Results 211 to 220 of about 585,938 (268)

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Composition‐Tuned Enhancement of the Anomalous Nernst Effect in FeCo–Pt Thin Films on Rigid and Flexible Substrates

Advanced Engineering Materials, EarlyView.
Disordered (Fe50Co50)1−xPtx thin films exhibit a pronounced anomalous Nernst effect (ANE) with a strong composition dependence on both rigid and flexible substrates. The transverse thermoelectric response peaks near 22.5 at.% Pt, accompanied by enhanced αxy/σxy scaling, thermal transport, and ANE sensitivity.
Mojtaba Mohammadi, Hiroyuki Awano, Kenji Tanabe   +2 more
wiley   +1 more source

Low‐Angle Grain Boundaries and Re‐Segregation in Single‐Crystalline Ni‐Base Superalloys

Advanced Engineering Materials, EarlyView.
This work demonstrates that Re‐segregation at low‐angle grain boundaries (LAGBs) in Ni‐base superalloys is influenced by misorientation angle. Advanced microscopy and atom probe tomography reveal that higher misorientation angles increases Re‐segregation.
Alireza B. Parsa, Aparna Saksena, Alesander Kostka, Pascal Thome, Felicitas Scholz, Alexandre Mussi, Christoph Somsen, Baptiste Gault, Jan Frenzel, Gunther Eggeler   +9 more
wiley   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

Creating Ti–Fe α/β Alloys by Diffusion‐Driven Solid‐State Processing

Advanced Engineering Materials, EarlyView.
This study proposes making alloys containing fast diffusing elements that are difficult to produce by ingot metallurgy, by diffusion‐driven solid‐state HIP processing of elemental powders and low‐temperature homogenisation. Here, novel Fe‐Ti α–β alloys are formed having fine α–β lamellae, a small β prior grain size without significant intermetallics ...
Jiaqi Xu, Xun Zhang, Jack M. Donoghue, Albert D. Smith, Rahul Unnikrishnan, Rhys Thomas, Vahid Nekouie, Jie Luo, Dongchen Hu, Michael Preuss, Philip J. Withers   +10 more
wiley   +1 more source

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Coupled Principal Component Analysis

IEEE Transactions on Neural Networks, 2004
A framework for a class of coupled principal component learning rules is presented. In coupled rules, eigenvectors and eigenvalues of a covariance matrix are simultaneously estimated in coupled equations. Coupled rules can mitigate the stability-speed problem affecting noncoupled learning rules, since the convergence speed in all eigendirections of the
Möller, Ralf, Könies, Axel
openaire   +5 more sources

Quantitative analysis of system coupling

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011
To solve the problem that it is difficult to calculate system coupling in the field of systems science and software engineering, this article discussed quantitative analysis of system coupling. It is difficult to calculate system coupling in the field of system science and software engineering.
Yin Zhang 0002, Hua Zhou, Qing Duan, Yun Liao, Junhui Liu, Zhenli He   +5 more
openaire   +1 more source

Dynamic coupled component analysis

Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2005
We present a method for simultaneously learning linear models of multiple high dimensional data sets and the dependencies between them. For example, we learn asymmetrically coupled linear models for the faces of two different people and show how these models can be used to animate one face given a video sequence of the other.
Fernando De la Torre, Michael J. Black
openaire   +1 more source

Statistical Timing Analysis With Coupling

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2006
As technology scales to smaller dimensions, increasing process variations and coupling induced delay variations make timing verification extremely challenging. In this paper, the authors establish a theoretical framework for statistical timing analysis with coupling.
Debjit Sinha, Hai Zhou 0001
openaire   +1 more source