Results 81 to 90 of about 7,214 (256)

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

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration. [PDF]

Sensors (Basel), 2020
Nkenyereye L, Nkenyereye L, Tama BA, Reddy AG, Song J.   +4 more
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

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Artificial Intelligence and Access to Justice at the ‘Shop Front’: The Potential and Limitations of Meeting Legal Need Through Technology

Australian Journal of Social Issues, EarlyView.
ABSTRACT In Australia, governments fund Community Legal Centres (CLCs) as part of the legal assistance sector (LAS) to meet the ‘legal needs’ of people experiencing disadvantage who cannot afford private legal services. Persistent unmet demand for CLCs is well‐documented. As artificial intelligence (AI) is increasingly used in private legal practice to
Catherine Hastings, Art Cotterell, Farzana Bruce   +2 more
wiley   +1 more source

One Anatomy, Multiple Valve Choices: Interobserver Agreement in Selecting Transcatheter Pulmonary Valve

Catheterization and Cardiovascular Interventions, EarlyView.
Methodological framework among international observers to understand clinical decision‐making and interobserver agreement in TPVR planning. ABSTRACT Background Transcatheter pulmonary valve replacement (TPVR) requires selecting the optimal device type, size, and position. Variability in anatomical shape may affect procedural planning.
Camilo E. Pérez‐Cualtán, Jaime Cabrales, Francisco Garay, Carlos Eduardo Guerrero‐Chalela, Marcelo Rivarola, Juan P. Rozo, Juan Carlos Samayoa, Jenny Zablah, Javier Navarro‐Rueda, Juan C. Briceño Triana, Luis Felipe Giraldo   +10 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Experimental methods in chemical engineering: Cyclic voltammetry—CV

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Cyclic voltammetry (CV) is a foundational electroanalytical technique for investigating redox behaviour and evaluating material performance across fields such as molecular electrochemistry, electrocatalysis, sensing, and energy storage. Despite its widespread use, a gap remains between formal electrochemical theory and the practical data ...
Yasser Matos‐Peralta, Christopher Panaritis, JoElen Hagler, Clara Santato, Gregory S. Patience   +4 more
wiley   +1 more source