Suppr超能文献

用OLi、ONa和LiF分子修饰的六方氮化硼(h-BN)片用于增强储能

Hexagonal Boron Nitride (h-BN) Sheets Decorated with OLi, ONa, and Li F Molecules for Enhanced Energy Storage.

作者信息

Naqvi Syeda Rabab, Rao Gollu Sankar, Luo Wei, Ahuja Rajeev, Hussain Tanveer

机构信息

Condensed Matter Theory Group, Department of Physics and Astronomy, Box 516, Uppsala University, SE-751 20, Uppsala, Sweden.

Department of Physics, University of Basel, Basel-, 4056, Switzerland.

出版信息

Chemphyschem. 2017 Mar 3;18(5):513-518. doi: 10.1002/cphc.201601063. Epub 2017 Jan 18.

Abstract

First-principles electronic structure calculations were carried out on hexagonal boron nitride (h-BN) sheets functionalized with small molecules, such as OLi, ONa, and Li F, to study their hydrogen (H ) storage properties. We found that OLi and ONa strongly adsorb on h-BN sheets with reasonably large inter-adsorbent separations, which is desirable for H storage. Ab initio molecular dynamics (MD) simulations further confirmed the structural stability of OLi-BN and ONa-BN systems at 400 K. On the other hand, Li F molecules form clusters over the surface of h-BN at higher temperatures. We performed a Bader charge investigation to explore the nature of binding between the functionalized molecules and h-BN sheets. The density of states (DOS) revealed that functionalized h-BN sheets become metallic with two-sided coverage of each type of molecules. Hydrogenation of OLi-BN and ONa-BN revealed that the functionalized systems adsorb multiple H molecules around the Li and Na atoms, with H adsorption energies ranging from 0.20 to 0.28 eV, which is desirable for an efficient H storage material.

摘要

对用小分子(如OLi、ONa和LiF)功能化的六方氮化硼(h-BN)片进行了第一性原理电子结构计算,以研究它们的储氢性能。我们发现OLi和ONa以合理的大吸附剂间距强烈吸附在h-BN片上,这对于储氢是有利的。从头算分子动力学(MD)模拟进一步证实了OLi-BN和ONa-BN体系在400 K时的结构稳定性。另一方面,LiF分子在较高温度下在h-BN表面形成团簇。我们进行了巴德电荷研究,以探索功能化分子与h-BN片之间的结合性质。态密度(DOS)表明,每种类型分子的双面覆盖使功能化的h-BN片变成金属。OLi-BN和ONa-BN的氢化表明,功能化体系在Li和Na原子周围吸附多个H分子,H吸附能范围为0.20至0.28 eV,这对于高效储氢材料是有利的。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验