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H·(H2O)n 簇合物:通过分子从头算梯度嵌入遗传算法(GEGA)对氢原子的微溶剂化作用。

H·(H2O)n clusters: microsolvation of the hydrogen atom via molecular ab initio gradient embedded genetic algorithm (GEGA).

机构信息

Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095-1569, USA.

出版信息

J Phys Chem A. 2010 Dec 9;114(48):12591-9. doi: 10.1021/jp1092543. Epub 2010 Nov 15.

Abstract

A new version of the ab initio gradient embedded genetic algorithm (GEGA) program for finding the global minima on the potential energy surface (PES) of mixed clusters formed by molecules and atoms is reported. The performance of the algorithm is demonstrated on the neutral H·(H(2)O)(n) (n = 1-4) clusters, that is, a radical H atom solvated in 1-4 water molecules. These clusters are of a fundamental interest. The solvated hydrogen atom forms during photochemical events in water, or during scavenging of solvated electrons by acids, and transiently exists in biological systems and possibly in inclusion complexes in the deep ocean and in the ice shield of earth. The processes associated with its existence are intriguingly complex, however, and have been the subject of decades-long debates. Using GEGA, we explicate the apparently extreme structural diversity in the H·(H(2)O)(n) (n = 1-4) clusters. All considered clusters have four basic structural types: type I, where the H radical is weakly coordinated to the oxygen atom of one of the water molecules; type II, where H is weakly coordinated to a H atom of one of the water molecules; type III, consisting of H(2), the OH radical, and n - 1 H(2)O molecules; and type IV, consisting of H(3)O and n - 1 H(2)O. There are myriads of isomers of all four types. The lowest energy species of types I and II are the isoenergetic global minima. H·(H(2)O)(n) clusters appear to be a challenging case for GEGA because they have many shallow minima close in energy some of which are significantly less stable than the global minimum. Additionally, the global minima themselves have high structural degeneracy, they are only weakly bound, and they are prone to dissociation. GEGA performed exceptionally well in finding both the global and the low-energy local minima that were subsequently confirmed at higher levels of theory.

摘要

报告了一个新的从头算梯度嵌入遗传算法(GEGA)程序版本,用于在分子和原子混合团簇的势能表面(PES)上寻找全局最小值。该算法的性能在中性 H·(H(2)O)(n)(n=1-4)团簇上得到了验证,即自由基 H 原子溶解在 1-4 个水分子中。这些团簇具有基本的研究意义。溶解的氢原子在水中的光化学事件中形成,或者在酸中捕获溶剂化电子时形成,并在生物系统中短暂存在,可能存在于深海中的包合物和地球冰盾中。然而,与它的存在相关的过程非常复杂,并且已经成为数十年争论的主题。使用 GEGA,我们详细说明了 H·(H(2)O)(n)(n=1-4)团簇中明显的极端结构多样性。所有考虑的团簇都有四种基本结构类型:I 型,其中 H 自由基与一个水分子的氧原子弱配位;II 型,其中 H 与一个水分子的 H 原子弱配位;III 型,由 H(2)、OH 自由基和 n-1 个 H(2)O 分子组成;IV 型,由 H(3)O 和 n-1 个 H(2)O 组成。所有四种类型都有无数的异构体。I 型和 II 型的最低能量物种是等能量的全局最小值。H·(H(2)O)(n)团簇似乎是 GEGA 的一个具有挑战性的案例,因为它们有许多能量相近的浅局域最小值,其中一些比全局最小值稳定得多。此外,全局最小值本身具有高结构简并性,它们的结合力较弱,容易解离。GEGA 在寻找全局和低能局域最小值方面表现出色,随后在更高的理论水平上得到了证实。

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