English(EN) Towards Automated Discovery: A Review of Generative Models, Multimodal Learning and Closed-Loop Workflows in Inverse Materials Design

综述详述AI在材料发现方面的进展

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-01 17:20

一篇新的综述文章详细介绍了逆向材料设计中生成模型、多模态学习和闭环工作流的进展。文章探讨了各种生成模型类别，如变分自编码器（VAEs）、归一化流和扩散模型，并强调了物理约束的集成方式。文章还讨论了融合不同数据模态和逆向设计策略，同时强调了常见的失败模式和评估实践。 AI

影响这篇综述整合了材料发现领域的最新AI进展，有望加速该领域的研究和开发。

排序理由该集群包含一篇关于AI技术应用于材料科学的综述文章。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

报道来源 [2]

arXiv cs.LG TIER_1 English(EN) · Anand Babu, Rog\'erio Almeida Gouv\^ea, Gian-Marco Rignanese · 2026-06-02 04:00

Towards Automated Discovery: A Review of Generative Models, Multimodal Learning and Closed-Loop Workflows in Inverse Materials Design

arXiv:2606.02507v1 Announce Type: cross Abstract: Inverse materials design is shifting materials discovery from forward prediction to targeted proposal of candidates that satisfy objectives under physical constraints. Here, we review recent advances in generative crystal structur…
arXiv cs.LG TIER_1 English(EN) · Gian-Marco Rignanese · 2026-06-01 17:20

Towards Automated Discovery: A Review of Generative Models, Multimodal Learning and Closed-Loop Workflows in Inverse Materials Design

Inverse materials design is shifting materials discovery from forward prediction to targeted proposal of candidates that satisfy objectives under physical constraints. Here, we review recent advances in generative crystal structure modeling, multimodal learning, and closed-loop d…