使用铜基催化剂预测 CO2 加氢反应中甲醇产率的硅学模型

IF 2.3 4区 化学 Q3 CHEMISTRY, PHYSICAL
Vanjari Pallavi, Reddi Kamesh, K. Yamuna Rani
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引用次数: 0

摘要

二氧化碳加氢制甲醇有助于减少碳排放,并提供可再生的清洁燃料--甲醇。虽然铜基催化剂已被证明是该反应经济高效的催化剂,但它也存在催化剂效率低和烧结的缺点。在这项研究中,我们开发了六种不同的机器学习(ML)模型,用于预测铜基催化剂在二氧化碳加氢过程中的甲醇产率(%)。梯度提升随机树模型的准确度 R2 和 RMSE 分别为 0.96、0.71(训练数据)和 0.75、1.75(测试数据),优于其他 ML 模型。研究发现,压力、金属与支撑物的比例、活性金属成分、GHSV 和反应温度是影响甲醇产量优化的重要参数。该模型的预测能力也根据不同输入参数的未见实验数据进行了验证,预测结果良好,R2 和 RMSE 分别为 0.9 和 1.14。因此,该模型可视为指导铜基催化剂实验设计的重要解决方案,而无需进行实际实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In Silico Models for Prediction of Methanol Yield in CO2 Hydrogenation Reaction Using Cu-Based Catalysts

CO2 hydrogenation to methanol is instrumental in mitigating carbon emissions and providing a renewable source of clean fuel, methanol. Though Cu-based catalysts proved to be economical and efficient catalysts for this reaction, it has the disadvantage of low catalyst efficiency and sintering. In this study, we developed different six machine learning (ML) models for the prediction of methanol yield (%) from CO2 hydrogenation for Cu-based catalysts. The gradient boost random trees model outperformed other ML models with accuracy R2 and RMSE of 0.96, 0.71 on train data and 0.75, 1.75 on test data. Pressure, metal:support ratio, active metal composition, GHSV and reaction temperature were found to be influential parameters for optimization of methanol yield. The prediction capability of this model is also validated based on unseen experimental data with varied input parameters and the predictions are good enough with R2 and RMSE of 0.9 and 1.14. Therefore, this model can be regarded as a valuable solution to guide experimental design without actual experimentation for Cu-based catalysts.

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来源期刊
Catalysis Letters
Catalysis Letters 化学-物理化学
CiteScore
5.70
自引率
3.60%
发文量
327
审稿时长
1 months
期刊介绍: Catalysis Letters aim is the rapid publication of outstanding and high-impact original research articles in catalysis. The scope of the journal covers a broad range of topics in all fields of both applied and theoretical catalysis, including heterogeneous, homogeneous and biocatalysis. The high-quality original research articles published in Catalysis Letters are subject to rigorous peer review. Accepted papers are published online first and subsequently in print issues. All contributions must include a graphical abstract. Manuscripts should be written in English and the responsibility lies with the authors to ensure that they are grammatically and linguistically correct. Authors for whom English is not the working language are encouraged to consider using a professional language-editing service before submitting their manuscripts.
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