航空材料学报2026，Vol.46Issue(5)：119-147,29.DOI:10.11868/j.issn.1005-5053.2026.000045
人工智能驱动高性能钛基材料设计与制造的研究进展:机遇与挑战
Research progress on artificial intelligence-driven design and manufacturing of high-performance titanium-based materials:opportunities and challenges
摘要
Abstract
Due to the sensitivity and complexity of the composition-process-microstructure-performance relationship,the research and development of high-performance titanium-based materials have long been constrained by the dual challenges of high-dimensional nonlinear optimization and high trial-and-error costs.As a highly pervasive disruptive technology,artificial intelligence(AI)is introducing a new research and development paradigm for the strategic field of high-performance titanium-based materials,shifting from experience-driven modes to dual-driven approaches supported by models and data.This review summarizes the latest research advances in artificial intelligence-enabled high-performance titanium-based material technology(AI+Ti),focusing on how AI provides innovative solutions targeting the inherent characteristics of high-performance titanium-based materials,including complex compositions,diverse phase transitions,narrow thermal processing windows,and strong path dependence of microstructure evolution.The main contents include breakthroughs achieved by AI in constructing high-precision phase diagram and performance prediction models,as well as realizing the inverse design from performance objectives to microstructures and further to composition and processing parameters;the intelligent upgrading from forming control to active regulation of microstructures and properties in key processes such as additive manufacturing and heat treatment;and the establishment of an in-service behavior prediction framework based on digital twins.On this basis,this paper further analyzes the core challenges in the AI+Ti field regarding data,models,verification and integration,and prospects future development directions such as physics-informed machine learning and autonomous experimental platforms.Finally,it discusses controversial issues involving knowledge representation,human-machine collaboration modes and engineering trust establishment,and elaborates on the future development trends of this field:(1)material performance prediction and multi-scale coupling under complex service environments;(2)intelligent coordination of full-process processing parameters;(3)the construction and iteration of specialized physics-informed perception models for titanium alloys.Beyond simple tool application,AI+Ti has evolved into a transformative revolution that enables in-depth understanding and ultimate mastery of the cognition and research paradigm for high-performance titanium-based materials.关键词
高性能钛基材料/人工智能/机器学习/材料设计/智能制造/发展挑战Key words
high-performance titanium-based material/artificial intelligence/machine learning/material design/intelligent manufacturing/development challenge分类
矿业与冶金引用本文复制引用
弭光宝,李培杰,王新宇,唐堰清,成浩,孙若晨,孙圆治,邱越海,谭勇,陈义斯,隋楠,肖文龙..人工智能驱动高性能钛基材料设计与制造的研究进展:机遇与挑战[J].航空材料学报,2026,46(5):119-147,29.基金项目
国家自然科学基金"叶企孙"科学基金(U2141222) （U2141222）
