Lattice thermal conductivity (klat) of mantle minerals is a key factor in determining the Earth's energy budget and influences its dynamic processes. Here, we trained a neuroevolution machine learning potential for CaSiO3 perovskite (CaPv), the third most abundant mineral of the lower mantle, to investigate the klat of pyrolitic aggregates at the core–mantle boundary (CMB). We show that the klat of two types of pyrolitic aggregates has increased by 7% and 5% upon the addition of CaPv, demonstrating its significance in shaping the thermal structure of Earth's interior. Considering other mantle minerals and iron content, as well as the global distribution of temperature, we evaluated the heat flow across the CMB to be 7.98 ± 0.4 TW. The estimated heat flow is inconsistent with the value derived from the Fe alloy, which might suggest the presence of a thermally or chemically stratified layer atop the outer core.

中文翻译：

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具有神经进化潜力的 CaSiO3 钙钛矿热导率的大规模模拟


地幔矿物的晶格热导率（klat）是决定地球能量收支并影响其动态过程的关键因素。在这里，我们训练了 CaSiO3 钙钛矿 (CaPv)（下地幔第三丰富的矿物）的神经进化机器学习潜力，以研究地核-地幔边界 (CMB) 处热解聚集体的 klat。我们发现，添加 CaPv 后，两种热解聚集体的 klat 分别增加了 7% 和 5%，这证明了其在塑造地球内部热结构方面的重要性。考虑到其他地幔矿物和铁含量，以及全球温度分布，我们评估穿过 CMB 的热流为 7.98 ± 0.4 TW。估计的热流与铁合金得出的值不一致，这可能表明外核顶部存在热或化学分层层。