Results 171 to 180 of about 23,148 (262)

Habitat‐Specific Design Strategies for Untethered Soft Robots

open access: yesAdvanced Science, EarlyView.
Habitat shapes the design of untethered soft robots. Across land, water, air, and living tissues, environmental constraints govern viable combinations of compliant structures, actuation mechanisms, and energy delivery. This review connects these constraints with robotic performance and identifies design principles for advancing adaptable, durable, and ...
Siyang Li   +3 more
wiley   +1 more source

Data‐Driven and Physics‐Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence

open access: yesAdvanced Science, EarlyView.
This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Wenbo Hui   +4 more
wiley   +1 more source

Multifunctional Matrix‐Activated Electrodes Enabling Efficient Proton Transport and Durable Low‐Pt Operation for High‐Temperature Proton Exchange Membrane Fuel Cells

open access: yesAdvanced Energy Materials, EarlyView.
This work introduces a CeHP‐enabled multifunctional matrix‐activated electrode (MME) for high‐temperature PEM fuel cells, forming an electrochemically and mechanically functional matrix within the catalyst layer. The design increases peak power density by 38% and reduces voltage decay by 62% at 240 °C, while using only 40% of the Pt loading of a ...
Gyeongseok Gwak   +12 more
wiley   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury   +4 more
wiley   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia   +2 more
wiley   +1 more source

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