Results 91 to 100 of about 6,335,183 (252)

Aluminium matrix composites reinforced with high entropy alloys: A comprehensive review on interfacial reactions, mechanical, corrosion, and tribological characteristics

Journal of Materials Research and Technology
Aluminium matrix composites (AMCs) reinforced with high entropy alloy particulates (HEAp) represent an innovative category of metal-matrix composites with considerable potential for fulfilling the stringent demands of emerging technological applications.
Sodiq Abiodun Kareem, Justus Uchenna Anaele, Emmanuel Omosegunfunmi Aikulola, Ufoma Silas Anamu, Abdalrhaman Koko, Michael Oluwatosin Bodunrin, Kenneth Kanayo Alaneme   +6 more
doaj   +1 more source

Wavy‐Interlocked Stretchable Triboelectric Nanogenerators Enhanced by Liquid Metal Microflowers for Self‐Powered Wearable Motion Monitoring

Advanced Science, EarlyView.
Schematic showing a stretchable triboelectric nanogenerator based on interlocked wavy architectures that uses EGaIn microflower‐embedded PVDF‐TrFE and Nylon‐6 nanofiber membranes. The multi‐petaled, electron‐rich EGaIn microflowers enhance interfacial polarization and capacitance, while the interlocked wavy architecture enlarges the effective contact ...
Qianqian Xu, Huimin Li, Hanmin Zeng, Yahui Meng, Yimeng He, Xinke Hu, Senfeng Zhao, Jianxun Zhang, Peiqiong Zhou, Kechao Zhou, Dou Zhang, Chris Bowen, Yan Zhang   +12 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

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

Investigation of internal action to enhance structural stability and electrochemical performance of K+/Mg2+ co-doped cathodes in high voltage environments utilizing dual coordination

Materials Reports: Energy
Sodium-ion batteries (SIBs) are emerging as a promising alternative for large-scale energy storage, particularly in grid applications. Within the array of potential cathode materials, Fe/Mn-based layered oxides are notable for their advantageous ...
Xuantian Feng, Minjie Hou, Bowen Xu, Yiyong Zhang, Da Zhang, Yun Zeng, Yong Lei, Feng Liang   +7 more
doaj   +1 more source

Book of abstracts of the 16th International Symposium of Croatian Metallurgical Society - SHMD '2023, Materials and metallurgy [PDF]

, 2023
Book of abstracts of the 16th International Symposium of Croatian Metallurgical Society - SHMD '2023, Materials and metallurgy, Zagreb, Croatia, April 20-21, 2023.
Mamuzić, Ilija (ed.)
core  

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

From melt pool to performance: A review of microstructural engineering in the additive manufacturing of nickel-based superalloys

Results in Engineering
This review critically and systematically analyses recent progress in additively manufactured (AM) Ni-based superalloys, mapping processing–microstructure–property linkages relevant to qualification of hot-section hardware in aerospace and energy ...
Hedayat Hamdi, Sadaf Sadatabhari, Atefeh Tajik, Abbas Zarei Hanzaki, Ahmad Hatamiyan, Hamid Reza Abedi   +5 more
doaj   +1 more source

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