Results 131 to 140 of about 248,546 (297)

Enhancing Specific Stiffness of Nano‐Architected Materials Through Generative AI and Active Learning

Advanced Science, EarlyView.
A structure‐centric generative framework searches voxelated design space directly, coupling a variational autoencoder with multi‐objective optimization and active learning to progressively expand the validated design domain. The discovered nano‐architectures, realized as pyrolytic carbon by two‐photon lithography, deliver 18–23% higher stiffness and 26–
Jinwook Yeo, Peter Serles, Donggeun Park, Julia R. Greer, Seunghwa Ryu   +4 more
wiley   +1 more source

Improved Deformability of Co‐Free Medium Entropy Oxides by Controlled Entropy Destabilization

Advanced Science, EarlyView.
Controlled entropy destabilization activates defect‐mediated plasticity in Co‐free (CuMgNiZn)O by promoting pre‐existing Cu‐rich secondary phases that serve as defect sources. Temperature‐dependent dislocation activity evolves from limited motion at room temperature to extensive glide and stacking‐fault formation at 600 °C, enabling improved plasticity
Chang Liu, Ke Xu, Zhongxia Shang, Yang Chen, Debargha Paul, Yinghang Liu, Jeremy Gan, Shiyu Zhou, R. Edwin García, Xinghang Zhang, Haiyan Wang   +10 more
wiley   +1 more source

Noncommutative maximal operators with rough kernels

Analysis & PDE
34 pages. Analysis & PDE.
openaire   +2 more sources

The rough guide to climate change. 'Guía del cambio climático'

, 2009
Edición actualizada que recoge el informe de 2007 del Grupo Intergubernamental de Expertos sobre el cambio climático y la evolución de los acuerdos de Kyoto.
Henson, Robert
core  

Decoupling Stable Cyclic Deformation From Defect Accumulation in Metals

Advanced Science, EarlyView.
Introducing amorphous nanoparticles into a metal matrix enables a cyclic deformation regime where strain hardening and defect accumulation are decoupled. These nanoparticles act as dislocation sinks and undergo reversible shear transformations, sustaining microstructural stability over millions of cycles.
Chenjun Ye, Shaofan Ge, Tian Yang, Leyi Tang, Kang Wang, Y. Morris Wang, Jun Ding, Zan Li, Di Zhang, En (Evan) Ma   +9 more
wiley   +1 more source

Data‐Driven and Physics‐Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence

Advanced Science, EarlyView.
This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Wenbo Hui, Yunyi Wang, Teng Zhang, Yang Chen, Min Pan   +4 more
wiley   +1 more source

Ultra‐Low Power Consumption and Highly Durability in Sm:HfO2 Thin Film Ferroelectric Memristor for Edge Detection

Advanced Electronic Materials, EarlyView.
ABSTRACT With the continuous development of computer image processing, developing efficient and low‐power computing devices has become a key challenge. Memristors have integrated in‐situ storage and computing capabilities, making them an ideal choice for low‐power image processing computing architectures. However, current memristors are confronted with
Tengyu Li, YongRui Wang, Weifeng Zhang, Jikang Xu, Xiaobing Yan   +4 more
wiley   +1 more source

AI‐Assisted Ultrasensitive Biosensing using Metal‐Electrolyte‐Metal‐Insulator‐Silicon Structure Based on Oxygen‐Tunable Iridium Oxide Nanonets for Lysyl‐Oxidase‐Like‐2 Breast Cancer Detection

Advanced Electronic Materials, EarlyView.
An oxygen‐controlled iridium‐oxide (IrOx) nano‐net structure is developed to enhance the sensitivity of metal‐electrolyte‐metal‐insulator‐silicon (MEMIS) biosensors. Integrated with a deep learning model, this platform achieves a high accuracy of 94.8% for detecting the breast cancer biomarker LOXL2.
Chiao‐Fan Chiu, Pankaj Kumar, Long Nguyen Minh Le, Ping‐Hsuan Wu, Punnatorn Boonyoung, Shen Tingyang, Abhijit Aich, Yi‐Pin Chen, Shih‐Yin Huang, Siddheswar Maikap   +9 more
wiley   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Bilinear endpoint estimates for Calderón commutator with rough kernel

, 2017
In this paper, we establish some bilinear endpoint estimates of Calderón commutator $\mathcal{C}[\nabla A,f](x)$ with a homogeneous kernel when $Ω\in L\log^+L(\mathbf{S}^{d-1})$. More precisely, we prove that $\mathcal{C}[\nabla A,f]$ maps $L^q(\mathbb{R}^d)\times L^1(\mathbb{R}^d)$ to $L^{r,\infty}(\mathbb{R}^d)$ if $q>d$ which improves previous ...
openaire   +2 more sources