Shi Hongbo, Koskinen Pekka, Ramasubramaniam Ashwin
Department of Chemical Engineering, University of Massachusetts , Amherst, Massachusetts 01003, United States.
Department of Physics, University of Jyväskylä , 40014 Jyväskylä, Finland.
J Phys Chem A. 2017 Mar 30;121(12):2497-2502. doi: 10.1021/acs.jpca.7b00701. Epub 2017 Mar 17.
We present a self-consistent charge density-functional tight-binding (SCC-DFTB) parametrization for PtRu alloys, which is developed by employing a training set of alloy cluster energies and forces obtained from Kohn-Sham density-functional theory (DFT) calculations. Extensive simulations of a testing set of PtRu alloy nanoclusters show that this SCC-DFTB scheme is capable of capturing cluster formation energies with high accuracy relative to DFT calculations. The new SCC-DFTB parametrization is employed within a genetic algorithm to search for global minima of PtRu clusters in the range of 13-81 atoms and the emergence of Ru-core/Pt-shell structures at intermediate alloy compositions, consistent with known results, is systematically demonstrated. Our new SCC-DFTB parametrization enables computationally inexpensive and accurate modeling of Pt-Ru clusters that are among the best-performing catalysts in numerous energy applications.
我们提出了一种用于铂钌合金的自洽电荷密度泛函紧束缚（SCC-DFTB）参数化方法，该方法是通过使用从Kohn-Sham密度泛函理论（DFT）计算中获得的合金团簇能量和力的训练集来开发的。对一组铂钌合金纳米团簇测试集的广泛模拟表明，相对于DFT计算，这种SCC-DFTB方案能够高精度地捕捉团簇形成能。新的SCC-DFTB参数化方法被应用于遗传算法中，以搜索13 - 81个原子范围内铂钌团簇的全局最小值，并系统地证明了在中间合金成分下出现的钌核/铂壳结构，这与已知结果一致。我们新的SCC-DFTB参数化方法能够对铂 - 钌团簇进行计算成本低廉且准确的建模，这些团簇是众多能源应用中性能最佳的催化剂之一。
