Results 41 to 50 of about 322,705 (229)
Multimodal Data‐Driven Microstructure Characterization
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič +7 more
wiley +1 more source
This study presents novel anti‐counterfeiting tags with multilevel security features that utilize additional disguise features. They combine luminescent nanosized Ln‐MOFs with conductive polymers to multifunctional mixed‐matrix membranes and powder composites. The materials exhibit visible/NIR emission and matrix‐based conductivity even as black bodies.
Moritz Maxeiner +9 more
wiley +1 more source
The study presents biodegradable and recyclable mixed‐matrix membranes (MMMs), hydrogels, and cryogels using luminescent nanoscale metal‐organic frameworks (nMOFs) and biopolymers. These bio‐nMOF‐MMMs combine europium‐based nMOFs as probes for the status of the materials with the biopolymers agar and gelatine and present alternatives to conventional ...
Moritz Maxeiner +4 more
wiley +1 more source
3D‐Printed Sulfur‐Derived Polymers With Controlled Architectures for Lithium‐Sulfur Batteries
Rheology‐guided formulation design for direct ink writing enables the fabrication of 3D sulfur copolymer cathodes with controlled architectures for lithium‐sulfur batteries. The printed electrodes exhibit multiscale porosity and high sulfur utilization, delivering enhanced electrochemical performance compared to conventional cast electrodes.
Bin Ling +7 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Slight Truncation Changes in Iron Oxide Nanocubes Strongly Affect Their Magnetic Properties
Subtle variations in nanoparticle morphology can lead to significant changes in functional properties. An automated shape‐fitting method captures minor differences in corner truncation between iron oxide nanocubes of similar sizes synthesized under identical conditions, revealing pronounced disparities in their magnetic and hyperthermia behavior ...
Kingsley Poon +7 more
wiley +1 more source
An asymptotic dimension for metric spaces, and the 0-th Novikov-Shubin invariant
A nonnegative number d_infinity, called asymptotic dimension, is associated with any metric space. Such number detects the asymptotic properties of the space (being zero on bounded metric spaces), fulfills the properties of a dimension, and is invariant ...
Guido, Daniele, Isola, Tommaso
core
An innovative medium entropy alloy (MEA) composite material was fabricated via micro laser powder bed fusion (μ‐LPBF) with appropriate nano‐ceramic particles doping and exhibited markedly improved overall performance, including synergistically enhanced strength and ductility, increased hardness and compressive strength, improved wear resistance and ...
Zhonglin Shen, Mingwang Fu
wiley +1 more source
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa +19 more
wiley +1 more source

