Results 211 to 220 of about 16,021,923 (280)

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Leveraging Immersive Virtual Reality to Prevent Child Injuries in the Home: Proof-of-Concept Study. [PDF]

JMIR Pediatr Parent
Osborne MC, Zhang L, Garefino A, Freeman R.   +3 more
europepmc   +1 more source

A Large Scale Multi‐Modal Workflow for Battery Characterization: From Concept to Implementation

Advanced Energy Materials, EarlyView.
Isolated characterization techniques produce independent datasets and single‐property insights. However, progressively more holistic interpretations of battery‐material behavior is needed in the future. Here we demonstrate a coordinated multimodal workflow enabling the correlation of heterogeneous datasets and the construction of multidimensional ...
François Cadiou, Cinthya Herrera, Duncan Atkins, Elixabete Ayerbe, Giorgio Baraldi, Stéphanie Belin, Anass Benayad, Didier Blanchard, Federico Capone, Ennio Capria, Isidora Cekic‐Laskovic, Robert Dominko, Kristina Edström, Ajay Gautam, Lukas Helfen, Antonella Iadecola, Quentin Jacquet, Gregor Kapun, Xinyu Li, Aleksandar Matic, Nataliia Mozhzhukhina, Andrew J. Naylor, Poul Norby, Chris O'Keefe, Alexandre Ponrouch, Jean‐Pascal Rueff, Elena Tchernykova, Deyana Tchitchekova, Israel Temprano, Nikita Vostrov, Marnix Wagemaker, Martin Winter, Christian Wölke, Tejs Vegge, Sandrine Lyonnard   +34 more
wiley   +1 more source

XR-based bullying prevention interventions among K-12 students: a scoping review of design, theory, and outcomes. [PDF]

Front Psychiatry
Li X, Luo H, Wang Z, Li L.
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Evaluating the Teaching Effectiveness of Interactive Virtual Platform Based on Artificial Intelligence for Obstetrics and Gynecology Residency Training. [PDF]

Adv Med Educ Pract
Hu W, Ding Z, Zhao X, Ye J.
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Exploring nursing students' communication experiences with artificial intelligence-supported virtual patients: a qualitative study. [PDF]

BMC Nurs
Korkmaz Doğdu A, Dağistan Akgöz A.
europepmc   +1 more source

Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring

Advanced Intelligent Discovery, EarlyView.
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira, Marcos de C. Leite, Pedro H. M. Zanineli, Juliana N. Y. Costa, Débora M. Cunha, Sophia P. Serra, Pedro H. Sophia, Flávio M. Shimizu, Yasmin W. Moura, Célio C. Oliveira, Gabriel R. Schleder, Gabriela F. Persinoti, Leandro Merces, Renato S. Lima   +13 more
wiley   +1 more source