Machine Learning Thermobarometry for Biotite‐Bearing Magmas
Machine Learning Thermobarometry for Biotite‐Bearing Magmas
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DOI：
10.1029/2022jb024137
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发表时间：
2022-09
期刊：
影响因子：
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通讯作者：
Xiaoyan Li;C. Zhang
中科院分区：
文献类型：
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作者：
Xiaoyan Li;C. Zhang
黑云母(Sensu Lato)是一种广泛存在于岩浆岩中的造岩矿物，可以在很宽的压力和温度范围内保持稳定，但缺乏合适的黑云母温度计或气压计。基于收集的包含广泛组成范围的黑云母的实验数据集(n=839，T=625-1,325°C，P=1-48 kbar)，我们训练了几种机器学习算法来校准黑云母温度气压计。我们对模型性能的评估表明，从极度随机的树木派生的温压计是最好的选择，它返回了决定系数(R2)≥0.97，用于仅使用黑云母或黑云母+熔体模型来估计温度和压力。分别使用三种不同的方法对黑云母和黑云母+熔体温压计的模型可靠性进行了评估，包括蒙特卡罗交叉验证(RMSE分别为65℃和4.7kbar，38℃和3.2kbar)，用独立测试集进行测试(RMSE分别为54℃和4.4kbar，35℃和2.4kbar)，以及假设分析不确定度的误差传播(2*MAD分别为54℃和1.27kbar，10℃和1.26kbar)。温度压力计中相关组分的量化相对重要性支持了对黑云母作为压力和温度函数的稳定性的热力学内在控制。我们将新的黑云母温度压力计应用于含黑云母的安山岩、声橄榄岩和流纹岩火山系统，为岩浆的储存、上升和演化提供了可靠的温度和压力约束。我们还提供了一个用户友好的网页，在线性能的温度气压计(https://lixiaoyan.shinyapps.io/Biotite_thermobarometer/).
Biotite (sensu lato) is a widespread rock‐forming mineral in magmatic rocks that can be stable in a broad range of pressure and temperature, but appropriate biotite thermometers or barometers are lacking. Based on a collected experimental dataset (n = 839, T = 625–1,325°C, P = 1–48 kbar) containing biotites that span a wide compositional range [e.g., Mg/(Mg + Fe) = 0–1, TiO2 = 0–9 wt%], we have trained several machine learning algorithms for calibrating a biotite thermobarometer. Our evaluation on model performance reveals that the thermobarometry derived from extremely randomized trees is the best option, which returns coefficients of determination (R2) ≥0.97 for estimating both temperature and pressure using either biotite‐only or biotite + melt model. The model reliability were evaluated using three different approaches for the biotite‐only and biotite + melt thermobarometers respectively, including Monte Carlo cross‐validation (RMSEs are 65°C and 4.7 kbar, 38°C and 3.2 kbar, respectively), testing with independent test set (RMSEs are 54°C and 4.4 kbar, 35°C and 2.4 kbar, respectively), and error propagation from assumed analytical uncertainty (2*MAD are 54°C and 1.27 kbar, 10°C and 1.26 kbar, respectively). Quantified relative importance of involved components in the thermobarometers supports an intrinsic control of thermodynamics in the stability of biotite as a function of pressure and temperature. We applied the new biotite thermobarometer for biotite‐bearing andesitic, phonolitic and rhyolitic volcanic systems provide reliable constraints of temperature and pressure for magma storage, ascent, and evolution. We also offer a user‐friendly webpage for online performance of the thermobarometers (https://lixiaoyan.shinyapps.io/Biotite_thermobarometer/).