Results 161 to 170 of about 31,120 (273)

Pattern Formation in Non‐Equilibrium Architected Materials

open access: yesAdvanced Materials Technologies, EarlyView.
This article demonstrates an artificial mechanical system ‐ a robotic metamaterial ‐ as an accessible and versatile platform within which to explore and prescribe the reaction‐diffusion driven pattern formation hitherto associated with comparatively less accessible and versatile non‐equilibrium biological and chemical systems.
Vinod Ramakrishnan, Michael J. Frazier
wiley   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

open access: yesAdvanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue   +8 more
wiley   +1 more source

Smart and Sustainable Sizing: Investigating the Sensing Behavior of Glass Fabrics Coated With Waterborne Polyurethane/Graphene Dispersions

open access: yesAdvanced Materials Technologies, EarlyView.
Waterborne polyurethane/graphene formulations are developed as piezoresistive coatings on glass fabric to enable flexible strain sensing. The graphene‐enabled conductive network provides a stable electromechanical response under cyclic compression. The coating demonstrates reliable pressure‐dependent resistance changes, highlighting its potential for ...
Vishnu Vijayan Pillai   +8 more
wiley   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

open access: yesAdvanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding   +5 more
wiley   +1 more source

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