on a flexible printed circuit board that can be retrofitted into the instrument channel of conventional colonoscopes.
Tuukka Panula, Anni Halkilahti, Andrei Ivanov, Matti Kaisti   +3 more
wiley   +1 more source

Shadow‐Calibrated Stereo Vision for Colorimetric Sweat Analysis

Advanced Science, EarlyView.
By establishing a mathematical model that reconstructs 3D structures through geometric features of object shadows under controlled illumination, and combining it with Convolutional Neural Network‐based 2D image analysis for volumetric calibration, this work enables highly accurate 3D morphological reconstruction.
Ting Xiao, Yuwen Yan, Miaorong Lin, Jiahui Chen, Jianxin Meng, Xiang Cui, Peng Zhang, Fengyu Li   +7 more
wiley   +1 more source

Faster and Durable: A Cell‐to‐System Validation of a Low‐Degradation Fast‐Charge Protocol for Li‐Ion Batteries

Advanced Science, EarlyView.
A physics‐based framework resolving graphite phase‐separation dynamics establishes a predictive, degradation‐aware fast‐charging methodology for commercial Li‐ion batteries. The resulting model‐informed protocol achieves 20%–80% state‐of‐charge in 14 min while matching the long‐term degradation of a commercial 25‐minute EV strategy.
Marco Lagnoni, Francesco Giuseppe Quilici, Davide Cademartori, Claudio Scarpelli, Uways Nurulain Mithoowani, Federica Barontini, Alessandro Ruvio, Monica Puccini, Giovanni Lutzemberger, Maria Paola Carpanese, Antonio Bertei   +10 more
wiley   +1 more source

Decoupling Intrinsic Molecular Efficacy From Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery

Advanced Science, EarlyView.
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang, Ziyuan Li, Shan Gao, Zhen Zhu, Jing Wang, Xiangmei Duan   +5 more
wiley   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Enhancing Electrical Impedance Based Deformation Sensing with Dielectric Current Guide

Advanced Electronic Materials, EarlyView.
This work introduces a dielectric‐based field manipulation strategy for electrical impedance tomography in soft robotics. By using silicone as a passive electric field guide, improved deformation sensing accuracy and reduced interference are achieved without embedding conductive components.
Arsen Abdulali, David Hardman, Yue Xie, Fumiya Iida   +3 more
wiley   +1 more source

A DC Compact Model of an Organic Electrochemical Transistor Based on a Semiconductor Physics and Thermodynamic Approach

Advanced Electronic Materials, EarlyView.
This work presents a physics‐based DC compact model of an Organic Electrochemical Transistor (OECT) that takes into account the faradaic redox reaction in the above threshold regime and incorporates the diffusive current of the subthreshold regime based on semiconductor physics.
Ermias Telahun Teka, Yeohoon Yoon, Laura Teuerle, Tommy Meier, Hans Kleemann, Ghader Darbandy, Benjamin Iniguez   +6 more
wiley   +1 more source

Evaluation du potentiel d’énergie éolienne au Liban

Revue des Énergies Renouvelables, 2014
Dans cette étude, les caractéristiques du vent sont analysées en utilisant les données de la vitesse du vent recueillies pour cinq stations météorologiques au Liban et disponibles pour au moins une année (2 ans pour Klaiaat, 10 ans pour les Cèdres, 7 ans
G. Al Zohbi, P. Hendrick, P. Bouillard   +2 more
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