English(EN) Benchmark Dataset for Catalysis on 2D MXenes

新的机器学习数据集加速二维MXenes催化研究

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-02 04:00

研究人员开发了一个新的基准数据集和机器学习模型，以加速二维MXenes的催化研究。通过结合密度泛函理论计算和机器学习原子间势，他们在预测原子力和形成能方面实现了显著的加速。这种方法通过EquiformerV2和MACE等模型进行了验证，保持了高精度，并有望更有效地探索MXene的催化性能。 AI

影响通过实现更快的模拟，加速了新型催化材料的发现。

排序理由该集群包含一篇学术论文，详细介绍了用于材料科学研究的新基准数据集和机器学习模型。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Pavlo Melnyk, Anmar Karmush, M{\aa}rten Wadenb\"ack, Ania Beatriz Rodr\'iguez-Barrera, Johanna Rosen, Michael Felsberg, Jonas Bj\"ork · 2026-06-02 04:00

用于二维MXene催化的基准数据集

arXiv:2606.00794v1 Announce Type: cross Abstract: Merging first-principles calculations with machine learning (ML), we aim to accelerate the exploration of catalytic behaviour in novel materials. We focus on two-dimensional (2D) Ti$_2$CT$_y$ MXenes, whose versatile surface chemis…