Results 1 to 10 of about 99 (99)

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

3D Bioprinting of Thick Adipose Tissues with Integrated Vascular Hierarchies

open access: yesAdvanced Functional Materials, Volume 35, Issue 12, March 18, 2025.
An advanced 3D bioprinting technique is used here to create thick adipose tissues with a central, vessel and extensive branching. The construct is made using alginate, gelatin and collagen‐based bioinks. Flow through the complex vessel network is demonstrated as well as its successful integration with a femoral artery following implantation in a rat ...
Idit Goldfracht   +5 more
wiley   +1 more source

Material Composition Gradient Controls the Autonomous Opening of Banksia Seed Pods in Fire‐Prone Habitats

open access: yesAdvanced Functional Materials, EarlyView.
The seed pod valves of Australian Banksia attenuata plants are not simply bi‐layers which bend when dry. These experiments and models reveal complex mechanics, which allow seed release only after several steps of seed pod opening. Stiffness gradients prevent delamination of the valves during loading, and a shape‐memory function protects the seeds ...
Friedrich Reppe   +7 more
wiley   +1 more source

Stratum Corneum‐Inspired Zwitterionic Hydrogels with Intrinsic Water Retention and Anti‐Freezing Properties for Intelligent Flexible Sensors

open access: yesAdvanced Functional Materials, EarlyView.
A novel stratum corneum‐inspired zwitterionic hydrogel is developed for intelligent, flexible sensors, featuring intrinsic water retention and anti‐freezing properties. The quasi‐gel, composed of hygroscopic polymers and bound water, maintains its softness across a wide range of humidity.
Meng Wu   +8 more
wiley   +1 more source

Flexible Leaf‐Like Fuel Cell From Plasmonic Janus Nanosheet

open access: yesAdvanced Functional Materials, EarlyView.
A flexible leaf‐like fuel cell is fabricated by conductive gold nanowire sponge‐supported plasmonic Janus nanosheet, which can generate a power of 8.93 mW cm⁻2 with less than 10% performance deterioration even being bent or twisted. Further assembly in a tree‐like layout demonstrates omnidirectional light harvesting capability and wind resistance ...
Yifeng Huang   +3 more
wiley   +1 more source

Carbon Nanotube 3D Integrated Circuits: From Design to Applications

open access: yesAdvanced Functional Materials, EarlyView.
As Moore's law approaches its physical limits, carbon nanotube (CNT) 3D integrated circuits (ICs) emerge as a promising alternative due to the miniaturization, high mobility, and low power consumption. CNT 3D ICs in optoelectronics, memory, and monolithic ICs are reviewed while addressing challenges in fabrication, design, and integration.
Han‐Yang Liu   +3 more
wiley   +1 more source

Active Learning‐Driven Discovery of Sub‐2 Nm High‐Entropy Nanocatalysts for Alkaline Water Splitting

open access: yesAdvanced Functional Materials, EarlyView.
High‐entropy nanoparticles (HENPs) hold great promise for electrocatalysis, yet optimizing their compositions remains challenging. This study employs active learning and Bayesian Optimization to accelerate the discovery of octonary HENPs for hydrogen and oxygen evolution reactions.
Sakthivel Perumal   +5 more
wiley   +1 more source

High‐Entropy Magnetism of Murunskite

open access: yesAdvanced Functional Materials, EarlyView.
The study of murunskite (K2FeCu3S4) reveals that its magnetic and orbital order emerges in a simple I4/mmm crystal structure with complete disorder in the transition metal positions. Mixed‐valence Fe ions randomly occupy 1/4 of the tetrahedral sites, with the remaining 3/4 being filled by non‐magnetic Cu+ ions.
Davor Tolj   +18 more
wiley   +1 more source

Predicting Aggregation Behavior of Nanoparticles in Liquid Crystals via Automated Data‐Driven Workflows

open access: yesAdvanced Functional Materials, EarlyView.
Herein, a comprehensive framework that enabled the optimization of colloidal solubility within a high‐dimensional parameter space and study of reversible assembly processes is developed. This data‐driven workflow integrated innovations including the robotic platform for automated AuNPs functionalization, machine learning for predicting and revealing ...
Yueyang Gao   +5 more
wiley   +1 more source

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