Gould Tim, Dale Stephen G
Qld Micro- and Nanotechnology Centre, Griffith University, Nathan, Qld 4111, Australia.
Phys Chem Chem Phys. 2022 Mar 16;24(11):6398-6403. doi: 10.1039/d2cp00268j.
Large benchmark sets like GMTKN55 [Goerigk , , 2017, , 32184] let us analyse the performance of density functional theory over a diverse range of systems and bonding types. However, assessing over a large and diverse set can miss cases where approaches fail badly, and can give a misleading sense of security. To this end we introduce a series of 'poison' benchmark sets, P30-5, P30-10 and P30-20, comprising systems with up to 5, 10 and 20 atoms, respectively. These sets represent the most difficult-to-model systems in GMTKN55. We expect them to be useful in developing new approximations, identifying weak points in existing ones, and to aid in selecting appropriate DFAs for computational studies involving difficult physics, catalysis.
像GMTKN55 [戈里格克，，2017，，32184]这样的大型基准集使我们能够分析密度泛函理论在各种不同系统和键合类型上的性能。然而，在一个庞大且多样的集合上进行评估可能会遗漏方法严重失败的情况，并且可能会给人一种误导性的安全感。为此，我们引入了一系列“有毒”基准集，P30 - 5、P30 - 10和P30 - 20，分别包含最多5、10和20个原子的系统。这些集合代表了GMTKN55中最难建模的系统。我们期望它们在开发新的近似方法、识别现有方法的弱点以及帮助为涉及困难物理、催化的计算研究选择合适的密度泛函近似方面有用。
