研究论文
Review: Recent progress in titanium alloys development via machine learning and high-throughput preparation
Feiyang Gao, Weiwen Zhang, Xiaotao Liu, Xuan Luo, Zhi Wang, Ning Li, L.H. Liu
South China University of Technology Huazhong University of Science and Technology
来源Journal of Materials Science
年份2025
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逐年被引趋势
320
326
关键指标
3
被引次数 · OpenAlex
0.77
领域内被引倍数
同类平均 = 1
同类平均 = 1
前 32%
引用位次
同领域 · 同年份 · 同类型
同领域 · 同年份 · 同类型
216
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学术脉络
学科主题
材料 / 化学Titanium Alloys Microstructure and Properties
Machine Learning in Materials Science · Additive Manufacturing Materials and Processes
参考文献 216
Mechanism in the β phase evolution during hot deformation of Ti–5Al–2Sn–2Zr–4Mo–4Cr with a transformed microstructure
被引 137Lian Li, M.Q. Li, Jiao Luo · Acta Materialia · 2015
Mining data with random forests: current options for real‐world applications
被引 290Andreas Ziegler, Inke R. König · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · 2013
Ultralow-fatigue shape memory alloy films
被引 513Christoph Chluba, Wenwei Ge, Rodrigo Lima de Miranda · Science · 2015
此处列出前 3 条
引用本文 3
Machine learning-assisted exploration and experimental assessment of β-type Ti54-xZr15Nb14Mo17Cux alloy with an ultra-low modulus for orthopedic applications
被引 1JianTao Liu, Ni Jin, Y. Y. Zhang · Journal of Materials Science · 2026
Artificial Intelligence, Machine Learning, and High-Throughput Material Discovery Tools
被引 0Praveen Kumar Verma, Hitesh Vasudev · World sustainability series · 2026
Machine learning for titanium alloy development: Composition design, process optimization, microstructure informatics, and performance prediction
被引 0Chenxuan Liu, Mingxuan Ling, Chen Luo · Journal of Materials Research and Technology · 2026
按被引量排序，此处列出前 3 条