Results 221 to 230 of about 6,434,325 (301)

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Structure-Property Relationships in Urea-Formaldehyde Bonded Napier Grass Composites: Influence of Lignocellulosic Chemistry on Interfacial Interaction and Thermal Stability. [PDF]

ACS Omega
Bairwan RD, Ying GY, Abdullah CK, Jeffri NI, Mohamad Khalid MSF, Edrus SSOA, Mohammad Rawi NF.   +6 more
europepmc   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

Dual Action of Phase Separation and Mechanical Locking Enabled Low-Value Waste Wood Into High-Performance Structural Phase-Change-Induced Self-Healing Materials. [PDF]

Adv Mater
Ma Q, Liu Y, Zhou J, Wang F, Liu K, Ji X, Qiao L, Tian X, Ba S, Cui S, Liu B, Li Y, Li G, Yang H, Jia Z, Wang C.   +15 more
europepmc   +1 more source

On the Dielectric Properties of Wood

Busseiron Kenkyu, 1953
openaire   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Effect of Long-Term Outdoor Storage on the Multi-Scale Structural and Mechanical Properties of Oriental Beech (<i>Fagus orientalis</i> Lipsky) and European Hornbeam (<i>Carpinus betulus</i> L.) Wood. [PDF]

Polymers (Basel)
Şirin G.
europepmc   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Against the grain: Discovery of wood-nesting reveals hidden substrate flexibility in a major bee lineage. [PDF]

Ecology
Soh ZWW, Ascher JS.
europepmc   +1 more source

Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer

Advanced Science, EarlyView.
This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu, Xia Ling, Xianhe Zhang, Chuanjiang Jian, Leilei Shi, Wentao Song, Xiaonan Wang, Bin Liu   +7 more
wiley   +1 more source