Results 101 to 110 of about 6,070,112 (198)

Physical Origin of Temperature Induced Activation Energy Switching in Electrically Conductive Cement

Advanced Science, EarlyView.
The temperature‐induced Arrhenius activation energy switching phenomenon of electrical conduction in electrically conductive cement originates from structural degradation within the biphasic ionic‐electronic conduction architecture and shows percolation‐governed characteristics: pore network opening dominates the low‐percolation regime with downward ...
Jiacheng Zhang, Xinyuan Ke, Andrew Heath, Richard J. Ball, Jiawei Xie, Jinchen Fan, Guisheng Li, Kevin Paine   +7 more
wiley   +1 more source

Portfolio Analysis with Multivariate Normal Tempered Stable Processes and Distributions

, 2011
Using the construction approach of Brownian subordination, the univariate framework of Normal Tempered Stable Lévy processes is extended to an arbitrary number of dimensions. A thorough study of the mathematical properties of the multivariate stochastic process is followed by various applications of its distributions in financial econometrics and ...
openaire   +3 more sources

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Exact Simulation of Finite Variation Tempered Stable Ornstein-Uhlenbeck Processes

, 2009
MI: Global COE Program Education-and-Research Hub for Mathematics-for-IndustryグローバルCOEプログラム「マス･フォア･インダストリ教育研究拠点」We develop an exact yet simple simulation algorithm for a wide class of Ornstein-Uhlenbeck processes with a tempered stable stationary ...
Masuda, Hiroki, Kawai, Reiichiro, 河合, 玲一郎, 増田, 弘毅   +3 more
core  

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

New High‐Tc Charge‐Transfer Multiferroicity in the Quasi‐2D Antiferromagnet CrSbS3

Advanced Science, EarlyView.
ABSTRACT Low‐dimensional magnets, particularly 2D systems, offer a rich platform for realizing unconventional multiferroic mechanisms, especially when multiple polarization channels coexist. In the quasi‐2D antiferromagnet CrSbS3, which crystallizes in the centrosymmetric orthorhombic space group Pnma and orders magnetically at TN ≈ 90 K, two ...
Hung‐Cheng Wu, Yu‐Hsin Liao, Chih‐Chung Tsai, Pei‐Ying Yang, Yu‐Hao Chang, Yu‐Hui Liang, D. Chandrasekhar Kakarla, Ajay Tiwari, C. Dhanasekhar, Chin‐Wei Wang, Daisuke Okuyama, Chia‐Nung Kuo, Chin‐Shan Lue, Tzu‐Hsuan Weng, Kung‐Hsuan Lin, Jau‐Wern Chiou, Chi‐Hung Lee, Hung‐Duen Yang   +17 more
wiley   +1 more source

Value at Risk (VaR) and the alpha-stable distribution [PDF]

Volatility in financial markets is a matter of considerable concern to financial institutions and their supervisors. Already it is clear that this volatility has had an adverse effect on the real economy.
John C. Frain
core  

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source