Results 161 to 170 of about 221,379 (304)

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

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios   +4 more
wiley   +1 more source

Toward More Autonomous Soft Robots: Development and Characterization of a 3D‐Printed Pneumatic Contact Sensor for a Six‐Legged Soft Robotic Walker

open access: yesAdvanced Intelligent Systems, EarlyView.
This article introduces a fully 3D‐printed, electronics‐free sensory system for a six‐legged soft robot, enabling adaptive responses such as obstacle detection and directional changes using pneumatic logic gates. The design demonstrates efficient, robust operation through rapid sensor feedback and autonomous functionality, highlighting new ...
Philipp Auth   +6 more
wiley   +1 more source

Impact of Biomimetic Pinna Shape Variation on Clutter Echoes: A Machine Learning Approach

open access: yesAdvanced Intelligent Systems, EarlyView.
Bats with dynamic ear structures navigate dense, echo‐rich environments, yet the echoes they receive are highly random. This study shows that machine learning can reliably detect structural signatures in these seemingly chaotic biosonar signals. The results open new directions for biologically inspired sensing, where time‐varying receiver shapes ...
Ibrahim Eshera   +2 more
wiley   +1 more source

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