Results 121 to 130 of about 405,787 (272)
We present ultrathin flexible transparent electrodes through iCVD‐enabled molecular control of 10 nm gold films on poly(dimethylaminomethylstyrene). In vivo validation demonstrated photoelectric artifact reduction vs. opaque electrodes and preservation of natural neural dynamics.
Tae Jin Mun +11 more
wiley +1 more source
Photon Avalanching Nanoparticles: The Next Generation of Upconverting Nanomaterials?
This Perspective outlines the mechanistic foundations that enable photon‐avalanche (PA) behavior in lanthanide nanomaterials and contrasts them with emerging application spaces and forward‐looking design strategies. By bridging threshold engineering, energy‐transfer dynamics, and materials engineering, we provide a coherent roadmap for advancing the ...
Kimoon Lee +7 more
wiley +1 more source
Bio‐Inspired Multimodal Hardware Front‐End Enabled by 2D Floating‐Gate Memory for UAV Perception
A MoS2/h‐BN /graphene floating‐gate memory underpins a bio‐inspired multimodal front end that integrates visual, inertial, and airflow cues. A 4 × 4 FG memory array encodes temporal intensity differences, while IMU‐ and airflow‐driven threshold modulation suppresses self‐motion artifacts, enabling fast, low‐power, robust autonomous UAV tracking and ...
Lianghao Guo +11 more
wiley +1 more source
Amyloidogenic Peptide Fragments Designed From Bacterial Collagen‐like Proteins Form Hydrogel
This study identified amyloidogenic sequence motifs in bacterial collagen‐like proteins and exploited these to design peptides that self‐assemble into β‐sheet fibers and form hydrogels. One hydrogel supported healthy fibroblast growth, showing promise for biocompatible materials. Our work demonstrates that bacterial sequences can be harnessed to create
Vamika Sagar +5 more
wiley +1 more source
Engineering Strategies for Stable and Long‐Life Alkaline Zinc‐Based Flow Batteries
Alkaline zinc‐based flow batteries face persistent challenges from unstable zinc deposition, including dendrite growth, passivation, corrosion, and hydrogen evolution, which severely limit cycling stability. Current research addresses these issues through coordinated electrode structuring, electrolyte regulation, and membrane design to control zinc ...
Yuran Bai +6 more
wiley +1 more source
Thermodynamics-Informed Graph Neural Networks
In this paper we present a deep learning method to predict the temporal evolution of dissipative dynamic systems. We propose using both geometric and thermodynamic inductive biases to improve accuracy and generalization of the resulting integration scheme. The first is achieved with Graph Neural Networks, which induces a non-Euclidean geometrical prior
Quercus Hernández +3 more
openaire +2 more sources
Human periosteum‐derived cell spheroids bioprinted at high density within a hyaluronic acid matrix promote fusion and hypertrophic cartilage formation in vitro. Early encapsulation enhances spheroid interaction and matrix maturation, generating scalable cartilage templates intended for endochondral bone regeneration.
Ane Albillos Sanchez +6 more
wiley +1 more source
Thermal Processing Creates Water‐Stable PEDOT:PSS Films for Bioelectronics
Instead of using chemical cross–linkers, it is shown that PEDOT:PSS thin films for bioelectronics become water‐stable after a simple heat treatment. The heat treatment is compatible with a range of rigid and elastomeric substrates and films are stable in vivo for >20 days.
Siddharth Doshi +16 more
wiley +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
Existing Graph Neural Networks (GNNs) are limited to process graphs each of whose vertices is represented by a vector or a single value, limited their representing capability to describe complex objects. In this paper, we propose the first GNN (called Graph in Graph Neural (GIG) Network) which can process graph-style data (called GIG sample) whose ...
Wang, Jiongshu +4 more
openaire +2 more sources

