Results 61 to 70 of about 7,180 (259)

Developing high-strength, ductile Ni-free Fe–Cr–Mn–C–N stainless steels by interstitial-alloying and thermomechanical processing

Journal of Materials Research and Technology, 2019
Microstructures and mechanical properties of a new grade of Fe–18Cr–12Mn–CN (wt%) austenitic stainless steels interstitial-alloyed with 0.3–0.48 wt% C + N at 0.22–1.06 C/N ratios were investigated after thermomechanical processing.
Dariush Rasouli, Ahmad Kermanpur, Abbas Najafizadeh   +2 more
doaj   +1 more source

Fabrication of Fibers With Complex Features Using Thermal Drawing of 3D‐Printed Preforms

Advanced Materials Technologies, EarlyView.
3D printing enables rapid fabrication of macroscale polymer preforms with complex geometries. Thermal drawing then scales these structures into long fibers while preserving micron‐scale cross‐sectional features. This workflow provides a fast, low‐cost route to functional fibers with tailored geometries and material combinations for catheter, robotic ...
Ali Anil Demircali, Jinshi Zhao, Ayhan Aktas, Mohamed E. M. K. Abdelaziz, Burak Temelkuran   +4 more
wiley   +1 more source

Liquid Crystalline Elastomers in Soft Robotics: Assessing Promise and Limitations

Advanced Robotics Research, EarlyView.
Liquid crystalline elastomers (LCEs) are programmable soft materials that undergo large, anisotropic deformation in response to external stimuli. Their molecular alignment encodes directional actuation in a monolithic structure, making them long‐standing candidates for soft robotic systems.
Justin M. Speregen, Timothy J. White
wiley   +1 more source

Machine learning-assisted process mapping and constitutive modeling of hot deformation in lightweight steel

Journal of Materials Research and Technology
Accurate modeling of hot flow behavior in advanced lightweight steels is critical for optimizing thermomechanical processes, yet remains challenging due to the complexity of deformation mechanisms across wide temperature and strain rate ranges.
M.M. Salehi Mehr, Hamid Reza Abedi, A.R. Kalantari, A. Zarei Hanzaki   +3 more
doaj   +1 more source

Numerical Modeling of Photothermal Self‐Excited Composite Oscillators

Advanced Robotics Research, EarlyView.
We present a numerical framework for simulating photothermal self‐excited oscillations. The driving mechanism is elucidated by highlighting the roles of inertia and overshoot, as well as the phase lag between the thermal moment and the oscillation angle, which together construct the feedback loop between the system state and the environmental stimulus.
Zixiao Liu, Ryan R. Rusch, Zheng Wu, Chi Chen, Pengju Shi, Hao Qiu, Ximin He   +6 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

Microstructural Characterization Of Quenched And Plastically Deformed Two-Phase α+β Titanium Alloys

Archives of Metallurgy and Materials, 2015
Development of microstructure in two-phase α+β titanium alloys is realized by thermomechanical processing – sequence of heat treatment and plastic working operations.
Motyka M., Sieniawski J., Ziaja W., Mrówka-Nowotnik G.   +3 more
doaj   +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

Fundamentals of Thermal Transport and Energy Conversion in Ultra‐High Temperature Ceramics: From Microscale Mechanisms to Macroscopic Properties

Advanced Science, EarlyView.
This review critically examines thermal transport and radiative properties of ultra‐high temperature ceramics for hypersonic flight, advanced nuclear systems, and next‐generation energy conversion devices. It explores phonon–photon–electron interactions, microstructural engineering, thermoelectric conversion, and machine learning‐accelerated multiscale
Zhipeng Pei, Yue Li, Jiayu Xing, Yue Zhu, Ru Zhang, Huan Wu, Zihao Qin, Gang Pei, Man Li   +8 more
wiley   +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