Odbadrakh Tuguldur T, Gale Ariel G, Ball Benjamin T, Temelso Berhane, Shields George C
Department of Chemistry, Furman University.
College of Charleston;
J Vis Exp. 2020 Apr 8(158). doi: 10.3791/60964.
The computational study of the formation and growth of atmospheric aerosols requires an accurate Gibbs free energy surface, which can be obtained from gas phase electronic structure and vibrational frequency calculations. These quantities are valid for those atmospheric clusters whose geometries correspond to a minimum on their potential energy surfaces. The Gibbs free energy of the minimum energy structure can be used to predict atmospheric concentrations of the cluster under a variety of conditions such as temperature and pressure. We present a computationally inexpensive procedure built on a genetic algorithm-based configurational sampling followed by a series of increasingly accurate screening calculations. The procedure starts by generating and evolving the geometries of a large set of configurations using semi-empirical models then refines the resulting unique structures at a series of high-level ab initio levels of theory. Finally, thermodynamic corrections are computed for the resulting set of minimum-energy structures and used to compute the Gibbs free energies of formation, equilibrium constants, and atmospheric concentrations. We present the application of this procedure to the study of hydrated glycine clusters under ambient conditions.
大气气溶胶形成与生长的计算研究需要精确的吉布斯自由能面,这可以通过气相电子结构和振动频率计算获得。这些量对于那些几何结构对应于其势能面最小值的大气团簇是有效的。最低能量结构的吉布斯自由能可用于预测在各种条件(如温度和压力)下该团簇在大气中的浓度。我们提出了一种计算成本低廉的方法,该方法基于基于遗传算法的构型采样,随后进行一系列精度不断提高的筛选计算。该方法首先使用半经验模型生成并演化大量构型的几何结构,然后在一系列高水平的从头算理论水平上优化所得的独特结构。最后,对所得的最低能量结构集计算热力学校正,并用于计算形成吉布斯自由能、平衡常数和大气浓度。我们展示了该方法在环境条件下水合甘氨酸团簇研究中的应用。