Blasius Jan, Zaby Paul, Dölz Jürgen, Kirchner Barbara
Mulliken Center for Theoretical Chemistry, Institute for Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4+6, 53115 Bonn, Germany.
Institute for Numerical Simulation, University of Bonn, Friedrich-Hirzebruch-Allee 7, 53115 Bonn, Germany.
J Chem Phys. 2022 Jul 7;157(1):014505. doi: 10.1063/5.0093057.
In this work, we investigate how uncertainties in experimental input data influence the results of quantum cluster equilibrium calculations. In particular, we focus on the calculation of vaporization enthalpies and entropies of seven organic liquids, compare two computational approaches for their calculation, and investigate how these properties are affected by changes in the experimental input data. It is observed that the vaporization enthalpies and entropies show a smooth dependence on changes in the reference density and boiling point. The reference density is found to have only a small influence on the vaporization thermodynamics, whereas the boiling point has a large influence on the vaporization enthalpy but only a small influence on the vaporization entropy. Furthermore, we employed the Gauss--Hermite estimator in order to quantify the uncertainty in thermodynamic functions that stems from inaccuracies in the experimental reference data for the example of the vaporization enthalpy of (R)-butan-2-ol. We quantify the uncertainty as 30.95 · 10 kJ mol. In addition, we compare the convergence behavior and computational effort of the Gauss-Hermite estimator with the Monte Carlo approach and show the superiority of the former. Using this study, we present how uncertainty quantification can be applied to examples from theoretical chemistry.
在这项工作中，我们研究了实验输入数据中的不确定性如何影响量子团簇平衡计算的结果。具体而言，我们专注于七种有机液体汽化焓和熵的计算，比较了两种用于计算它们的计算方法，并研究了这些性质如何受到实验输入数据变化的影响。结果表明，汽化焓和熵对参考密度和沸点的变化呈现出平滑的依赖性。发现参考密度对汽化热力学的影响较小，而沸点对汽化焓有较大影响，但对汽化熵的影响较小。此外，我们以(R)-丁-2-醇的汽化焓为例，采用高斯-埃尔米特估计器来量化源于实验参考数据不准确的热力学函数中的不确定性。我们将不确定性量化为30.95·10 kJ/mol。此外，我们将高斯-埃尔米特估计器的收敛行为和计算工作量与蒙特卡罗方法进行了比较，并展示了前者的优越性。通过这项研究，我们展示了不确定性量化如何应用于理论化学的实例。
