Results 21 to 30 of about 55,134 (231)

Packaging of Macroscopic Material Payloads: Needs, Challenges, Concepts, and Future Directions

open access: yesAdvanced Engineering Materials, EarlyView.
This review introduces a unified framework that decomposes any macroscopic packaging system into the payload, packaging material, and packaging strategy and combines them into a conceptual packaging equation: packaging strategy = payload + packaging material.
Venkata S. R. Jampani, Manos Anyfantakis
wiley   +1 more source

Division subspaces and integrable kernels

open access: yes, 2018
In this note we prove that the reproducing kernel of a Hilbert space satisfying the division property has integrable form, is locally of trace class, and the Hilbert space itself is a Hilbert space of holomorphic functions.Comment: 11 ...
Bufetov, Alexander I., Romanov, Roman V.
core   +3 more sources

EBSD Study of Creep‐Induced Lattice Misorientation in MgO‐Particle‐Reinforced Austenitic Steel Composites

open access: yesAdvanced Engineering Materials, EarlyView.
Creep experiments at 900°C on coarse‐grained steel‐ceramic composites containing recycled magnesia reveal that higher ceramic volume fractions significantly enhance the creep resistance. Detailed EBSD investigations identify subgrain formation in the steel matrix as the dominant deformation mechanism.
Moritz Müller   +6 more
wiley   +1 more source

Analysis of unbounded operators and random motion

open access: yes, 2009
We study infinite weighted graphs with view to \textquotedblleft limits at infinity,\textquotedblright or boundaries at infinity. Examples of such weighted graphs arise in infinite (in practice, that means \textquotedblleft very\textquotedblright large ...
Dunford N.   +6 more
core   +1 more source

Multimodal Data‐Driven Microstructure Characterization

open access: yesAdvanced Engineering Materials, EarlyView.
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

Sampling and Reconstruction of Signals in a Reproducing Kernel Subspace of $L^p({\Bbb R}^d)$

open access: yes, 2009
In this paper, we consider sampling and reconstruction of signals in a reproducing kernel subspace of $L^p(\Rd), 1\le p\le \infty$, associated with an idempotent integral operator whose kernel has certain off-diagonal decay and regularity.
Nashed, M. Zuhair, Sun, Qiyu
core   +1 more source

Weighted reproducing kernels in Bergman spaces.

open access: yesMichigan Mathematical Journal, 1994
A major inspiration for this paper is the factorization theory developed by \textit{H. Hedenmalm} [J. Reine Angew. Math. 422, 45-68 (1991; Zbl 0734.30040)] for the standard Bergman space \(A^2\), and later generalized to the Bergman space \(A^2\) by \textit{P. Duren}, \textit{D. Khavinson}, \textit{H. S. Shapiro} and \textit{C. Sundberg} [Pac. J. Math.
MacGregor, T. H., Stessin, M. I.
openaire   +2 more sources

Influence of Test Temperature and Test Frequency on Fatigue Life of Aluminum Alloy EN AW‐2618A

open access: yesAdvanced Engineering Materials, EarlyView.
The influence of test temperature and test frequency on the fatigue life of EN AW‐2618A is investigated. High‐cycle fatigue tests are performed at different test temperatures and frequencies on the 1000 h/230°C overaged state. Both test parameters reduce fatigue life due to time‐dependent damage mechanisms.
Ying Han   +5 more
wiley   +1 more source

3D (Bio) Printing Combined Fiber Fabrication Methods for Tissue Engineering Applications: Possibilities and Limitations

open access: yesAdvanced Functional Materials, EarlyView.
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana   +2 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced Functional Materials, EarlyView.
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

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