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  • GitHub - HouGroup InterOptimus: High-throughput simulation for . . .
    Structure pre-optimization by MLIP-predicted interface energy Install pip install InterOptimus integrated machine learning interatomic potentials (MLIPs) including grace-2l chgnet mace orb-models sevenn Details can be find in https: matbench-discovery materialsproject org
  • InterOptimus: An AI-assisted robust workflow for screening ground-state . . .
    We present InterOptimus, an integrated workflow designed to facilitate screening ground-state heterogeneous interfaces between two arbitrary crystals, exemplified by key interfaces in lithium batteries Compared to previous tools, InterOptimus introduces several key innovations
  • InterOptimus · PyPI
    InterOptimus integrated machine learning interatomic potentials (MLIPs) including grace-2l chgnet mace orb-models sevenn Details can be find in https: matbench-discovery materialsproject org
  • InterOptimus: An AI-assisted robust workflow for . . . - ResearchGate
    Here, we employ advanced characterizations and computational studies to elucidate how protons intercalate into the layered structure of NCM, leading to the leaching of Li⁺ and the formation of
  • 侯廷政团队在人工智能加速锂电池材料界面研究领域取得新进展
    为此，清华大学深圳国际研究生院助理教授侯廷政团队与香港城市大学（东莞）助理教授蒋璐合作提出了一种人工智能辅助的晶体界面稳态结构筛选优化工具——InterOptimus。 该工具的算法流程（如图3所示）。 InterOptimus可实现自动化的晶格匹配、端面搜索等过程，并通过对称性分析算法进行等价性去重避免了等价结构重复运算。 作为该工作的亮点，
  • InterOptimus：一种人工智能辅助的强大工作流程，用于筛选锂电 - Book学术
    通过集成通用机器学习原子间势（MLIPs）， InterOptimus能够快速预测界面能量和稳定性，显着降低密度泛函理论（DFT）中必要的计算成本超过90%。 我们在三个关键的锂电池界面，Li2S|Ni3S2， LiF|NCM和Li3PS4|Li上对几种MLIPs进行了基准测试，并证明MLIPs在建模势能面和排序界面稳定性方面达到了与DFT相当的精度。 因此，InterOptimus促进了基态非均相界面结构的有效确定和后续结构-性能关系的研究，加速了新型电池材料的界面工程。 本文章由计算机程序翻译，如有差异，请以英文原文为准。
  • InterOptimus: An AI-assisted robust workflow for screening ground-state . . .
    Xie Y et al InterOptimus: An AI-assisted robust workflow for screening ground-state heterogeneous interface structures in lithium batteries Journal of Energy Chemistry 2025 Vol 106 pp 631-641
  • InterOptimus README. md at master · HouGroup InterOptimus - GitHub
    An efficient python package for Interface Simulation Structure pre-optimization by CHGNet-predicted interface energy Install pip install
  • Hou Group @ Tsinghua SIGS - GitHub
    Using this package, one can get the predicted potential energy for any structure using any MLIP without needing to change python environments
  • InterOptimus
    Welcome to a brand new web home of InterOptimus Trade Solutions! We are working on our new site and we hope to make it available by September 2013 Thank you for visiting us and we hope that you will come back soon





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