Results 81 to 90 of about 2,141,833 (276)
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
Introduction to the Phillips Machine and the Analogue Computing Tradition in Economics [PDF]
In this paper I try to argue for the desirability of analog computation in economics from a variety of perspectives, using the example of the Phillips Machine. Ultimately, a case is made for the underpinning of both analog and digital computing theory in
K. Vela Velupillai
core
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
Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng +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
This study advances our understanding of aortic valve stenosis by capturing spatially resolved chemical and structural changes at the nanoscale. The findings highlight the potential of combined Raman and electron microscopy for understanding calcification mechanisms across diverse tissue types.
Robin H. M. Van der Meijden +11 more
wiley +1 more source
In this strategy, a conductive nano‐probe is employed to induce nanoscale phase transitions and map the nanoscale conductivity and trap density of GST films. By utilizing the contrasting properties of phase‐change states, nano‐resonators are fabricated that exhibit plasmonic conduction and dramatically different transport characteristics.
Sunwoo Bang +4 more
wiley +1 more source
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
Magnetic Force Microscopy Signatures of Higher‐Order Skyrmions and Antiskyrmions
Magnetic force microscopy operated under vacuum conditions enables the qualitative identification of higher‐order skyrmions and antiskyrmions in Co/Ni multilayers at room temperature. Distinct stray‐field contrast signatures arise from vertical Bloch lines and complex domain‐wall configurations.
Sabri Koraltan +8 more
wiley +1 more source

