Results 91 to 100 of about 244,714 (312)
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
Joint Reconstruction via Coupled Bregman Iterations with Applications to PET-MR Imaging
Joint reconstruction has recently attracted a lot of attention, especially in the field of medical multi-modality imaging such as PET-MRI. Most of the developed methods rely on the comparison of image gradients, or more precisely their location ...
Brinkmann, Eva-Maria +2 more
core +1 more source
Microstructure Evolution of a VMnFeCoNi High‐Entropy Alloy After Synthesis, Swaging, and Annealing
The synthesis and processing (rotary swaging and annealing) of the novel VMnFeCoNi alloy is investigated, alongside the estimation of the grain size effect on hardness. Analysis of a wide grain size range of recrystallized microstructures (12–210 µm) reveals a low annealing twin density.
Aditya Srinivasan Tirunilai +6 more
wiley +1 more source
Stretching the Printability Metric in Direct‐Ink Writing with Highly Extensible Yield‐Stress Fluids
This study introduces “drawability” as a new metric for assessing printability in direct‐ink writing, focusing on gap‐spanning performance and speed robustness. By designing yield‐stress fluids with high extensibility, we demonstrate that extensional strain‐to‐break significantly enhances printability.
Chaimongkol Saengow +9 more
wiley +1 more source
Traditional single-ended traveling wave fault location is sensitive to velocity uncertainty, complex topologies, and variations in the equivalent impedance of converter stations. This paper proposes a fault distance calibration method based on the fusion
Zewen Li +3 more
doaj +1 more source
When integrating evolutionary algorithms into the process of the design of modular robots, the “reality gap” problem leads to the difference between simulation and reality.
Yang Liu +4 more
doaj +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
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
Cosmological Implications of Large-Scale Flows
Cosmological implications of the observed large-scale peculiar velocities are reviewed, alone or combined with redshift surveys and CMB data. The latest version of the POTENT method for reconstructing the underlying three-dimensional velocity and mass ...
Dekel, Avishai
core +1 more source
Counterion Dependent Side‐Chain Relaxation Stiffens a Chemically Doped Thienothiophene Copolymer
Oxidation of a thienothiophene copolymer, p(g3TT‐T2), via different doping strategies and dopant molecules resulted in materials with similar oxidation levels and a high electrical conductivity of ≈100 S cm−1. However, mechanical properties varied significantly, with sub‐glass transition temperatures and elastic moduli spanning from –44°C to –3°C and ...
Mariavittoria Craighero +12 more
wiley +1 more source

