Advancing thermodynamic group-contribution methods by machine learning: UNIFAC 2.0

IF 13.3 1区 工程技术 Q1 ENGINEERING, CHEMICAL
Nicolas Hayer, Thorsten Wendel, Stephan Mandt, Hans Hasse, Fabian Jirasek
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引用次数: 0

Abstract

Accurate prediction of thermodynamic properties is pivotal in chemical engineering for optimizing process efficiency and sustainability. Physical group-contribution (GC) methods are widely employed for this purpose but suffer from historically grown, incomplete parameterizations, limiting their applicability and accuracy. In this work, we overcome these limitations by combining GC with matrix completion methods (MCM) from machine learning. We use the novel approach to predict a complete set of pair-interaction parameters for the most successful GC method: UNIFAC, the workhorse for predicting activity coefficients in liquid mixtures. The resulting new method, UNIFAC 2.0, is trained and validated on more than 224,000 experimental data points, showcasing significantly enhanced prediction accuracy (e.g., nearly halving the mean squared error) and increased scope by eliminating gaps in the original model’s parameter table. Moreover, the generic nature of the approach facilitates updating the method with new data or tailoring it to specific applications.

Abstract Image

通过机器学习推进热力学群贡献方法:UNIFAC 2.0
在化学工程中,准确预测热力学性质对于优化工艺效率和可持续性至关重要。物理群贡献(GC)方法被广泛用于此目的,但由于历史上发展的不完整的参数化,限制了它们的适用性和准确性。在这项工作中,我们通过将GC与机器学习中的矩阵补全方法(MCM)相结合来克服这些限制。我们使用这种新方法来预测最成功的气相色谱方法:UNIFAC的完整的对相互作用参数,UNIFAC是预测液体混合物活度系数的主要方法。由此产生的新方法UNIFAC 2.0在超过224,000个实验数据点上进行了训练和验证,显示出显著提高的预测精度(例如,近一半的均方误差),并通过消除原始模型参数表中的空白来扩大范围。此外,该方法的通用特性有助于使用新数据更新方法或将其定制为特定的应用程序。
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来源期刊
Chemical Engineering Journal
Chemical Engineering Journal 工程技术-工程:化工
CiteScore
21.70
自引率
9.30%
发文量
6781
审稿时长
2.4 months
期刊介绍: The Chemical Engineering Journal is an international research journal that invites contributions of original and novel fundamental research. It aims to provide an international platform for presenting original fundamental research, interpretative reviews, and discussions on new developments in chemical engineering. The journal welcomes papers that describe novel theory and its practical application, as well as those that demonstrate the transfer of techniques from other disciplines. It also welcomes reports on carefully conducted experimental work that is soundly interpreted. The main focus of the journal is on original and rigorous research results that have broad significance. The Catalysis section within the Chemical Engineering Journal focuses specifically on Experimental and Theoretical studies in the fields of heterogeneous catalysis, molecular catalysis, and biocatalysis. These studies have industrial impact on various sectors such as chemicals, energy, materials, foods, healthcare, and environmental protection.
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