人工晶体学报2026，Vol.55Issue(3)：327-330,4.DOI:10.16553/j.cnki.issn1000-985x.2026.0001
功能材料的生成式设计:MatterGen的突破与展望
Generative Design of Functional Materials:Breakthroughs and Prospects of MatterGen
摘要
Abstract
Traditional material discovery methods,including experimental trial-and-error and high-throughput screening,are constrained by database scalability,hindering efficient exploration of the vast chemical space.Generative artificial intelligence(AI)is revolutionizing materials science by enabling a new paradigm for the inverse design of functional materials.This paper centers on the landmark work published in Nature—the MatterGen generative model,detailing its diffusion model-based approach for achieving stable and controllable inorganic crystal material generation.MatterGen not only generates diverse and stable crystal structures across the periodic table but also facilitates conditional generation with fine-tuning for target chemical compositions,spatial symmetries,and multiple performance constraints(e.g.,mechanical,electrical,and magnetic properties).By examining the technical principles,performance advantages,and experimental validation of MatterGen,this paper illustrates how generative models are transforming material design from"screening"to"creation",while also discussing the challenges and future development trends of this technology.关键词
逆向设计/生成式人工智能/扩散模型/晶体生成/功能材料Key words
reverse design/generative artificial intelligence/diffusion model/crystal generation/functional material分类
通用工业技术引用本文复制引用
马凤凯,张裕祥,李真,张晨波,陈振强,徐军,苏良碧..功能材料的生成式设计:MatterGen的突破与展望[J].人工晶体学报,2026,55(3):327-330,4.基金项目
国家自然科学基金(62475104,61905289) （62475104,61905289）
广东省稀土开发及应用研究重点实验室开放基金(XTKY-202402) （XTKY-202402）
