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English(EN) EP-Flow: Disordered Crystal Structure Prediction without Site-Level Annotations

新AI框架可在无位点标注的情况下预测无序晶体结构

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了EP-Flow，一种预测无序晶体结构的新型框架。该方法利用占用分布矩阵（ODM）来表示连续的位点-物种无序性，克服了现有生成器需要位点级别标注或假设确定性占用的局限性。EP-Flow采用边际约束流匹配方法来学习无序模式并生成占用、分数坐标和晶格参数，在无序晶体结构预测基准测试中取得了最先进的性能。 AI

影响 这种新方法通过实现对无序晶体结构更准确的预测，有望加速材料发现。

排序理由 该集群包含一篇详细介绍晶体结构预测新计算方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新AI框架可在无位点标注的情况下预测无序晶体结构

本文如何被排名

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该集群包含一篇详细介绍晶体结构预测新计算方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Qiuliang Liu, Liming Wu, Qi Li, Zhonglong Peng, Chang Chen, Xiaolong Chen, Wenbing Huang, Shifeng Jin ·

    EP-Flow：无需位点级标注的无序晶体结构预测

    arXiv:2610.01315v1 Announce Type: new Abstract: Generative models have made rapid progress in ordered crystal structure prediction, yet many functional materials are intrinsically disordered, with substitutional mixing, vacancies, or interstitial species controlling their propert…

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