Results 81 to 90 of about 1,905 (201)

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

Precipitation‐Modulated Harmonic Architectures Enable Superior Strength–Ductility Synergy from Cryogenic to Elevated Temperatures in Nanostructured Alloys

Advanced Science, EarlyView.
Precipitation‐modulated recrystallization enables a programmable bimodal harmonic architecture in a high‐entropy alloy, delivering 1–2 GPa yield strength with >10% ductility from −196 °C to 700 °C. The resulting broad‐temperature robustness arises from the synergy of dual‐mode nanoprecipitation, harmonic core–shell topology, and temperature‐adaptive ...
Wei Li, Liangyin Xiong, Mengchao Niu, Junhua Luan, Wei Wang, Zengbao Jiao   +5 more
wiley   +1 more source

About the choice of Tungsten carbide indenter to determine mechanical properties of superalloys by using high-temperature microhardness tester

Acta Polytechnica CTU Proceedings
In the aeronautical field, materials are used in severe environmental conditions (temperature, atmosphere), particularly in engine applications. In order to qualify mechanical properties of new composition Ni-based superalloys, ONERA performs Vickers ...
Bruno Passilly, Amélie Kardache
doaj   +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

Research progress in effect of static magnetic field on microstructure of directionally solidified Ni-based superalloy

Cailiao gongcheng, 2019
The current research progress in the influence of static magnetic field on the microstructures of directionally solidified Ni-based superalloy at home and abroad was reviewed, and the effect of different ways, strength of static magnetic fields on the ...
LIU Cheng-lin, SU Hai-jun, ZHANG Jun, LIU Lin, FU Heng-zhi   +4 more
doaj   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

Advanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao, Junkang Wu, Jie Su, Fuzhu Wang, Zi Wang, Li Wang, Liming Tan, Lan Huang, Feng Liu, Yong Liu   +9 more
wiley   +1 more source

Progress on modeling and simulation of directional solidification of superalloy turbine blade casting [PDF]

China Foundry, 2012
Directional solidified turbine blades of Ni-based superalloy are widely used as key parts of the gas turbine engines. The mechanical properties of the blade are greatly influenced by the final microstructure and the grain orientation determined directly ...
Xu Qingyan, Liu Baicheng, Pan Dong
doaj  

Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning

Advanced Intelligent Systems, EarlyView.
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang, Zichao Wang, Zhiwei He, Qingquan Wei, Yong Zuo, Linzhen Nie, Zhishuai Yin   +6 more
wiley   +1 more source

Solar Fuels Via Methane Valorization: Thermochemical Pathways, Unified Metrics, and Techno‐Economic Perspectives

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A first‐of‐its‐kind review benchmarks three solar methane valorization pathways with unified performance metrics for clean fuel production. Meeting global climate targets and sustainable energy demands requires carbon‐neutral fuels and innovative conversion pathways.
Muhammad Abdulmoez, Amjad Othman, Majid Linjawi, Amro Al‐Qutub   +3 more
wiley   +1 more source