Results 1 to 10 of about 749,068 (264)

Simultaneous Improvement of Yield Strength and Ductility at Cryogenic Temperature by Gradient Structure in 304 Stainless Steel [PDF]

open access: yesNanomaterials, 2021
The tensile properties and the corresponding deformation mechanism of the graded 304 stainless steel (ss) at both room and cryogenic temperatures were investigated and compared with those of the coarse-grained (CGed) 304 ss.
Shuang Qin   +3 more
doaj   +2 more sources

Gradient Structure Construction of High Thermal Conductivity Polyurethane/Boron Nitride Composite Fiber Membrane for Thermal Management [PDF]

open access: yesMolecules
Accompanied by the rapid progress of the digital era and the continuous innovation of material science and technology, wearable electronic devices are widely used in various industries due to their excellent portability and flexibility.
Zhengyang Miao   +3 more
doaj   +2 more sources

Improvement of Aerosol Filtering Performance of PLLA/PAN Composite Fiber with Gradient Structure [PDF]

open access: yesNanomaterials, 2022
Since commercial non-woven air filtering materials have unstable filtering efficiency and poor moisture permeability for the abundant condensed aerosol particles in the highly humid atmospheric environment, the PLLA/PAN composite fiber material with a ...
Ping Zhu, Wang Sun, Yunchun Liu
doaj   +2 more sources

Extraordinary strain hardening by gradient structure. [PDF]

open access: yesProc Natl Acad Sci U S A, 2014
Significance Nature creates the gradient structure (GS) for a purpose: to make biological systems strong and tough to survive severe natural forces. For the grain-size GS, the deformation physics is still unclear. One wonders if the grain-size GS in the nanomicroscale would also benefit materials engineered by mankind.
Wu X, Jiang P, Chen L, Yuan F, Zhu YT.
europepmc   +4 more sources

The Structure of Conservative Gradient Fields [PDF]

open access: yesSIAM Journal on Optimization, 2021
The classical Clarke subdifferential alone is inadequate for understanding automatic differentiation in nonsmooth contexts. Instead, we can sometimes rely on enlarged generalized gradients called "conservative fields", defined through the natural path-wise chain rule: one application is the convergence analysis of gradient-based deep learning ...
Adrian S. Lewis, Tonghua Tian
openaire   +2 more sources

Structured Stochastic Gradient MCMC

open access: yesCoRR, 2021
paper accepted in ICML2022.
Antonios Alexos   +2 more
openaire   +3 more sources

Review on Anti-Fatigue Performance of Gradient Microstructures in Metallic Components by Laser Shock Peening

open access: yesMetals, 2023
Laser-shock-peening technology is an international research hotspot in the surface-strengthening field, which utilizes the mechanical effects of laser-induced plasma shock waves to effectively improve the fatigue performance of metallic components by ...
Fei Yang   +5 more
doaj   +1 more source

Methods for Obtaining a Gradient Structure

open access: yesУспехи физики металлов
The methods for fabrication of the functionally-gradient materials, which have a high complex of unique mechanical, technological and special properties, when they working on impact, wear, fatigue, experiencing increased cyclic and alternating loads, are
I.E. Volokitina, A.I. Denissova, A.V. Volokitin, and E.A. Panin
doaj   +2 more sources

Thermo-Economic Assessments on a Heat Storage Tank Filled with Graded Metal Foam

open access: yesEnergies, 2022
To save and better deploy waste heat, the use of a mobilized heat storage system (MHSS) with phase change enhancement means is developed. In this paper, three kinds of gradient structures (positive gradient, negative gradient, and non-gradient) are ...
Gang Liu   +5 more
doaj   +1 more source

On the Overlooked Structure of Stochastic Gradients

open access: yesAdvances in Neural Information Processing Systems 36, 2023
Stochastic gradients closely relate to both optimization and generalization of deep neural networks (DNNs). Some works attempted to explain the success of stochastic optimization for deep learning by the arguably heavy-tail properties of gradient noise, while other works presented theoretical and empirical evidence against the heavy-tail hypothesis on ...
Zeke Xie   +3 more
openaire   +3 more sources

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