Results 211 to 220 of about 522,468 (334)

Designing Memristive Materials for Artificial Dynamic Intelligence

open access: yesAdvanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

Autonomous Machine Learning‐Based Classification and Arrangement of Submillimeter Objects Using a Capillary Force Gripper

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando   +4 more
wiley   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

open access: yesAdvanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan   +3 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

open access: yesAdvanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang   +4 more
wiley   +1 more source

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

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