Results 81 to 90 of about 30,820 (254)

Strain‐Activated Mechanical Metamaterial With Programmable Dual‐Phase Stiffness and Enhanced Energy Absorption

Advanced Materials Technologies, EarlyView.
A strain‐activated mechanical metamaterial is developed to achieve programmable dual‐phase stiffness through an intrinsic geometric locking mechanism. Finite element modeling and parametric analysis identify the key design parameters governing activation strain, stiffness transition, and energy absorption.
Ramin Yousefi‐Nooraie, Romain Lemoine, Mario Guagliano, Sara Bagherifard   +3 more
wiley   +1 more source

Structure and Tensile Properties of Pb–0.3%Sn–0.1%Ca Negative Grid Alloy for Lead-Acid Batteries

East European Journal of Physics
The structure and tensile properties of Pb–0.3%Sn–0.1%Ca alloy for negative grids of lead-acid batteries have been characterised as functions of mould preheating temperature during casting and ageing time during storage under atmospheric conditions ...
Victor O. Dzenzerskiy, Serhii V. Tarasov, Olena V. Sukhova, Dmytro O. Redchyts, Volodymyr A. Ivanov   +4 more
doaj   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Degradable Magnetic Composites from Recycled NdFeB Magnets for Soft Actuation and Sensing

Advanced Robotics Research, EarlyView.
This work presents a degradable soft magnetic composite made from recycled NdFeB particles embedded in a gelatin‐based organogel. The material is processed into magnetic sensors and soft robotic components, which can later be dissolved in a green solvent to recover NdFeB magnetic particles.
Muhammad Bilal Khan, Lin Guo, Kilian Schäfer, Eduardo Sergio Oliveros‐Mata, Xiaotao Wang, Florian Hofmann, Matthias Lutzi, Mark Suppelt, Proloy Taran Das, Jan Schmidtpeter, Imants Dirba, Stephan Rinderknecht, Mario Kupnik, Denys Makarov, Oliver Gutfleisch   +14 more
wiley   +1 more source

In Situ X‐Ray Tomography and Acoustic Emission Monitoring of Damage Evolution in C/C‐SiC Composites Fabricated by Liquid Silicon Infiltration

Advanced Science, EarlyView.
This study investigates how the internal structure of fiber‐reinforced ceramic composites affects their resistance to damage. By combining 3D X‐ray imaging with acoustic emission monitoring during mechanical testing, it reveals how silicon distribution influences crack formation.
Yang Chen, Renato S. M. Almeida, Stefan Flauder, Guillaume Couégnat, Kamen Tushtev, Jürgen Horvath, Peter Wriggers, Kurosch Rezwan   +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

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

Estimation of the ultimate tensile strength and yield strength for the pure metals and alloys by using the acoustic wave properties. [PDF]

Sci Rep, 2020
Mohammed AA, Haris SM, Al Azzawi W.
europepmc   +1 more source

A Model for the Effect of Microstructure on the Ultimate Tensile Strength of Cast Irons

International Journal of Metalcasting
Abstract The aim of the present study is to elucidate the influence of individual microstructural parameters, such as pearlite fraction, nodularity, and eutectic cell size, on the tensile strength (UTS) of cast irons. The UTS model was built by integrating the rule of mixtures for each microstructural component, and the UTS was described as a
Taishi Matsushita, Björn Domeij, Vasilios Fourlakidis, Ilja Belov, Attila Diószegi   +4 more
openaire   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source