用于甲烷氧化偶联的多组分 La2O3 催化剂的高通量筛选和文献数据驱动的机器学习辅助研究,Catalysis Science & Technology

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用于甲烷氧化偶联的多组分 La2O3 催化剂的高通量筛选和文献数据驱动的机器学习辅助研究
Catalysis Science & Technology ( IF 4.4 ) Pub Date : 2022-02-10 , DOI: 10.1039/d1cy02206g
Shun Nishimura ₁ , Son Dinh Le ₁ , Itsuki Miyazato ₂ , Jun Fujima ₂ , Toshiaki Taniike ₁ , Junya Ohyama ₃ , Keisuke Takahashi ₂

Affiliation

在此，基于高通量筛选 (HTS) 和文献数据集以及包括随机森林回归在内的多输出机器学习 (ML) 方法设计了用于甲烷氧化耦合 (OCM) 的多组分 La ₂ O ₃基催化剂。 RFR)、支持向量回归 (SVR)、高斯过程回归 (贝叶斯) 和项集挖掘 (LCM)。_{HTS数据和SVR的联合使用先后在20个C 2}验证中辅助搜索了11种多组分La ₂ O ₃基OCM催化剂基于间接 ML 辅助，在 450°C 时出现的产率。从 ML 预测的适当多组分有助于确定基于 La ₂ O ₃的 OCM 催化剂的较低起始温度的特征。SVR 扩展 HTS 数据区的 LCM 应用支持了对 HTS 区有效元素的观察。然而，一个具有挑战性的主题仍然存在，即，从 20 种选定类型的催化剂验证中推断，两种类型的多组分 La ₂ O ₃基催化剂在 450 ℃下提供了有效的 C _{2产率（>5.0%）。}因此，预测独特的多组分 La ₂ O ₃基于 OCM 催化剂进一步，HTS 和文献数据的组合被应用于四种 ML 方法。这有助于在 38 种选定类型的预测中发现 17 种额外的多组分 La ₂ O ₃基催化剂组合，在 450 °C下提供有效的 C _{2产率（>5.0%）。}基于 HTS 驱动的间接 ML 辅助，共发现30 种新型多组分 La ₂ O ₃基催化剂，在 CH ₄ /O _{2 = 2.0 条件下 450 ℃时 C}₂产率大于 5.0%和文献资料。

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High-throughput screening and literature data-driven machine learning-assisted investigation of multi-component La2O3-based catalysts for the oxidative coupling of methane

Herein, multi-component La₂O₃-based catalysts for the oxidative coupling of methane (OCM) were designed based on high-throughput screening (HTS) and literature datasets with multi-output machine learning (ML) approaches including random forest regression (RFR), support vector regression (SVR), Gaussian process regression (Bayesian), and itemset mining (LCM). The combined use of HTS data and SVR successively assisted the search for 11 types of multi-component La₂O₃-based OCM catalysts in 20 validations with C₂ yields appearing at 450 °C based on indirect ML assistance. The appropriate multi-component predicted from ML contributed to the determination of a characteristic feature of the lower onset temperature for an La₂O₃-based OCM catalyst. The LCM application on the SVR extended HTS data area supported the observation of the effective elements in the HTS area. However, a challenging subject remains, i.e., 2 types of multi-component La₂O₃-based catalysts afforded an effective C₂ yield (>5.0%) at 450 °C, as inferred from the 20 selected types of catalyst validation. Thus, to predict unique multi-component La₂O₃-based OCM catalysts further, a combination of HTS and literature data was applied for four ML approaches. This was helpful to discover 17 additional combinations of multi-component La₂O₃-based catalysts affording effective C₂ yields (>5.0%) at 450 °C in the 38 selected types of predictions. In total, 30 new types of multi-component La₂O₃-based catalysts with a C₂ yield greater than 5.0% at 450 °C in CH₄/O₂ = 2.0 condition were found based on the indirect ML assistance driven by HTS and literature data.

更新日期：2022-02-10

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