Results 81 to 90 of about 1,258,060 (324)

A tail estimate for empirical processes of multivariate Gaussian under general dependence [PDF]

, 2023
Wen Huo, Yasutaka Shimizu
openalex   +1 more source

Fabrication of Multifunctional FeSi Gyroid Lattice Composites via Additive Manufacturing and Polymer Infiltration

Advanced Engineering Materials, EarlyView.
A two‐step approach combining laser powder bed fusion of FeSi electrical steel with Bakelite infiltration enables the fabrication of multifunctional gyroid lattice composites. The resulting structures exhibit high strength, magnetic anisotropy, and complete polymer infiltration, demonstrating a simple and scalable route toward lightweight, mechanically
Angelo F. Andreoli, Mayumi A. Nakahashi, Vitor E. Pinotti, Felipe O. C. Bernardo, Lidiane C. Costa, Francisco G. Coury, Ronei C. de Oliveira, Adilson J. A. de Oliveira, Carlos E. H. Ventura, Piter Gargarella   +9 more
wiley   +1 more source

deform: An R Package for Nonstationary Spatial Gaussian Process Models by Deformations and Dimension Expansion [PDF]

, 2023
Benjamin D. Youngman
openalex   +1 more source

Four‐Point Bending Tests at High Temperatures on Commercial MgO‐C Refractory Bricks with and Without Recyclate Considering Different Carbon Contents

Advanced Engineering Materials, EarlyView.
Four‐point bending tests are conducted in an argon atmosphere on commercial MgO‐C brick grades with and without MgO‐C recyclate from room temperature up to 1300 °C. No detrimental effect of the MgO‐C recyclates on bending strength is found. Instead, a decisive influence of the total carbon content is observed, with lower total carbon contents ...
Alexander Schramm, Lukas Knöchel, Thomas Schemmel, Christos G. Aneziris, Anja Weidner, Horst Biermann   +5 more
wiley   +1 more source

Revisiting statefinder via Gaussian process

European Physical Journal C: Particles and Fields
The statefinder diagnostic is useful to discriminate dark energy models. In this paper, under the minimum assumption of a spatially flat Friedmann–Lemaître–Robertson–Walker Universe, we reconstruct the statefinder pair $$\{r(z),s(z)\}$$ { r ( z ) , s ( z
Zhihua Feng, Lixin Xu
doaj   +1 more source

Long-Term Forecasting of Solar Irradiation in Riyadh, Saudi Arabia, Using Machine Learning Techniques

Big Data and Cognitive Computing
Forecasting of time series data presents some challenges because the data’s nature is complex and therefore difficult to accurately forecast. This study presents the design and development of a novel forecasting system that integrates efficient data ...
Khalil AlSharabi, Yasser Bin Salamah, Majid Aljalal, Akram M. Abdurraqeeb, Fahd A. Alturki   +4 more
doaj   +1 more source

Enhancing Optoelectronic Properties in Phthalocyanine‐Based SURMOFs: Synthesis of ABAB Linkers by Avoiding Statistical Condensation with Tailored Building Blocks

Advanced Functional Materials, EarlyView.
A novel phthalocyanine (PC)‐based metal–organic framework (MOFs) is synthesized using ditopic PC linkers obtained through regioselective statistical condensation. The resulting MOF exhibits significant improvements in electronic absorption, thereby enhancing the material's performance in light harvesting and energy conversion.
Lukas S. Langer, Mareen Stahlberger, Xiaojing Liu, Yi Luo, Niklas E. Häußermann, Puja Singhvi, Yidong Liu, Olaf Fuhr, Martin Nieger, Lars Heinke, Thomas Heine, Christof Wöll, Stefan Bräse   +12 more
wiley   +1 more source

Organic Electrochemical Transistor Channel Materials: Copolymerization Versus Physical Mixing of Glycolated and Alkoxylated Polymers

Advanced Functional Materials, EarlyView.
This work discusses the use of blended channel materials in OECTs. It explores how mixing glycolated and alkoxylated polymers in various ratios offers a simpler and more efficient route to tuning OECT properties. The performance of the polymer blends is compared to the corresponding copolymers, demonstrating similar OECT characteristics, swelling ...
Lize Bynens, Kaishuai Zhang, Priscila Cavassin, Arwin Goossens, Jochen Vanderspikken, Tania C. H. Castillo, Demetra Tsokkou, Adam Marks, Arianna Magni, Karrie Weaver, Laurence Lutsen, Sahika Inal, Koen Vandewal, Natalie Banerji, Wouter Maes   +14 more
wiley   +1 more source

Monte Carlo simulation for variable-density groundwater flow through reduced-order model coupled with Gaussian process

Shuiwen dizhi gongcheng dizhi
Variable-density groundwater flow (VDGF) is jointly driven by hydraulic and density gradient, leading to strong nonlinearity, large computational burden of numerical models, and therefore huge computational cost of Monte Carlo simulation for uncertainty ...
Chuan’an XIA, Xiufeng FAN, Hao WANG, Wenbin JIAN   +3 more
doaj   +1 more source

Pre-trained Gaussian Processes for Bayesian Optimization [PDF]

, 2021
Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek   +7 more
openalex   +1 more source