金属二聚体掺杂h-BN结构作为新型敏感气体传感器的ADFT研究

IF 4.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
H. Cruz-Martínez, H. Rojas-Chávez, L. Santiago-Silva, L. López-Sosa, P. Calaminici
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引用次数: 0

摘要

有毒气体的监测和检测是减少公共卫生问题的根本。因此,在这项工作中,为了探索新兴的传感器材料,采用辅助密度泛函理论(ADFT)研究了3d金属二聚体掺杂六方氮化硼(h-BN)结构作为新型CO和NO气体传感器。首先,测定了沉积在缺陷h-BN上的Co2、Ni2和Cu2二聚体的稳定性。然后,研究了3d金属二聚体掺杂h-BN结构对NO和CO气体的敏感性。结果表明,嵌入在缺陷h-BN上的3d-金属二聚体的相互作用能高于沉积在原始h-BN结构上的相互作用能,表明3d-金属二聚体在缺陷h-BN上具有良好的稳定性。此外,本研究表明,在3d金属二聚体掺杂的h-BN结构上,CO和NO的吸附能高于文献中对原始h-BN结构的计算。因此,本文考虑的3d金属二聚体掺杂h-BN结构可以作为有毒CO和NO气体检测的良好候选者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Metal Dimers-Doped h-BN Structures as Novel Toxic Gases Sensors With Enhanced Sensitivity Properties: An ADFT Study

Metal Dimers-Doped h-BN Structures as Novel Toxic Gases Sensors With Enhanced Sensitivity Properties: An ADFT Study

Toxic gases monitoring and detection are fundamental to lessening public health problems. Therefore, in this work, to explore emergent sensor materials, 3d-metal dimers-doped hexagonal boron nitride (h-BN) structures were investigated employing auxiliary density functional theory (ADFT) as novel CO and NO gas sensors. Firstly, the stabilities of Co2, Ni2, and Cu2 dimers deposited on defective h-BN were determined. Then, sensitivities of 3d-metal dimers-doped h-BN structures towards the NO and CO gases were investigated. It was found that the interaction energies of these 3d-metal dimers embedded on defective h-BN are higher than those deposited on pristine h-BN structure, which indicates that the 3d-metal dimers exhibit good stability on defective h-BN. Moreover, this work demonstrated that the CO and NO adsorption energies on 3d-metal dimers-doped h-BN structures are higher than those computed in the literature for pristine h-BN structure. Consequently, the here considered 3d-metal dimers-doped h-BN structures can be good candidates for toxic CO and NO gas detection.

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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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